“Eventually, my dream would be to simulate a virtual cell.”—Demis Hassabis

The aspiration to build the virtual cell is considered to be equivalent to a moonshot for digital biology. Recently, 42 leading life scientists published a paper in Cell on why this is so vital, and how it may ultimately be accomplished. This conversation is with 2 of the authors, Charlotte Bunne, now at EPFL and Steve Quake, a Professor at Stanford University, who heads up science at the Chan-Zuckerberg Initiative

The audio (above) is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.

TRANSCRIPT WITH LINKS TO AUDIO

Eric Topol (00:06):

Hello, it's Eric Topol with Ground Truths and we've got a really hot topic today, the virtual cell. And what I think is extraordinarily important futuristic paper that recently appeared in the journal Cell and the first author, Charlotte Bunne from EPFL, previously at Stanford’s Computer Science. And Steve Quake, a young friend of mine for many years who heads up the Chan Zuckerberg Initiative (CZI) as well as a professor at Stanford. So welcome, Charlotte and Steve.

Steve Quake (00:42):

Thanks, Eric. It's great to be here.

Charlotte Bunne:

Thanks for having me.

Eric Topol (00:45):

Yeah. So you wrote this article that Charlotte, the first author, and Steve, one of the senior authors, appeared in Cell in December and it just grabbed me, “How to build the virtual cell with artificial intelligence: Priorities and opportunities.” It's the holy grail of biology. We're in this era of digital biology and as you point out in the paper, it's a convergence of what's happening in AI, which is just moving at a velocity that's just so extraordinary and what's happening in biology. So maybe we can start off by, you had some 42 authors that I assume they congregated for a conference or something or how did you get 42 people to agree to the words in this paper?

Steve Quake (01:33):

We did. We had a meeting at CZI to bring community members together from many different parts of the community, from computer science to bioinformatics, AI experts, biologists who don't trust any of this. We wanted to have some real contrarians in the mix as well and have them have a conversation together about is there an opportunity here? What's the shape of it? What's realistic to expect? And that was sort of the genesis of the article.

Eric Topol (02:02):

And Charlotte, how did you get to be drafting the paper?

Charlotte Bunne (02:09):

So I did my postdoc with Aviv Regev at Genentech and Jure Leskovec at CZI and Jure was part of the residency program of CZI. And so, this is how we got involved and you had also prior work with Steve on the universal cell embedding. So this is how everything got started.

Eric Topol (02:29):

And it's actually amazing because it's a who's who of people who work in life science, AI and digital biology and omics. I mean it's pretty darn impressive. So I thought I'd start off with a quote in the article because it kind of tells a story of where this could go. So the quote was in the paper, “AIVC (artificial intelligence virtual cell) has the potential to revolutionize the scientific process, leading to future breakthroughs in biomedical research, personalized medicine, drug discovery, cell engineering, and programmable biology.” That's a pretty big statement. So maybe we can just kind of toss that around a bit and maybe give it a little more thoughts and color as to what you were positing there.

Steve Quake (03:19):

Yeah, Charlotte, you want me to take the first shot at that? Okay. So Eric, it is a bold claim and we have a really bold ambition here. We view that over the course of a decade, AI is going to provide the ability to make a transformative computational tool for biology. Right now, cell biology is 90% experimental and 10% computational, roughly speaking. And you've got to do just all kinds of tedious, expensive, challenging lab work to get to the answer. And I don't think AI is going to replace that, but it can invert the ratio. So within 10 years I think we can get to biology being 90% computational and 10% experimental. And the goal of the virtual cell is to build a tool that'll do that.

Eric Topol (04:09):

And I think a lot of people may not understand why it is considered the holy grail because it is the fundamental unit of life and it's incredibly complex. It's not just all the things happening in the cell with atoms and molecules and organelles and everything inside, but then there's also the interactions the cell to other cells in the outside tissue and world. So I mean it's really quite extraordinary challenge that you've taken on here. And I guess there's some debate, do we have the right foundation? We're going to get into foundation models in a second. A good friend of mine and part of this whole I think process that you got together, Eran Segal from Israel, he said, “We're at this tipping point…All the stars are aligned, and we have all the different components: the data, the compute, the modeling.” And in the paper you describe how we have over the last couple of decades have so many different data sets that are rich that are global initiatives. But then there's also questions. Do we really have the data? I think Bo Wang especially asked about that. Maybe Charlotte, what are your thoughts about data deficiency? There's a lot of data, but do you really have what we need before we bring them all together for this kind of single model that will get us some to the virtual cell?

Charlotte Bunne (05:41):

So I think, I mean one core idea of building this AIVC is that we basically can leverage all experimental data that is overall collected. So this also goes back to the point Steve just made. So meaning that we basically can integrate across many different studies data because we have AI algorithms or the architectures that power such an AIVC are able to integrate basically data sets on many different scales. So we are going a bit away from this dogma. I'm designing one algorithm from one dataset to this idea of I have an architecture that can take in multiple dataset on multiple scales. So this will help us a bit in being somewhat efficient with the type of experiments that we need to make and the type of experiments we need to conduct. And again, what Steve just said, ultimately, we can very much steer which data sets we need to collect.

Charlotte Bunne (06:34):

Currently, of course we don't have all the data that is sufficient. I mean in particular, I think most of the tissues we have, they are healthy tissues. We don't have all the disease phenotypes that we would like to measure, having patient data is always a very tricky case. We have mostly non-interventional data, meaning we have very limited understanding of somehow the effect of different perturbations. Perturbations that happen on many different scales in many different environments. So we need to collect a lot here. I think the overall journey that we are going with is that we take the data that we have, we make clever decisions on the data that we will collect in the future, and we have this also self-improving entity that is aware of what it doesn't know. So we need to be able to understand how well can I predict something on this somewhat regime. If I cannot, then we should focus our data collection effort into this. So I think that's not a present state, but this will basically also guide the future collection.

Eric Topol (07:41):

Speaking of data, one of the things I think that's fascinating is we saw how AlphaFold2 really revolutionized predicting proteins. But remember that was based on this extraordinary resource that had been built, the Protein Data Bank that enabled that. And for the virtual cell there's no such thing as a protein data bank. It's so much more as you emphasize Charlotte, it's so much dynamic and these perturbations that are just all across the board as you emphasize. Now the human cell atlas, which currently some tens of millions, but going into a billion cells, we learned that it used to be 200 cell types. Now I guess it's well over 5,000 and that we have 37 trillion cells approximately in the average person adult's body is a formidable map that's being made now. And I guess the idea that you're advancing is that we used to, and this goes back to a statement you made earlier, Steve, everything we did in science was hypothesis driven. But if we could get computational model of the virtual cell, then we can have AI exploration of the whole field. Is that really the nuts of this?

Steve Quake (09:06):

Yes. A couple thoughts on that, maybe Theo Karaletsos, our lead AI person at CZI says machine learning is the formalism through which we understand high dimensional data and I think that's a very deep statement. And biological systems are intrinsically very high dimensional. You've got 20,000 genes in the human genome in these cell atlases. You're measuring all of them at the same time in each single cell. And there's a lot of structure in the relationships of their gene expression there that is just not evident to the human eye. And for example, CELL by GENE, our database that collects all the aggregates, all of the single cell transcriptomic data is now over a hundred million cells. And as you mentioned, we're seeing ways to increase that by an order of magnitude in the near future. The project that Jure Leskovec and I worked on together that Charlotte referenced earlier was like a first attempt to build a foundational model on that data to discover some of the correlations and structure that was there.

Steve Quake (10:14):

And so, with a subset, I think it was the 20 or 30 million cells, we built a large language model and began asking it, what do you understand about the structure of this data? And it kind of discovered lineage relationships without us teaching it. We trained on a matrix of numbers, no biological information there, and it learned a lot about the relationships between cell type and lineage. And that emerged from that high dimensional structure, which was super pleasing to us and really, I mean for me personally gave me the confidence to say this stuff is going to work out. There is a future for the virtual cell. It's not some made up thing. There is real substance there and this is worth investing an enormous amount of CZIs resources in going forward and trying to rally the community around as a project.

Eric Topol (11:04):

Well yeah, the premise here is that there is a language of life, and you just made a good case that there is if you can predict, if you can query, if you can generate like that. It is reminiscent of the famous Go game of Lee Sedol, that world champion and how the machine came up with a move (Move 37) many, many years ago that no human would've anticipated and I think that's what you're getting at. And the ability for inference and reason now to add to this. So Charlotte, one of the things of course is about, well there's two terms in here that are unfamiliar to many of the listeners or viewers of this podcast, universal representations (UR) and virtual instrument (VIs) that you make a pretty significant part of how you are going about this virtual cell model. So could you describe that and also the embeddings as part of the universal representation (UR) because I think embeddings, or these meaningful relationships are key to what Steve was just talking about.

Charlotte Bunne (12:25):

Yes. So in order to somewhat leverage very different modalities in order to leverage basically modalities that will take measurements across different scales, like the idea is that we have large, may it be transformer models that might be very different. If I have imaging data, I have a vision transformer, if I have a text data, I have large language models that are designed of course for DNA then they have a very wide context and so on and so forth. But the idea is somewhat that we have models that are connected through the scales of biology because those scales we know. We know which components are somewhat involved or in measurements that are happening upstream. So we have the somewhat interconnection or very large model that will be trained on many different data and we have this internal model representation that somewhat capture everything they've seen. And so, this is what we call those universal representation (UR) that will exist across the scales of biology.

Charlotte Bunne (13:22):

And what is great about AI, and so I think this is a bit like a history of AI in short is the ability to predict the last years, the ability to generate, we can generate new hypothesis, we can generate modalities that we are missing. We can potentially generate certain cellular state, molecular state have a certain property, but I think what's really coming is this ability to reason. So we see this in those very large language models, the ability to reason about a hypothesis, how we can test it. So this is what those instruments ultimately need to do. So we need to be able to simulate the change of a perturbation on a cellular phenotype. So on the internal representation, the universal representation of a cell state, we need to simulate the fact the mutation has downstream and how this would propagate in our representations upstream. And we need to build many different type of virtual instruments that allow us to basically design and build all those capabilities that ultimately the AI virtual cell needs to possess that will then allow us to reason, to generate hypothesis, to basically predict the next experiment to conduct to predict the outcome of a perturbation experiment to in silico design, cellular states, molecular states, things like that. And this is why we make the separation between internal representation as well as those instruments that operate on those representations.

Eric Topol (14:47):

Yeah, that's what I really liked is that you basically described the architecture, how you're going to do this. By putting these URs into the VIs, having a decoder and a manipulator and you basically got the idea if you can bring all these different integrations about which of course is pending. Now there are obviously many naysayers here that this is impossible. One of them is this guy, Philip Ball. I don't know if you read the language, How Life Works. Now he's a science journalist and he's a prolific writer. He says, “Comparing life to a machine, a robot, a computer, sells it short. Life is a cascade of processes, each with a distinct integrity and autonomy, the logic of which has no parallel outside the living world.” Is he right? There's no way to model this. It's silly, it's too complex.

Steve Quake (15:50):

We don't know, alright. And it's great that there's naysayers. If everyone agreed this was doable, would it be worth doing? I mean the whole point is to take risks and get out and do something really challenging in the frontier where you don't know the answer. If we knew that it was doable, I wouldn't be interested in doing it. So I personally am happy that there's not a consensus.

Eric Topol (16:16):

Well, I mean to capture people's imagination here, if you're successful and you marshal a global effort, I don't know who's going to pay for it because it's a lot of work coming here going forward. But if you can do it, the question here is right today we talk about, oh let's make an organoid so we can figure out how to treat this person's cancer or understand this person's rare disease or whatever. And instead of having to wait weeks for this culture and all the expense and whatnot, you could just do it in a computer and in silico and you have this virtual twin of a person's cells and their tissue and whatnot. So the opportunity here is, I don't know if people get, this is just extraordinary and quick and cheap if you can get there. And it's such a bold initiative idea, who will pay for this do you think?

Steve Quake (17:08):

Well, CZI is putting an enormous amount of resources into it and it's a major project for us. We have been laying the groundwork for it. We recently put together what I think is if not the largest, one of the largest GPU supercomputer clusters for nonprofit basic science research that came online at the end of last year. And in fact in December we put out an RFA for the scientific community to propose using it to build models. And so we're sharing that resource within the scientific community as I think you appreciate, one of the real challenges in the field has been access to compute resources and industry has it academia at a much lower level. We are able to be somewhere in between, not quite at the level of a private company but the tech company but at a level beyond what most universities are being able to do and we're trying to use that to drive the field forward. We're also planning on launching RFAs we this year to help drive this project forward and funding people globally on that. And we are building a substantial internal effort within CZI to help drive this project forward.

Eric Topol (18:17):

I think it has the looks of the human genome project, which at time as you know when it was originally launched that people thought, oh, this is impossible. And then look what happened. It got done. And now the sequence of genome is just a commodity, very relatively, very inexpensive compared to what it used to be.

Steve Quake (18:36):

I think a lot about those parallels. And I will say one thing, Philip Ball, I will concede him the point, the cells are very complicated. The genome project, I mean the sort of genius there was to turn it from a biology problem to a chemistry problem, there is a test tube with a chemical and it work out the structure of that chemical. And if you can do that, the problem is solved. I think what it means to have the virtual cell is much more complex and ambiguous in terms of defining what it's going to do and when you're done. And so, we have our work cut out for us there to try to do that. And that's why a little bit, I established our North Star and CZI for the next decade as understanding the mysteries of the cell and that word mystery is very important to me. I think the molecules, as you pointed out earlier are understood, genome sequenced, protein structure solved or predicted, we know a lot about the molecules. Those are if not solved problems, pretty close to being solved. And the real mystery is how do they work together to create life in the cell? And that's what we're trying to answer with this virtual cell project.

Eric Topol (19:43):

Yeah, I think another thing that of course is happening concurrently to add the likelihood that you'll be successful is we've never seen the foundation models coming out in life science as they have in recent weeks and months. Never. I mean, I have a paper in Science tomorrow coming out summarizing the progress about not just RNA, DNA, ligands. I mean the whole idea, AlphaFold3, but now Boltz and so many others. It's just amazing how fast the torrent of new foundation models. So Charlotte, what do you think accounts for this? This is unprecedented in life science to see foundation models coming out at this clip on evolution on, I mean you name it, design of every different molecule of life or of course in cells included in that. What do you think is going on here?

Charlotte Bunne (20:47):

So on the one hand, of course we benefit profits and inherit from all the tremendous efforts that have been made in the last decades on assembling those data sets that are very, very standardized. CELLxGENE is very somehow AI friendly, as you can say, it is somewhat a platform that is easy to feed into algorithms, but at the same time we actually also see really new building mechanisms, design principles of AI algorithms in itself. So I think we have understood that in order to really make progress, build those systems that work well, we need to build AI tools that are designed for biological data. So to give you an easy example, if I use a large language model on text, it's not going to work out of the box for DNA because we have different reading directions, different context lens and many, many, many, many more.

Charlotte Bunne (21:40):

And if I look at standard computer vision where we can say AI really excels and I'm applying standard computer vision, vision transformers on multiplex images, they're not going to work because normal computer vision architectures, they always expect the same three inputs, RGB, right? In multiplex images, I'm measuring up to 150 proteins potentially in a single experiment, but every study will measure different proteins. So I deal with many different scales like larger scales and I used to attention mechanisms that we have in usual computer vision. Transformers are not going to work anymore, they're not going to scale. And at the same time, I need to be completely flexible in whatever input combination of channel I'm just going to face in this experiment. So this is what we right now did for example, in our very first work, inheriting the design principle that we laid out in the paper AI virtual cell and then come up with new AI architectures that are dealing with these very special requirements that biological data have.

Charlotte Bunne (22:46):

So we have now a lot of computer scientists that work very, very closely have a very good understanding of biologists. Biologists that are getting much and much more into the computer science. So people who are fluent in both languages somewhat, that are able to now build models that are adopted and designed for biological data. And we don't just take basically computer vision architectures that work well on street scenes and try to apply them on biological data. So it's just a very different way of thinking about it, starting constructing basically specialized architectures, besides of course the tremendous data efforts that have happened in the past.

Eric Topol (23:24):

Yeah, and we're not even talking about just sequence because we've also got imaging which has gone through a revolution, be able to image subcellular without having to use any types of stains that would disrupt cells. That's another part of the deep learning era that came along. One thing I thought was fascinating in the paper in Cell you wrote, “For instance, the Short Read Archive of biological sequence data holds over 14 petabytes of information, which is 1,000 times larger than the dataset used to train ChatGPT.” I mean that's a lot of tokens, that's a lot of stuff, compute resources. It's almost like you're going to need a DeepSeek type of way to get this. I mean not that DeepSeek as its claim to be so much more economical, but there's a data challenge here in terms of working with that massive amount that is different than the human language. That is our language, wouldn't you say?

Steve Quake (24:35):

So Eric, that brings to mind one of my favorite quotes from Sydney Brenner who is such a wit. And in 2000 at the sort of early first flush of success in genomics, he said, biology is drowning in a sea of data and starving for knowledge. A very deep statement, right? And that's a little bit what the motivation was for putting the Short Read Archive statistic into the paper there. And again, for me, part of the value of this endeavor of creating a virtual cell is it's a tool to help us translate data into knowledge.

Eric Topol (25:14):

Yeah, well there's two, I think phenomenal figures in your Cell paper. The first one that kicks across the capabilities of the virtual cell and the second that compares the virtual cell to the real or the physical cell. And we'll link that with this in the transcript. And the other thing we'll link is there's a nice Atlantic article, “A Virtual Cell Is a ‘Holy Grail’ of Science. It's Getting Closer.” That might not be quite close as next week or year, but it's getting close and that's good for people who are not well grounded in this because it's much more taken out of the technical realm. This is really exciting. I mean what you're onto here and what's interesting, Steve, since I've known you for so many years earlier in your career you really worked on omics that is being DNA and RNA and in recent times you've made this switch to cells. Is that just because you're trying to anticipate the field or tell us a little bit about your migration.

Steve Quake (26:23):

Yeah, so a big part of my career has been trying to develop new measurement technologies that'll provide insight into biology. And decades ago that was understanding molecules. Now it's understanding more complex biological things like cells and it was like a natural progression. I mean we built the sequencers, sequenced the genomes, done. And it was clear that people were just going to do that at scale then and create lots of data. Hopefully knowledge would get out of that. But for me as an academic, I never thought I'd be in the position I'm in now was put it that way. I just wanted to keep running a small research group. So I realized I would have to get out of the genome thing and find the next frontier and it became this intersection of microfluidics and genomics, which as you know, I spent a lot of time developing microfluidic tools to analyze cells and try to do single cell biology to understand their heterogeneity. And that through a winding path led me to all these cell atlases and to where we are now.

Eric Topol (27:26):

Well, we're fortunate for that and also with your work with CZI to help propel that forward and I think it sounds like we're going to need a lot of help to get this thing done. Now Charlotte, as a computer scientist now at EPFL, what are you going to do to keep working on this and what's your career advice for people in computer science who have an interest in digital biology?

Charlotte Bunne (27:51):

So I work in particular on the prospect of using this to build diagnostic tools and to make diagnostics in the clinic easier because ultimately we have somewhat limited capabilities in the hospital to run deep omics, but the idea of being able to somewhat map with a cheaper and lighter modality or somewhat diagnostic test into something much richer because a model has been seeing all those different data and can basically contextualize it. It's very interesting. We've seen all those pathology foundation models. If I can always run an H&E, but then decide when to run deeper diagnostics to have a better or more accurate prediction, that is very powerful and it's ultimately reducing the costs, but the precision that we have in hospitals. So my faculty position right now is co-located between the School of Life Sciences, School of Computer Science. So I have a dual affiliation and I'm affiliated to the hospitals to actually make this possible and as a career advice, I think don't be shy and stick to your discipline.

Charlotte Bunne (28:56):

I have a bachelor's in biology, but I never only did biology. I have a PhD in computer science, which you would think a bachelor in biology not necessarily qualifies you through. So I think this interdisciplinarity also requires you to be very fluent, very comfortable in reading many different styles of papers and publications because a publication in a computer science venue will be very, very different from the way we write in biology. So don't stick to your study program, but just be free in selecting whatever course gets you closer to the knowledge you need in order to do the research or whatever task you are building and working on.

Eric Topol (29:39):

Well, Charlotte, the way you're set up there with this coalescence of life science and computer science is so ideal and so unusual here in the US, so that's fantastic. That's what we need and that's really the underpinning of how you're going to get to the virtual cells, getting these two communities together. And Steve, likewise, you were an engineer and somehow you became one of the pioneers of digital biology way back before it had that term, this interdisciplinary, transdisciplinary. We need so much of that in order for you all to be successful, right?

Steve Quake (30:20):

Absolutely. I mean there's so much great discovery to be done on the boundary between fields. I trained as a physicist and kind of made my career this boundary between physics and biology and technology development and it's just sort of been a gift that keeps on giving. You've got a new way to measure something, you discover something new scientifically and it just all suggests new things to measure. It's very self-reinforcing.

Eric Topol (30:50):

Now, a couple of people who you know well have made some pretty big statements about this whole era of digital biology and I think the virtual cell is perhaps the biggest initiative of all the digital biology ongoing efforts, but Jensen Huang wrote, “for the first time in human history, biology has the opportunity to be engineering, not science.” And Demis Hassabis wrote or said, ‘we're seeing engineering science, you have to build the artifact of interest first, and then once you have it, you can use the scientific method to reduce it down and understand its components.’ Well here there's a lot to do to understand its components and if we can do that, for example, right now as both of AI drug discoveries and high gear and there's umpteen numbers of companies working on it, but it doesn't account for the cell. I mean it basically is protein, protein ligand interactions. What if we had drug discovery that was cell based? Could you comment about that? Because that doesn't even exist right now.

Steve Quake (32:02):

Yeah, I mean I can say something first, Charlotte, if you've got thoughts, I'm curious to hear them. So I do think AI approaches are going to be very useful designing molecules. And so, from the perspective of designing new therapeutics, whether they're small molecules or antibodies, yeah, I mean there's a ton of investment in that area that is a near term fruit, perfect thing for venture people to invest in and there's opportunity there. There's been enough proof of principle. However, I do agree with you that if you want to really understand what happens when you drug a target, you're going to want to have some model of the cell and maybe not just the cell, but all the different cell types of the body to understand where toxicity will come from if you have on-target toxicity and whether you get efficacy on the thing you're trying to do.

Steve Quake (32:55):

And so, we really hope that people will use the virtual cell models we're going to build as part of the drug discovery development process, I agree with you in a little of a blind spot and we think if we make something useful, people will be using it. The other thing I'll say on that point is I'm very enthusiastic about the future of cellular therapies and one of our big bets at CZI has been starting the New York Biohub, which is aimed at really being very ambitious about establishing the engineering and scientific foundations of how to engineer completely, radically more powerful cellular therapies. And the virtual cell is going to help them do that, right? It's going to be essential for them to achieve that mission.

Eric Topol (33:39):

I think you're pointing out one of the most important things going on in medicine today is how we didn't anticipate that live cell therapy, engineered cells and ideally off the shelf or in vivo, not just having to take them out and work on them outside the body, is a revolution ongoing, and it's not just in cancer, it's in autoimmune diseases and many others. So it's part of the virtual cell need. We need this. One of the things that's a misnomer, I want you both to comment on, we keep talking about single cell, single cell. And there's a paper spatial multi-omics this week, five different single cell scales all integrated. It's great, but we don't get to single cell. We're basically looking at 50 cells, 100 cells. We're not doing single cell because we're not going deep enough. Is that just a matter of time when we actually are doing, and of course the more we do get down to the single or a few cells, the more insights we're going to get. Would you comment about that? Because we have all this literature on single cell comes out every day, but we're not really there yet.

Steve Quake (34:53):

Charlotte, do you want to take a first pass at that and then I can say something?

Charlotte Bunne (34:56):

Yes. So it depends. So I think if we look at certain spatial proteomics, we still have subcellular resolutions. So of course, we always measure many different cells, but we are able to somewhat get down to resolution where we can look at certain colocalization of proteins. This also goes back to the point just made before having this very good environment to study drugs. If I want to build a new drug, if I want to build a new protein, the idea of building this multiscale model allows us to actually simulate different, somehow binding changes and binding because we simulate the effect of a drug. Ultimately, the redouts we have they are subcellular. So of course, we often in the spatial biology, we often have a bit like methods that are rather coarse they have a spot that averages over certain some cells like hundreds of cells or few cells.

Charlotte Bunne (35:50):

But I think we also have more and more technologies that are zooming in that are subcellular where we can actually tag or have those probe-based methods that allow us to zoom in. There's microscopy of individual cells to really capture them in 3D. They are of course not very high throughput yet, but it gives us also an idea of the morphology and how ultimately morphology determine certain somehow cellular properties or cellular phenotype. So I think there's lots of progress also on the experimental and that ultimately will back feed into the AI virtual cell, those models that will be fed by those data. Similarly, looking at dynamics, right, looking at live imaging of individual cells of their morphological changes. Also, this ultimately is data that we'll need to get a better understanding of disease mechanisms, cellular phenotypes functions, perturbation responses.

Eric Topol (36:47):

Right. Yes, Steve, you can comment on that and the amazing progress that we have made with space and time, spatial temporal resolution, spatial omics over these years, but that we still could go deeper in terms of getting to individual cells, right?

Steve Quake (37:06):

So, what can we do with a single cell? I'd say we are very mature in our ability to amplify and sequence the genome of a single cell, amplify and sequence the transcriptome of a single cell. You can ask is one cell enough to make a biological conclusion? And maybe I think what you're referring to is people want to see replicates and so you can ask how many cells do you need to see to have confidence in any given biological conclusion, which is a reasonable thing. It's a statistical question in good science. I think I've been very impressed with how the mass spec people have been doing recently. I think they've finally cracked the ability to look at proteins from single cells and they can look at a couple thousand proteins. That was I think one of these Nature method of the year things at the end of last year and deep visual proteomics.

Eric Topol (37:59):

Deep visual proteomics, yes.

Steve Quake (38:00):

Yeah, they are over the hump. Yeah, they are over the hump with single cell measurements. Part of what's missing right now I think is the ability to reliably do all of that on the same cell. So this is what Charlotte was referring to be able to do sort of multi-modal measurements on single cells. That's kind of in its infancy and there's a few examples, but there's a lot more work to be done on that. And I think also the fact that these measurements are all destructive right now, and so you're losing the ability to look how the cells evolve over time. You've got to say this time point, I'm going to dissect this thing and look at a state and I don't get to see what happens further down the road. So that's another future I think measurement challenge to be addressed.

Eric Topol (38:42):

And I think I'm just trying to identify some of the multitude of challenges in this extraordinarily bold initiative because there are no shortage and that's good about it. It is given people lots of work to do to overcome, override some of these challenges. Now before we wrap up, besides the fact that you point out that all the work has to be done and be validated in real experiments, not just live in a virtual AI world, but you also comment about the safety and ethics of this work and assuming you're going to gradually get there and be successful. So could either or both of you comment about that because it's very thoughtful that you're thinking already about that.

Steve Quake (41:10):

As scientists and members of the larger community, we want to be careful and ensure that we're interacting with people who said policy in a way that ensures that these tools are being used to advance the cause of science and not do things that are detrimental to human health and are used in a way that respects patient privacy. And so, the ethics around how you use all this with respect to individuals is going to be important to be thoughtful about from the beginning. And I also think there's an ethical question around what it means to be publishing papers and you don't want people to be forging papers using data from the virtual cell without being clear about where that came from and pretending that it was a real experiment. So there's issues around those sorts of ethics as well that need to be considered.

Eric Topol (42:07):

And of those 40 some authors, do you around the world, do you have the sense that you all work together to achieve this goal? Is there kind of a global bonding here that's going to collaborate?

Steve Quake (42:23):

I think this effort is going to go way beyond those 40 authors. It's going to include a much larger set of people and I'm really excited to see that evolve with time.

Eric Topol (42:31):

Yeah, no, it's really quite extraordinary how you kick this thing off and the paper is the blueprint for something that we are all going to anticipate that could change a lot of science and medicine. I mean we saw, as you mentioned, Steve, how that deep visual proteomics (DVP) saved lives. It was what I wrote a spatial medicine, no longer spatial biology. And so, the way that this can change the future of medicine, I think a lot of people just have to have a little bit of imagination that once we get there with this AIVC, that there's a lot in store that's really quite exciting. Well, I think this has been an invigorating review of that paper and some of the issues surrounding it. I couldn't be more enthusiastic for your success and ultimately where this could take us. Did I miss anything during the discussion that we should touch on before we wrap up?

Steve Quake (43:31):

Not from my perspective. It was a pleasure as always Eric, and a fun discussion.

Charlotte Bunne (43:38):

Thanks so much.

Eric Topol (43:39):

Well thank you both and all the co-authors of this paper. We're going to be following this with the great interest, and I think for most people listening, they may not know that this is in store for the future. Someday we will get there. I think one of the things to point out right now is the models we have today that large language models based on transformer architecture, they're going to continue to evolve. We're already seeing so much in inference and ability for reasoning to be exploited and not asking for prompts with immediate answers, but waiting for days to get back. A lot more work from a lot more computing resources. But we're going to get models in the future to fold this together. I think that's one of the things that you've touched on the paper so that whatever we have today in concert with what you've laid out, AI is just going to keep getting better.

Eric Topol (44:39):

The biology that these foundation models are going to get broader and more compelling as to their use cases. So that's why I believe in this. I don't see this as a static situation right now. I just think that you're anticipating the future, and we will have better models to be able to integrate this massive amount of what some people would consider disparate data sources. So thank you both and all your colleagues for writing this paper. I don't know how you got the 42 authors to agree to it all, which is great, and it's just a beginning of something that's a new frontier. So thanks very much.

Steve Quake (45:19):

Thank you, Eric.

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Funding for the NIH and US biomedical research is imperiled at a momentous time of progress. Exemplifying this is the work of Dr. Anna Greka, a leading physician-scientist at the Broad Institute who is devoted to unlocking the mysteries of rare diseases— that cumulatively affect 30 million Americans— and finding cures, science supported by the NIH.

A clip from our conversation

The audio is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.

Transcript with audio and external links

Eric Topol (00:06):

Well, hello. This is Eric Topol from Ground Truths, and I am really delighted to welcome today, Anna Greka. Anna is the president of the American Society for Clinical Investigation (ASCI) this year, a very prestigious organization, but she's also at Mass General Brigham, a nephrologist, a cell biologist, a physician-scientist, a Core Institute Member of the Broad Institute of MIT and Harvard, and serves as a member of the institute’s Executive Leadership Team. So we got a lot to talk about of all these different things you do. You must be pretty darn unique, Anna, because I don't know any cell biologists, nephrologists, physician-scientist like you.

Anna Greka (00:48):

Oh, thank you. It's a great honor to be here and glad to chat with you, Eric.

Eric Topol (00:54):

Yeah. Well, I had the real pleasure to hear you speak at a November conference, the AI for Science Forum, which we'll link to your panel. Where I was in a different panel, but you spoke about your extraordinary work and it became clear that we need to get you on Ground Truths, so you can tell your story to everybody. So I thought rather than kind of going back from the past where you were in Greece and somehow migrated to Boston and all that. We're going to get to that, but you gave an amazing TED Talk and it really encapsulated one of the many phenomenal stories of your work as a molecular sleuth. So maybe if you could give us a synopsis, and of course we'll link to that so people could watch the whole talk. But I think that Mucin-1 or MUC1, as you call it, discovery is really important to kind of ground our discussion.

A Mysterious Kidney Disease Unraveled

Anna Greka (01:59):

Oh, absolutely. Yeah, it's an interesting story. In some ways, in my TED Talk, I highlight one of the important families of this story, a family from Utah, but there's also other important families that are also part of the story. And this is also what I spoke about in London when we were together, and this is really sort of a medical mystery that initially started on the Mediterranean island of Cyprus, where it was found that there were many families in which in every generation, several members suffered and ultimately died from what at the time was a mysterious kidney disease. This was more than 30 years ago, and it was clear that there was something genetic going on, but it was impossible to identify the gene. And then even with the advent of Next-Gen sequencing, this is what's so interesting about this story, it was still hard to find the gene, which is a little surprising.

Anna Greka (02:51):

After we were able to sequence families and identify monogenic mutations pretty readily, this was still very resistant. And then it actually took the firepower of the Broad Institute, and it's actually from a scientific perspective, an interesting story because they had to dust off the old-fashioned Sanger sequencing in order to get this done. But they were ultimately able to identify this mutation in a VNTR region of the MUC1 gene. The Mucin-1 gene, which I call a dark corner of the human genome, it was really, it's highly repetitive, very GC-rich. So it becomes very difficult to sequence through there with Next-Gen sequencing. And so, ultimately the mutation of course was found and it's a single cytosine insertion in a stretch of cytosines that sort of causes this frameshift mutation and an early stop codon that essentially results in a neoprotein like a toxic, what I call a mangled protein that sort of accumulates inside the kidney cells.

Anna Greka (03:55):

And that's where my sort of adventure began. It was Eric Lander’s group, who is the founding director of the Broad who discovered the mutation. And then through a conversation we had here in Boston, we sort of discovered that there was an opportunity to collaborate and so that’s how I came to the Broad, and that's the beginnings of this story. I think what's fascinating about this story though, that starts in a remote Mediterranean island and then turns out to be a disease that you can find in every continent all over the world. There are probably millions of patients with kidney disease in whom we haven't recognized the existence of this mutation. What's really interesting about it though is that what we discovered is that the mangled protein that's a result of this misspelling of this mutation is ultimately captured by a family of cargo receptors, they’re called the TMED cargo receptors and they end up sort of grabbing these misfolded proteins and holding onto them so tight that it's impossible for the cell to get rid of them.

Anna Greka (04:55):

And they become this growing heap of molecular trash, if you will, that becomes really hard to manage, and the cells ultimately die. So in the process of doing this molecular sleuthing, as I call it, we actually also identified a small molecule that actually disrupts these cargo receptors. And as I described in my TED Talk, it's a little bit like having these cargo trucks that ultimately need to go into the lysosome, the cells recycling facility. And this is exactly what this small molecule can do. And so, it was just like a remarkable story of discovery. And then I think the most exciting of all is that these cargo receptors turn out to be not only relevant to this one mangled misshapen protein, but they actually handle a completely different misshapen protein caused by a different genetic mutation in the eye, causing retinitis pigmentosa, a form of blindness, familial blindness. We're now studying familial Alzheimer's disease that's also involving these cargo receptors, and there are other mangled misshapen proteins in the liver, in the lung that we're now studying. So this becomes what I call a node, like a nodal mechanism that can be targeted for the benefit of many more patients than we had previously thought possible, which has been I think, the most satisfying part about this story of molecular sleuthing.

Eric Topol (06:20):

Yeah, and it's pretty extraordinary. We'll put the figure from your classic Cell paper in 2019, where you have a small molecule that targets the cargo receptor called TMED9.

Anna Greka (06:34):

Correct.

Expanding the Mission

Eric Topol (06:34):

And what's amazing about this, of course, is the potential to reverse this toxic protein disease. And as you say, it may have applicability well beyond this MUC1 kidney story, but rather eye disease with retinitis pigmentosa and the familial Alzheimer's and who knows what else. And what's also fascinating about this is how, as you said, there were these limited number of families with the kidney disease and then you found another one, uromodulin. So there's now, as you say, thousands of families, and that gets me to part of your sleuth work is not just hardcore science. You started an entity called the Ladders to Cures (L2C) Scientific Accelerator.

Eric Topol (07:27):

Maybe you can tell us about that because this is really pulling together all the forces, which includes the patient advocacy groups, and how are we going to move forward like this?

Anna Greka (07:39):

Absolutely. I think the goal of the Ladders to Cures Accelerator, which is a new initiative that we started at the Broad, but it really encompasses many colleagues across Boston. And now increasingly it's becoming sort of a national, we even have some international collaborations, and it's only two years that it's been in existence, so we're certainly in a growth mode. But the inspiration was really some of this molecular sleuthing work where I basically thought, well, for starters, it cannot be that there's only one molecular node, these TMED cargo receptors that we discovered there's got to be more, right? And so, there's a need to systematically go and find more nodes because obviously as anyone who works in rare genetic diseases will tell you, the problem for all of us is that we do what I call hand to hand combat. We start with the disease with one mutation, and we try to uncover the mechanism and then try to develop therapies, and that's wonderful.

Anna Greka (08:33):

But of course, it's slow, right? And if we consider the fact that there are 30 million patients in the United States in every state, everywhere in the country who suffer from a rare genetic disease, most of them, more than half of them are children, then we can appreciate the magnitude of the problem. Out of more than 8,000 genes that are involved in rare genetic diseases, we barely have something that looks like a therapy for maybe 500 of them. So there's a huge mismatch in the unmet need and magnitude of the problem. So the Ladders to Cures Accelerator is here to address this and to do this with the most modern tools available. And to your point, Eric, to bring patients along, not just as the recipients of whatever we discover, but also as partners in the research enterprise because it's really important to bring their perspectives and of course their partnerships in things like developing appropriate biomarkers, for example, for what we do down the road.

Anna Greka (09:35):

But from a fundamental scientific perspective, this is basically a project that aims to identify every opportunity for nodes, underlying all rare genetic diseases as quickly as possible. And this was one of the reasons I was there at the AI for Science Forum, because of course when one undertakes a project in which you're basically, this is what we're trying to do in the Ladders to Cures Accelerator, introduce dozens of thousands of missense and nonsense human mutations that cause genetic diseases, simultaneously introduce them into multiple human cells and then use modern scalable technology tools. Things like CRISPR screens, massively parallel CRISPR screens to try to interrogate all of these diseases in parallel, identify the nodes, and then develop of course therapeutic programs based on the discovery of these nodes. This is a massive data generation project that is much needed and in addition to the fact that it will help hopefully accelerate our approach to all rare diseases, genetic diseases. It is also a highly controlled cell perturbation dataset that will require the most modern tools in AI, not only to extract the data and understand the data of this dataset, but also because this, again, an extremely controlled, well controlled cell perturbation dataset can be used to train models, train AI models, so that in the future, and I hope this doesn't sound too futuristic, but I think that we're all aiming for that cell biologists for sure dream of this moment, I think when we can actually have in silico the opportunity to make predictions about what cell behaviors are going to look like based on a new perturbation that was not in the training set. So an experiment that hasn't yet been done on a cell, a perturbation that has not been made on a human cell, what if like a new drug, for example, or a new kind of perturbation, a new chemical perturbation, how would it affect the behavior of the cell? Can we make a predictive model for that? This doesn't exist today, but I think this is something, the cell prediction model is a big question for biology for the future. And so, I'm very energized by the opportunity to both address this problem of rare monogenic diseases that remains an unmet need and help as many patients as possible while at the same time advancing biology as much as we possibly can. So it's kind of like a win-win lifting all boats type of enterprise, hopefully.

Eric Topol (12:11):

Yeah. Well, there's many things to get to unpack what you've just been reviewing. So one thing for sure is that of these 8,000 monogenic diseases, they have relevance to the polygenic common diseases, of course. And then also the fact that the patient family advocates, they are great at scouring the world internet, finding more people, bringing together communities for each of these, as you point out aptly, these rare diseases cumulatively are high, very high proportion, 10% of Americans or more. So they're not so rare when you think about the overall.

Anna Greka (12:52):

Collectively.

Help From the Virtual Cell?

Eric Topol (12:53):

Yeah. Now, and of course is this toxic proteinopathies, there's at least 50 of these and the point that people have been thinking until now that, oh, we found a mangled protein, but what you've zeroed in on is that, hey, you know what, it's not just a mangled protein, it's how it gets stuck in the cell and that it can't get to the lysosome to get rid of it, there's no waste system. And so, this is such fundamental work. Now that gets me to the virtual cell story, kind of what you're getting into. I just had a conversation with Charlotte Bunne and Steve Quake who published a paper in December on the virtual cell, and of course that's many years off, but of course it's a big, bold, ambitious project to be able to say, as you just summarized, if you had cells in silico and you could do perturbations in silico, and of course they were validated by actual experiments or bidirectionally the experiments, the real ones helped to validate the virtual cell, but then you could get a true acceleration of your understanding of cell biology, your field of course.

Anna Greka (14:09):

Exactly.

Eric Topol (14:12):

So what you described, is it the same as a virtual cell? Is it kind of a precursor to it? How do you conceive this because this is such a complex, I mean it’s a fundamental unit of life, but it's also so much more complex than a protein or an RNA because not only all the things inside the cell, inside all these organelles and nucleus, but then there's all the outside interactions. So this is a bold challenge, right?

Anna Greka (14:41):

Oh my god, it's absolutely from a biologist perspective, it's the challenge of a generation for sure. We think taking humans to Mars, I mean that's an aspirational sort of big ambitious goal. I think this is the, if you will, the Mars shot for biology, being able to, whether the terminology, whether you call it a virtual cell. I like the idea of saying that to state it as a problem, the way that people who think about it from a mathematics perspective for example, would think about it. I think stating it as the cell prediction problem appeals to me because it actually forces us biologists to think about setting up the way that we would do these cell perturbation data sets, the way we would generate them to set them up to serve predictions. So for example, the way that I would think about this would be can I in the future have so much information about how cell perturbations work that I can train a model so that it can predict when I show it a picture of another cell under different conditions that it hasn't seen before, that it can still tell me, ah, this is a neuron in which you perturbed the mitochondria, for example, and now this is sort of the outcome that you would expect to see.

Anna Greka (16:08):

And so, to be able to have this ability to have a model that can have the ability to predict in silico what cells would look like after perturbation, I think that's sort of the way that I think about this problem. It is very far away from anything that exists today. But I think that the beginning starts, and this is one of the unique things about my institute, if I can say, we have a place where cell biologists, geneticists, mathematicians, machine learning experts, we all come together in the same place to really think and grapple with these problems. And of course we're very outward facing, interacting with scientists all across the world as well. But there's this sort of idea of bringing people into one institute where we can just think creatively about these big aspirational problems that we want to solve. I think this is one of the unique things about the ecosystem at the Broad Institute, which I'm proud to be a part of, and it is this kind of out of the box thinking that will hopefully get us to generate the kinds of data sets that will serve the needs of building these kinds of models with predictive capabilities down the road.

Anna Greka (17:19):

But as you astutely said, AlphaFold of course was based on the protein database existing, right? And that was a wealth of available information in which one could train models that would ultimately be predictive, as we have seen this miracle that Demi Hassabis and John Jumper have given to humanity, if you will.

Anna Greka (17:42):

But as Demis and John would also say, I believe is as I have discussed with them, in fact, the cell prediction problem is really a bigger problem because we do not have a protein data bank to go to right now, but we need to create it to generate these data. And so, my Ladders to Cures Accelerator is here to basically provide some part of the answer to that problem, create this kind of well-controlled database that we need for cell perturbations, while at the same time maximizing our learnings about these fully penetrant coding mutations and what their downstream sequelae would be in many different human cells. And so, in this way, I think we can both advance our knowledge about these monogenic diseases, build models, hopefully with predictive capabilities. And to your point, a lot of what we will learn about this biology, if we think that it involves 8,000 or more out of the 20,000 genes in our genome, it will of course serve our understanding of polygenic diseases ultimately as well as we go deeper into this biology and we look at the combinatorial aspects of what different mutations do to human cells. And so, it's a huge aspirational problem for a whole generation, but it's a good one to work on, I would say.

Learning the Language of Life with A.I.

Eric Topol (19:01):

Oh, absolutely. Now I think you already mentioned something that's quite, well, two things from what you just touched on. One of course, how vital it is to have this inner or transdisciplinary capability because you do need expertise across these vital areas. But the convergence, I mean, I love your term nodal biology and the fact that there's all these diseases like you were talking about, they do converge and nodal is a good term to highlight that, but it's not. Of course, as you mentioned, we have genome editing which allows to look at lots of different genome perturbations, like the single letter change that you found in MUC1 pathogenic critical mutation. There's also the AI world which is blossoming like I've never seen. In fact, I had in Science this week about learning the language of life with AI and how there's been like 15 new foundation models, DNA, proteins, RNA, ligands, all their interactions and the beginning of the cell story too with the human cell.

Eric Topol (20:14):

So this is exploding. As you said, the expertise in computer science and then this whole idea that you could take these powerful tools and do as you said, which is the need to accelerate, we just can't sit around here when there's so much discovery work to be done with the scalability, even though it might take years to get to this artificial intelligence virtual cell, which I have to agree, everyone in biology would say that's the holy grail. And as you remember at our conference in London, Demi Hassabis said that's what we'd like to do now. So it has the attention of leaders in AI around the world, obviously in the science and the biomedical community like you and many others. So it is an extraordinary time where we just can't sit still with these tools that we have, right?

Anna Greka (21:15):

Absolutely. And I think this is going to be, you mentioned the ASCI presidency in the beginning of our call. This is going to be the president gets to give an address at the annual meeting in Chicago. This is going to be one of the points I make, no matter what field in biomedicine we're in, we live in, I believe, a golden era and we have so many tools available to us that we can really accelerate our ability to help more patients. And of course, this is our mandate, the most important stakeholders for everything that we do as physician-scientists are our patients ultimately. So I feel very hopeful for the future and our ability to use these tools and to really make good on the promise of research is a public good. And I really hope that we can advance our knowledge for the benefit of all. And this is really an exciting time, I think, to be in this field and hopefully for the younger colleagues a time to really get excited about getting in there and getting involved and asking the big questions.

Career Reflections

Eric Topol (22:21):

Well, you are the prototype for this and an inspiration to everyone really, I'm sure to your lab group, which you highlighted in the TED Talk and many other things that you do. Now I want to spend a little bit of time about your career. I think it's fascinating that you grew up in Greece and your father's a nephrologist and your mother's a pathologist. So you had two physicians to model, but I guess you decided to go after nephrology, which is an area in medicine that I kind of liken it to Rodney Dangerfield, he doesn't get any respect. You don't see many people that go into nephrology. But before we get to your decision to do that somehow or other you came from Greece to Harvard for your undergrad. How did you make that connect to start your college education? And then subsequently you of course you stayed in Boston, you've never left Boston, I think.

Anna Greka (23:24):

I never left. Yeah, this is coming into 31 years now in Boston.

Anna Greka (23:29):

Yeah, I started as a Harvard undergraduate and I'm now a full professor. It's kind of a long, but wonderful road. Well, actually I would credit my parents. You mentioned that my father, they're both physician-scientists. My father is now both retired, but my father is a nephrologist, and my mother is a pathologist, actually, they were both academics. And so, when we were very young, we lived in England when my parents were doing postdoctoral work. That was actually a wonderful gift that they gave me because I became bilingual. It was a very young age, and so that allowed me to have this advantage of being fluent in English. And then when we moved back to Greece where I grew up, I went to an American school. And from that time, this is actually an interesting story in itself. I'm very proud of this school.

Anna Greka (24:22):

It's called Anatolia, and it was founded by American missionaries from Williams College a long time ago, 150 and more years ago. But it is in Thessaloniki, Greece, which is my hometown, and it's a wonderful institution, which gave me a lot of gifts as well, preparing me for coming to college in the United States. And of course, I was a good student in high school, but what really was catalytic was that I was lucky enough to get a scholarship to go to Harvard. And that was really, you could say the catalyst that propelled me from a teenager who was dreaming about a career as a physician-scientist because I certainly was for as far back as I remember in fact. But then to make that a reality, I found myself on the Harvard campus initially for college, and then I was in the combined Harvard-MIT program for my MD PhD. And then I trained in Boston at Mass General in Brigham, and then sort of started my academic career. And that sort of brings us to today, but it is an unlikely story and one that I feel still very lucky and blessed to have had these opportunities. So for sure, it's been wonderful.

Eric Topol (25:35):

We're the ones lucky that you came here and set up shop and you did your productivity and discovery work and sleuthing has been incredible. But I do think it's interesting too, because when you did your PhD, it was in neuroscience.

Anna Greka (25:52):

Ah, yes. That's another.

Eric Topol (25:54):

And then you switch gears. So tell us about that?

Anna Greka (25:57):

This is interesting, and actually I encourage more colleagues to think about it this way. So I have always been driven by the science, and I think that it seems a little backward to some people, but I did my PhD in neuroscience because I was interested in understanding something about these ion channels that were newly discovered at the time, and they were most highly expressed in the brain. So here I was doing work in the brain in the neuroscience program at Harvard, but then once I completed my PhD and I was in the middle of my residency training actually at Mass General, I distinctly remember that there was a paper that came out that implicated the same family of ion channels that I had spent my time understanding in the brain. It turned out to be a channelopathy that causes kidney disease.

Anna Greka (26:43):

So that was the light bulb, and it made me realize that maybe what I really wanted to do is just follow this thread. And my scientific curiosity basically led me into studying the kidney and then it seemed practical therefore to get done with my clinical training as efficiently as possible. So I finished residency, I did nephrology training, and then there I was in the lab trying to understand the biology around this channelopathy. And that sort of led us into the early projects in my young lab. And in fact, it's interesting we didn't talk about that work, but that work in itself actually has made it all the way to phase II trials in patients. This was a paper we published in Science in 2017 and follow onto that work, there was an opportunity to build this into a real drug targeting one of these ion channels that has made it into phase II trials. And we'll see what happens next. But it's this idea of following your scientific curiosity, which I also talked about in my TED Talk, because you don't know to what wonderful places it will lead you. And quite interestingly now my lab is back into studying familial Alzheimer's and retinitis pigmentosa in the eye in brain. So I tell people, do not limit yourself to whatever someone says your field is or should be. Just follow your scientific curiosity and usually that takes you to a lot more interesting places. And so, that's certainly been a theme from my career, I would say.

Eric Topol (28:14):

No, I think that's perfect. Curiosity driven science is not the term. You often hear hypothesis driven or now with AI you hear more AI exploratory science. But no, that's great. Now I want to get a little back to the AI story because it’s so fascinating. You use lots of different types of AI such as cellular imaging would be fusion models and drug discovery. I mean, you've had drug discovery for different pathways. You mentioned of course the ion channel and then also as we touched on with your Cell paper, the whole idea of targeting the cargo receptor with a small molecule and then things in between. You discussed this of course at the London panel, but maybe you just give us the skinny on the different ways that you incorporate AI in the state-of-the-art science that you're doing?

Anna Greka (29:17):

Sure, yeah, thank you. I think there are many ways in which even for quite a long time before AI became such a well-known kind of household term, if you will, the concept of machine learning in terms of image processing is something that has been around for some time. And so, this is actually a form of AI that we use in order to process millions of images. My lab has by produced probably more than 20 million images over the last few years, maybe five to six years. And so, if you can imagine it's impossible for any human to process this many images and make sense of them. So of course, we've been using machine learning that is becoming increasingly more and more sophisticated and advanced in terms of being able to do analysis of images, which is a lot of what we cell biologists do, of course.

Anna Greka (30:06):

And so, there's multiple different kinds of perturbations that we do to cells, whether we're using CRISPR or base editing to make, for example, genome wide or genome scale perturbations or small molecules as we have done as well in the past. These are all ways in which we are then using machine learning to read out the effects in images of cells that we're looking at. So that's one way in which machine learning is used in our daily work, of course, because we study misshape and mangled proteins and how they are recognized by these cargo receptors. We also use AlphaFold pretty much every day in my lab. And this has been catalytic for us as a tool because we really are able to accelerate our discoveries in ways that were even just three or four years ago, completely impossible. So it's been incredible to see how the young people in my lab are just so excited to use these tools and they're becoming extremely savvy in using these tools.

Anna Greka (31:06):

Of course, this is a new generation of scientists, and so we use AlphaFold all the time. And this also has a lot of implications of course for some of the interventions that we might think about. So where in this cargo receptor complex that we study for example, might we be able to fit a drug that would disrupt the complex and lead the cargo tracks into the lysosome for degradation, for example. So there's many ways in which AI can be used for all of these functions. So I would say that if we were to organize our thinking around it, one way to think about the use of machine learning AI is around what I would call understanding biology in cells and what in sort of more kind of drug discovery terms you would call target identification, trying to understand the things that we might want to intervene on in order to have a benefit for disease.

Anna Greka (31:59):

So target ID is one area in which I think machine learning and AI will have a catalytic effect as they already are. The other of course, is in the actual development of the appropriate drugs in a rational way. So rational drug design is incredibly enabled by AlphaFold and all these advances in terms of understanding protein structures and how to fit drugs into them of all different modalities and kinds. And I think an area that we are not yet harnessing in my group, but I think the Ladders to Cures Accelerator hopes to build on is really patient data. I think that there's a lot of opportunity for AI to be used to make sense of medical records for example and how we extract information that would tell us that this cohort of patients is a better cohort to enroll in your trial versus another. There are many ways in which we can make use of these tools. Not all of them are there yet, but I think it's an exciting time for being involved in this kind of work.

Eric Topol (32:58):

Oh, no question. Now it must be tough when you know the mechanism of these families disease and you even have a drug candidate, but that it takes so long to go from that to helping these families. And what are your thoughts about that, I mean, are you thinking also about genome editing for some of these diseases or are you thinking to go through the route of here's a small molecule, here's the tox data in animal models and here's phase I and on and on. Where do you think because when you know so much and then these people are suffering, how do you bridge that gap?

Anna Greka (33:39):

Yeah, I think that's an excellent question. Of course, having patients as our partners in our research is incredible as a way for us to understand the disease, to build biomarkers, but it is also exactly creating this kind of emotional conflict, if you will, because of course, to me, honesty is the best policy, if you will. And so, I'm always very honest with patients and their families. I welcome them to the lab so they can see just how long it takes to get some of these things done. Even today with all the tools that we have, of course there are certain things that are still quite slow to do. And even if you have a perfect drug that looks like it fits into the right pocket, there may still be some toxicity, there may be other setbacks. And so, I try to be very honest with patients about the road that we're on. The small molecule path for the toxic proteinopathies is on its way now.

Anna Greka (34:34):

It's partnered with a pharmaceutical company, so it's on its way hopefully to patients. Of course, again, this is an unpredictable road. Things can happen as you very well know, but I'm at least glad that it's sort of making its way there. But to your point, and I'm in an institute where CRISPR was discovered, and base editing and prime editing were discovered by my colleagues here. So we are in fact looking at every other modality that could help with these diseases. We have several hurdles to overcome because in contrast to the liver and the brain, the kidney for example, is not an organ in which you can easily deliver nucleic acid therapies, but we're making progress. I have a whole subgroup within the bigger group who's focusing on this. It's actually organized in a way where they're running kind of independently from the cell biology group that I run.

Anna Greka (35:31):

And it's headed by a person who came from industry so that she has the opportunity to really drive the project the way that it would be run milestone driven, if you will, in a way that it would be run as a therapeutics program. And we're really trying to go after all kinds of different nucleic acid therapies that would target the mutations themselves rather than the cargo receptors. And so, there's ASO and siRNA technologies and then also actual gene editing technologies that we are investigating. But I would say that some of them are closer than others. And again, to your question about patients, I tell them honestly when a project looks to be more promising, and I also tell them when a project looks to have hurdles and that it will take long and that sometimes I just don't know how long it will take before we can get there. The only thing that I can promise patients in any of our projects, whether it's Alzheimer's, blindness, kidney disease, all I can promise is that we're working the hardest we possibly can on the problem.

Anna Greka (36:34):

And I think that is often reassuring I have found to patients, and it's best to be honest about the fact that these things take a long time, but I do think that they find it reassuring that someone is on it essentially, and that there will be some progress as we move forward. And we've made progress in the very first discovery that came out of my lab. As I mentioned to you, we've made it all the way to phase II trials. So I have seen the trajectory be realized, and I'm eager to make it happen again and again as many times as I can within my career to help as many people as possible.

The Paucity of Physician-Scientists

Eric Topol (37:13):

I have no doubts that you'll be doing this many times in your career. No, there's no question about it. It's extraordinary actually. There's a couple of things there I want to pick up on. Physician-scientists, as you know, are a rarefied species. And you have actually so nicely told the story about when you have a physician-scientist, you're caring for the patients that you're researching, which is, most of the time we have scientists. Nothing wrong with them of course, but you have this hinge point, which is really important because you’re really hearing the stories and experiencing the patients and as you say, communicating about the likelihood of being able to come up with a treatment or the progress. What are we going to do to get more physician-scientists? Because this is a huge problem, it has been for decades, but the numbers just keep going lower and lower.

Anna Greka (38:15):

I think you're absolutely right. And this is again, something that in my leadership of the ASCI I have made sort of a cornerstone of our efforts. I think that it has been well-documented as a problem. I think that the pressures of modern clinical care are really antithetical to the needs of research, protected time to really be able to think and be creative and even have the funding available to be able to pursue one's program. I think those pressures are becoming so heavy for investigators that many of them kind of choose one or the other route most often the clinical route because that tends to be, of course where they can support their families better. And so, this has been kind of the conundrum in some ways that we take our best and brightest medical students who are interested in investigation, we train them and invest in them in becoming physician-scientists, but then we sort of drop them at the most vulnerable time, which is usually after one completes their clinical and scientific training.

Anna Greka (39:24):

And they're embarking on early phases of one's careers. It has been found to be a very vulnerable point when a lot of people are now in their mid-thirties or even late thirties perhaps with some family to take care of other burdens of adulthood, if you will. And I think what it becomes very difficult to sustain a career where one salary is very limited due to the research component. And so, I think we have to invest in our youngest people, and it is a real issue that there's no good mechanism to do that at the present time. So I was actually really hoping that there would be an opportunity with leadership at the NIH to really think about this. It's also been discussed at the level of the National Academy of Medicine where I had some role in discussing the recent report that they put out on the biomedical enterprise in the United States. And it's kind of interesting to see that there is a note made there about this issue and the fact that there needs to be, I think, more generous investment in the careers of a few select physician-scientists that we can support. So if you look at the numbers, currently out of the entire physician workforce, a physician-scientist comprised of less than 1%.

Anna Greka (40:45):

It’s probably closer to 0.8% at this point.

Eric Topol (40:46):

No, it's incredible.

Anna Greka (40:48):

So that's really not enough, I think, to maintain the enterprise and if you will, this incredible innovation economy that the United States has had this miracle engine, if you will, in biomedicine that has been fueled in large part by physician investigators. Of course, our colleagues who are non-physician investigators are equally important partners in this journey. But we do need a few of the physician-scientists investigators I think as well, if you really think about the fact that I think 70% of people who run R&D programs in all the big pharmaceutical companies are physician-scientists. And so, we need people like us to be able to work on these big problems. And so, more investment, I think that the government, the NIH has a role to play there of course. And this is important from both an economic perspective, a competition perspective with other nations around the world who are actually heavily investing in the physician-scientist workforce.

Anna Greka (41:51):

And I think it's also important to do so through our smaller scale efforts at the ASCI. So one of the things that I have been involved in as a council member and now as president is the creation of an awards program for those early career investigators. So we call them the Emerging-Generation Awards, and we also have the Young Physician-Scientist Awards. And these are really to recognize people who are making that transition from being kind of a trainee and a postdoc and have finished their clinical training into becoming an independent assistant professor. And so, those are small awards, but they're kind of a symbolic tap on the shoulder, if you will, that the ASCI sees you, you're talented, stay the course. We want you to become a future member. Don't give up and please keep on fighting. I think that can take us only so far.

Anna Greka (42:45):

I mean, unless there's a real investment, of course still it will be hard to maintain people in the pipeline. But this is just one way in which we have tried to, these programs that the ASCI offers have been very successful over the last few years. We create a cohort of investigators who are clearly recognized by members of the ASCI is being promising young colleagues. And we give them longitudinal training as part of a cohort where they learn about how to write a grant, how to write a paper, leadership skills, how to run a lab. And they're sort of like a buddy system as well. So they know that they're in it together rather than feeling isolated and struggling to get their careers going. And so, we've seen a lot of success. One way that we measure that is conversion into an ASCI membership. And so, we're encouraged by that, and we hope that the program can continue. And of course, as president, I'm going to be fundraising for that as well, it's part of the role. But it is a really worthy cause because to your point, we have to somehow make sure that our younger colleagues stay the course that we can at least maintain, if not bolster our numbers within the scientific workforce.

Eric Topol (43:57):

Well, you outlined some really nice strategies and plans. It's a formidable challenge, of course. And we'd like to see billions of dollars to support this. And maybe someday we will because as you say, if we could relieve the financial concerns of people who have curiosity driven ideas.

Anna Greka (44:18):

Exactly.

Eric Topol (44:19):

We could do a lot to replenish and build a big physician-scientist workforce. Now, the last thing I want to get to, is you have great communication skills. Obviously, anybody who is listening or watching this.

Eric Topol (44:36):

Which is another really important part of being a scientist, no less a physician or the hybrid of the two. But I wanted to just go to the backstory because your TED Talk, which has been watched by hundreds of thousands of people, and I'm sure there's hundreds of thousands more that will watch it, but the TED organization is famous for making people come to the place a week ahead. This is Vancouver used to be in LA or Los Angeles area and making them rehearse the talk, rehearse, rehearse, rehearse, which seems crazy. You could train the people there, how to give a talk. Did you have to go through that?

Anna Greka (45:21):

Not really. I did rehearse once on stage before I actually delivered the talk live. And I was very encouraged by the fact that the TED folks who are of course very well calibrated, said just like that. It's great, just like that.

Eric Topol (45:37):

That says a lot because a lot of people that do these talks, they have to do it 10 times. So that kind of was another metric. But what I don't like about that is it just because these people almost have to memorize their talks from giving it so much and all this coaching, it comes across kind of stilted and unnatural, and you're just a natural great communicator added to all your other things.

Anna Greka (46:03):

I think it’s interesting. Actually, I would say, if I may, that I credit, of course, I actually think that it's important, for us physician-scientists, again, science and research is a public good, and being able to communicate to the public what it is that we do, I think is kind of an obligation for the fact that we are funded by the public to do this kind of work. And so, I think that's important. And I always wanted to cultivate those communication skills for the benefit of communicating simply and clearly what it is that we do in our labs. But also, I would say as part of my story, I mentioned that I had the opportunity to attend a special school growing up in Greece, Anatolia, which was an American school. One of the interesting things about that is that there was an oratory competition.

Anna Greka (46:50):

I got very early exposure entering that competition. And if you won the first prize, it was in the kind of ancient Rome way, first among equals, right? And so, that was the prize. And I was lucky to have this early exposure. This is when I was 14, 15, 16 years old, that I was training to give these oratory speeches in front of an audience and sort of compete with other kids who were doing the same. I think these are just wonderful gifts that a school can give a student that have stayed with me for life. And I think that that's a wonderful, yeah, I credit that experience for a lot of my subsequent capabilities in this area.

Eric Topol (47:40):

Oh, that's fantastic. Well, this has been such an enjoyable conversation, Anna. Did I miss anything that we need to bring up, or do you think we have it covered?

Anna Greka (47:50):

Not at all. No, this was wonderful, and I thoroughly enjoyed it as well. I'm very honored seeing how many other incredible colleagues you've had on the show. It's just a great honor to be a part of this. So thank you for having me.

Eric Topol (48:05):

Well, you really are such a great inspiration to all of us in the biomedical community, and we'll be cheering for your continued success and thanks so much for joining today, and I look forward to the next time we get a chance to visit.

Anna Greka (48:20):

Absolutely. Thank you, Eric.

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Transcript with links to Audio and External Links

Eric Topol (00:07):

Well, hello. It's Eric Topol with Ground Truths, and I am just thrilled today to welcome Carl Zimmer, who is one of the great science journalists of our times. He's written 14 books. He writes for the New York Times and many other venues of great science, journalism, and he has a new book, which I absolutely love called Air-Borne. And you can see I have all these rabbit pages tagged and there's lots to talk about here because this book is the book of air. I mean, we're talking about everything that you ever wanted to know about air and where we need to go, how we missed the boat, and Covid and everything else. So welcome, Carl.

Carl Zimmer (00:51):

Thanks so much. Great to be here.

A Book Inspired by the Pandemic

Eric Topol (00:54):

Well, the book starts off with the Skagit Valley Chorale that you and your wife Grace attended a few years later, I guess, in Washington, which is really interesting. And I guess my first question is, it had the look that this whole book was inspired by the pandemic, is that right?

Carl Zimmer (01:18):

Certainly, the seed was planted in the pandemic. I was working as a journalist at the New York Times with a bunch of other reporters at the Times. There were lots of other science writers also just trying to make sense of this totally new disease. And we were talking with scientists who were also trying to make sense of the disease. And so, there was a lot of uncertainty, ambiguity, and things started to come into focus. And I was really puzzled by how hard it was for consensus to emerge about how Covid spread. And I did some reporting along with other people on this conflict about was this something that was spreading on surfaces or was it the word people were using was airborne? And the World Health Organization said, no, it's not airborne, it's not airborne until they said it was airborne. And that just seemed like not quantum physics, you know what I'm saying? In the sense that it seemed like that would be the kind of thing that would get sorted out pretty quickly. And I think that actually more spoke to my own unfamiliarity with the depth of this field. And so, I would talk to experts like say, Donald Milton at the University of Maryland. I'd be like, so help me understand this. How did this happen? And he would say, well, you need to get to know some people like William Wells. And I said, who?

Eric Topol (02:50):

Yeah, yeah, that's what I thought.

Carl Zimmer (02:53):

Yeah, there were just a whole bunch of people from a century ago or more that have been forgotten. They've been lost in history, and yet they were real visionaries, but they were also incredibly embattled. And the question of how we messed up understanding why Covid was airborne turned out to have an answer that took me back thousands of years and really plunged me into this whole science that's known as aerobiology.

Eric Topol (03:26):

Yeah, no, it's striking. And we're going to get, of course, into the Covid story and how it got completely botched as to how it was being transmitted. But of course, as you go through history, you see a lot of the same themes of confusion and naysayers and just extraordinary denialism. But as you said, this goes back thousands of years and perhaps the miasma, the moral stain in the air that was start, this is of course long before there was thing called germ theory. Is that really where the air thing got going?

A Long History of Looking Into Bad Air

Carl Zimmer (04:12):

Well, certainly some of the earliest evidence we have that people were looking at the air and thinking about the air and thinking there's something about the air that matters to us. Aristotle thought, well, there's clearly something important about the air. Life just seems to be revolve around breathing and he didn't know why. And Hippocrates felt that there could be this stain on the air, this corruption of the air, and this could explain why a lot of people in a particular area, young and old, might suddenly all get sick at the same time. And so, he put forward this miasma theory, and there were also people who were looking at farm fields and asking, well, why are all my crops dead suddenly? What happened? And there were explanations that God sends something down to punish us because we've been bad, or even that the air itself had a kind of miasma that affected plants as well as animals. So these ideas were certainly there, well over 2,000 years ago.

Eric Topol (05:22):

Now, as we go fast forward, we're going to get to, of course into the critical work of William and Mildred Wells, who I'd never heard of before until I read your book, I have to say, talk about seven, eight decades filed into oblivion. But before we get to them, because their work was seminal, you really get into the contributions of Louis Pasteur. Maybe you could give us a skinny on what his contributions were because I was unaware of his work and the glaciers, Mer de Glace and figuring out what was going on in the air. So what did he really do to help this field?

Carl Zimmer (06:05):

Yeah, and this is another example of how we can kind of twist and deform history. Louis Pasteur is a household name. People know who Louis Pasteur is. People know about pasteurization of milk. Pasteur is associated with vaccines. Pasteur did other things as well. And he was also perhaps the first aerobiologist because he got interested in the fact that say, in a factory where beet juice was being fermented to make alcohol, sometimes it would spoil. And he was able to determine that there were some, what we know now are bacteria that were getting into the beet juice. And so, it was interrupting the usual fermentation from the yeast. That in itself was a huge discovery. But he was saying, well, wait, so why are there these, what we call bacteria in the spoiled juice? And he thought, well, maybe they just float in the air.

Carl Zimmer (07:08):

And this was really a controversial idea in say, 1860, because even then, there were many people who were persuaded that when you found microorganisms in something, they were the result of spontaneous generation. In other words, the beet juice spontaneously produced this life. This was standard view of how life worked and Pasteur was like, I'm not sure I buy this. And this basically led to him into an incredible series of studies around Paris. He would have a flask, and he'd have a long neck on it, and the flask was full of sterile broth, and he would just take it places and he would just hold it there for a while, and eventually bacteria would fall down that long neck and they would settle in the broth, and they would multiply in there. It would turn cloudy so he could prove that there was life in the air.

Carl Zimmer (08:13):

And they went to different places. He went to farm fields, he went to mountains. And the most amazing trip he took, it was actually to the top of a glacier, which was very difficult, especially for someone like Pasteur, who you get the impression he just hated leaving the lab. This was not a rugged outdoorsman at all. But there he is, climbing around on the ice with this flask raising it over his head, and he caught bacteria there as well. And that actually was pivotal to destroying spontaneous generation as a theory. So aerobiology among many, many other things, destroyed this idea that life could spontaneously burst into existence.

Eric Topol (08:53):

Yeah, no. He says ‘these gentlemen, are the germs of microscopic beings’ shown in the existence of microorganisms in the air. So yeah, amazing contribution. And of course, I wasn't familiar with his work in the air like this, and it was extensive. Another notable figure in the world of germ theory that you bring up in the book with another surprise for me was the great Robert Koch of the Koch postulates. So is it true he never did the third postulate about he never fulfilled his own three postulates?

Carl Zimmer (09:26):

Not quite. Yeah, so he had these ideas about what it would take to actually show that some particular pathogen, a germ, actually caused a disease, and that involved isolating it from patients, culturing it outside of them. And then actually experimentally infecting an animal and showing the symptoms again. And he did that with things like anthrax and tuberculosis. He nailed that. But then when it came to cholera, there was this huge outbreak in Egypt, and people were still battling over what caused cholera. Was it miasma? Was it corruption in the air, or was it as Koch and others believe some type of bacteria? And he found a particular kind of bacteria in the stool of people who were dying or dead of cholera, and he could culture it, and he consistently found it. And when he injected animals with it, it just didn't quite work.

Eric Topol (10:31):

Okay. Yeah, so at least for cholera, the Koch’s third postulate of injecting in animals, reproducing the disease, maybe not was fulfilled. Okay, that's good.

Eric Topol (10:42):

Now, there's a lot of other players here. I mean, with Fred Meier and Charles Lindbergh getting samples in the air from the planes and Carl Flügge. And before we get to the Wells, I just want to mention these naysayers like Charles Chapin, Alex Langmuir, the fact that they said, well, people that were sensitive to pollen, it was just neurosis. It wasn't the pollen. I mean, just amazing stuff. But anyway, the principles of what I got from the book was the Wells, the husband and wife, very interesting characters who eventually even split up, I guess. But can you tell us about their contributions? Because they're really notable when we look back.

William and Mildred Wells

Carl Zimmer (11:26):

Yeah, they really are. And although by the time they had died around 1960, they were pretty much forgotten already. And yet in the 1930s, the two of them, first at Harvard and then at University of Pennsylvania did some incredible work to actually challenge this idea that airborne infection was not anything real, or at least nothing really to worry about. Because once the miasmas have been cleared away, people who embrace the germ theory of disease said, look, we've got cholera in water. We've got yellow fever in mosquitoes. We've got syphilis in sex. We have all these ways that germs can get from one person to the next. We don't need to worry about the air anymore. Relax. And William Wells thought, I don't know if that's true. And we actually invented a new device for actually sampling the air, a very clever kind of centrifuge. And he started to discover, actually, there's a lot of stuff floating around in the air.

Carl Zimmer (12:37):

And then with a medical student of his, Richard Riley started to develop a physical model. How does this happen? Well, you and I are talking, as we are talking we are expelling tiny droplets, and those droplets can potentially contain pathogens. We can sneeze out big droplets or cough them too. Really big droplets might fall to the floor, but lots of other droplets will float. They might be pushed along by our breath like in a cloud, or they just may be so light, they just resist gravity. And so, this was the basic idea that he put forward. And then he made real headlines by saying, well, maybe there's something that we can do to these germs while they're still in the air to protect our own health. In the same way you'd protect water so that you don't get cholera. And he stumbled on ultraviolet light. So basically, you could totally knock out influenza and a bunch of other pathogens just by hitting these droplets in the air with light. And so, the Wells, they were very difficult to work with. They got thrown out of Harvard. Fortunately, they got hired at Penn, and they lasted there just long enough that they could run an experiment in some schools around Philadelphia. And they put up ultraviolet lamps in the classrooms. And those kids did not get hit by huge measles outbreak that swept through Philadelphia not long afterwards.

Eric Topol (14:05):

Yeah, it's pretty amazing. I had never heard of them. And here they were prescient. They did the experiments. They had this infection machine where they could put the animal in and blow in the air, and it was basically like the Koch's third postulate here of inducing the illness. He wrote a book, William and he’s a pretty confident fellow quoted, ‘the book is not for here and now. It is from now on.’ So he wasn't a really kind of a soft character. He was pretty strong, I guess. Do you think his kind of personality and all the difficulties that he and his wife had contributed to why their legacy was forgotten by most?

Carl Zimmer (14:52):

Yes. They were incredibly difficult to work with, and there's no biography of the Wellses. So I had to go into archives and find letters and unpublished documents and memos, and people will just say like, oh my goodness, these people are so unbearable. They just were fighting all the time. They were fighting with each other. They were peculiar, particularly William was terrible with language and just people couldn't deal with them. So because they were in these constant fights, they had very few friends. And when you have a big consensus against you and you don't have very many friends to not even to help you keep a job, it's not going to turn out well, unfortunately. They did themselves no favors, but it is still really remarkable and sad just how much they figured out, which was then dismissed and forgotten.

Eric Topol (15:53):

Yeah, I mean, I'm just amazed by it because it's telling about your legacy in science. You want to have friends, you want to be, I think, received well by your colleagues in your community. And when you're not, you could get buried, your work could get buried. And it kind of was until, for me, at least, your book Air-Borne. Now we go from that time, which is 60, 70 years ago, to fast forward H1N1 with Linsey Marr from Virginia Tech, who in 2009 was already looking back at the Wells work and saying, wait a minute there's something here that this doesn't compute, kind of thing. Can you give us the summary about Linsey? Of course, we're going to go to 2018 again all before the pandemic with Lydia, but let's first talk about Linsey.

Linsey Marr

See my previous Ground Truths podcast with Prof Marr here

Carl Zimmer (16:52):

Sure. So Linsey Marr belongs to this new generation of scientists in the 21st century who start to individually rediscover the Welles. And then in Lind\sey Marr's case, she was studying air pollution. She's an atmospheric scientist and she's at Virginia Tech. And she and her husband are trying to juggle their jobs and raising a little kid, and their son is constantly coming home from daycare because he's constantly getting sick, or there's a bunch of kids who are sick there and so on. And that got Linsey Marr actually really curious like what's going on because they were being careful about washing objects and so on, and doing their best to keep the kids healthy. And she started looking into ideas about transmission of diseases. And she got very interested in the flu because in 2009, there was a new pandemic, in other words that you had this new strain of influenza surging throughout the world. And so, she said, well, let me look at what people are saying. And as soon as she started looking at it, she just said, well, people are saying things that as a physicist I know make no sense. They're saying that droplets bigger than five microns just plummet to the ground.

Carl Zimmer (18:21):

And in a way that was part of a sort of a general rejection of airborne transmission. And she said, look, I teach this every year. I just go to the blackboard and derive a formula to show that particles much bigger than this can stay airborne. So there's something really wrong here. And she started spending more and more time studying airborne disease, and she kept seeing the Welles as being cited. And she was like, who are these? Didn't know who they were. And she had to dig back because finding his book is not easy, I will tell you that. You can't buy it on Amazon. It's like it was a total flop.

Eric Topol (18:59):

Wow.

Carl Zimmer (19:00):

And eventually she started reading his papers and getting deeper in it, and she was like, huh. He was pretty smart. And he didn't say any of the things that people today are claiming he said. There's a big disconnect here. And that led her into join a very small group of people who really were taking the idea of airborne infection seriously, in the early 2000s.

Lydia Bourouiba

Eric Topol (19:24):

Yeah, I mean, it's pretty incredible because had we listened to her early on in the pandemic and many others that we're going to get into, this wouldn't have gone years of neglect of airborne transmission of Covid. Now, in 2018, there was, I guess, a really important TEDMED talk by Lydia. I don't know how you pronounce her last name, Bourouiba or something. Oh, yeah. And she basically presented graphically. Of course, all this stuff is more strained for people to believe because of the invisibility story, but she, I guess, gave demos that were highly convincing to her audience if only more people were in her audience. Right?

Carl Zimmer (20:09):

That's right. That's right. Yeah. So Lydia was, again, not an infectious disease expert at first. She was actually trained as a physicist. She studied turbulence like what you get in spinning galaxies or spinning water in a bathtub as it goes down the drain. But she was very taken aback by the SARS outbreak in 2003, which did hit Canada where she was a student.

Carl Zimmer (20:40):

And it really got her getting interested in infectious diseases, emerging diseases, and asking herself, what tools can I bring from physics to this? And she's looked into a lot of different things, and she came to MIT and MIT is where Harold Edgerton built those magnificent stroboscope cameras. And we've all seen these stroboscope images of the droplets of milk frozen in space, or a bullet going through a card or things like that that he made in the 1930s and 1940s and so on. Well, one of the really famous images that was used by those cameras was a sneeze actually, around 1940. That was the first time many Americans would see these droplets frozen in space. Of course, they forgot them.

Carl Zimmer (21:34):

So she comes there and there's a whole center set up for this kind of high-speed visualization, and she starts playing with these cameras, and she starts doing experiments with things like breathing and sneezes and so on. But now she's using digital video, and she discovers that she goes and looks at William Wells and stuff. She's like, that's pretty good, but it's pretty simple. It's pretty crude. I mean, of course it is. It was in the 1930s. So she brings a whole new sophistication of physics to studying these things, which she finds that, especially with a sneeze, it sort of creates a new kind of physics. So you actually have a cloud that just shoots forward, and it even carries the bigger droplets with it. And it doesn't just go three feet and drop. In her studies looking at her video, it could go 10 feet, 20 feet, it could just keep going.

Eric Topol (22:24):

27 feet, I think I saw. Yeah, right.

Carl Zimmer (22:26):

Yeah. It just keeps on going. And so, in 2018, she gets up and at one of these TEDMED talks and gives this very impressive talk with lots of pictures. And I would say the world didn't really listen.

Eric Topol (22:48):

Geez and amazing. Now, the case that you, I think centered on to show how stupid we were, not everyone, not this group of 36, we're going to talk about not everyone, but the rest of the world, like the WHO and the CDC and others was this choir, the Skagit Valley Chorale in Washington state. Now, this was in March 2020 early on in the pandemic, there were 61 people exposed to one symptomatic person, and 52 were hit with Covid. 52 out of 61, only 8 didn't get Covid. 87% attack rate eventually was written up by an MMWR report that we'll link to. This is extraordinary because it defied the idea of that it could only be liquid droplets. So why couldn't this early event, which was so extraordinary, opened up people's mind that there's not this six-foot rule and it’s all these liquid droplets and the rest of the whole story that was wrong.

Carl Zimmer (24:10):

I think there's a whole world of psychological research to be done on why people accept or don't accept scientific research and I'm not just talking about the public. This is a question about how science itself works, because there were lots of scientists who looked at the claims that Linsey Marr and others made about the Skagit Valley Chorale outbreak and said, I don't know, I'm not convinced. You didn't culture viable virus from the air. How do you really know? Really, people have said that in print. So it does raise the question of a deep question, I think about how does science judge what the right standard of proof is to interpret things like how diseases spread and also how to set public health policy. But you're certainly right that and March 10th, there was this outbreak, and by the end of March, it had started to make news and because the public health workers were figuring out all the people who were sick and so on, and people like Linsey Marr were like, this kind of looks like airborne to me, but they wanted to do a closer study of it. But still at that same time, places like the World Health Organization (WHO) were really insisting Covid is not airborne.

“This is so mind-boggling to me. It just made it obvious that they [WHO] were full of s**t.”—Jose-Luis Jimenez

Getting It Wrong, Terribly Wrong

Eric Topol (25:56):

It's amazing. I mean, one of the quotes that there was, another one grabbed me in the book, in that group of the people that did air research understanding this whole field, the leaders, there's a fellow Jose-Luis Jimenez from University of Colorado Boulder, he said, ‘this is so mind-boggling to me. It just made it obvious that they were full of s**t.’ Now, that's basically what he's saying about these people that are holding onto this liquid droplet crap and that there's no airborne. But we know, for example, when you can't see cigarette smoke, you can't see the perfume odor, but you can smell it that there's stuff in the air, it's airborne, and it's not necessarily three or six feet away. There's something here that doesn't compute in people's minds. And by the way, even by March and April, there were videos like the one that Lydia showed in 2018 that we're circling around to show, hey, this stuff is all over the place. It's not just the mouth going to the other person. So then this group of 36 got together, which included the people we were talking about, other people who I know, like Joe Allen and many really great contributors, and they lobbied the CDC and the WHO to get with it, but it seemed like it took two years.

Carl Zimmer (27:32):

It was a slow process, yes. Yes. Because well, I mean, the reason that they got together and sort of formed this band is because early on, even at the end of January, beginning of February 2020, people like Joe Allen, people like Linsey Marr, people like Lidia Morawska in Australia, they were trying to raise the alarm. And so, they would say like, oh, I will write up my concerns and I will get it published somewhere. And journals would reject them and reject them and reject them. They'd say, well, we know this isn't true. Or they'd say like, oh, they're already looking into it. Don't worry about it. This is not a reason for concern. All of them independently kept getting rejected. And then at the same time, the World Health Organization was going out of their way to insist that Covid is not airborne. And so, Lidia Morawska just said like, we have to do something. And she, from her home in Australia, marshaled first this group of 36 people, and they tried to get the World Health Organization to listen to them, and they really felt very rebuffed it didn't really work out. So then they went public with a very strong open letter. And the New York Times and other publications covered that and that really started to get things moving. But still, these guidelines and so on were incredibly slow to be updated, let alone what people might actually do to sort of safeguard us from an airborne disease.

Eric Topol (29:15):

Well, yeah, I mean, we went from March 2020 when it was Captain Obvious with the choir to the end of 2021 with Omicron before this got recognized, which is amazing to me when you look back, right? That here you've got millions of people dying and getting infected, getting Long Covid, all this stuff, and we have this denial of what is the real way of transmission. Now, this was not just a science conflict, this is that we had people saying, you don't need to wear a mask. People like Jerome Adams, the Surgeon General, people like Tony Fauci before there was an adjustment later, oh, you don't need masks. You just stay more than six feet away. And meanwhile, the other parts of the world, as you pointed out in Japan with the three Cs, they're already into, hey, this is airborne and don't go into rooms indoors with a lot of people and clusters and whatnot. How could we be this far off where the leading public health, and this includes the CDC, are giving such bad guidance that basically was promoting Covid spread.

Carl Zimmer (30:30):

I think there are a number of different reasons, and I've tried to figure that out, and I've talked to people like Anthony Fauci to try to better understand what was going on. And there was a lot of ambiguity at the time and a lot of mixed signals. I think that also in the United States in particular, we were dealing with a really bad history of preparing for pandemics in the sense that the United States actually had said, we might need a lot of masks for a pandemic, which implicitly means that we acknowledge that the next pandemic might to some extent be airborne. At least our healthcare folks are going to need masks, good masks, and they stockpiled them, and then they started using them, and then they didn't really replace them very well, and supplies ran out, or they got old. So you had someone like Rick Bright who was a public health official in the administration in January 2020, trying to tell everybody, hey, we need masks.

The Mess with Masks

Carl Zimmer (31:56):

And people are like, don't worry about it, don't worry about it. Look, if we have a problem with masks, he said this, and he recounted this later. Look, if the health workers run out of masks, we just tell the public just to not use masks and then we'll have enough for the health workers. And Bright was like, that makes no sense. That makes no sense. And lo and behold, there was a shortage among American health workers, and China was having its own health surge, so they were going to be helping us out, and it was chaos. And so, a lot of those messages about telling the public don't wear a mask was don't wear a mask, the healthcare workers need them, and we need to make sure they have enough. And if you think about that, there's a problem there.

Carl Zimmer (32:51):

Yeah, fine. Why don't the healthcare workers have their own independent supply of masks? And then we can sort of address the question, do masks work in the general community? Which is a legitimate scientific question. I know there are people who are say, oh, masks don't work. There's plenty of studies that show that they can reduce risk. But unfortunately, you actually had people like Fauci himself who were saying like, oh, you might see people wearing masks in other countries. I wouldn't do it. And then just a few weeks later when it was really clear just how bad things were getting, he turns around and says, people should wear masks. But Jerome Adams, who you mentioned, Surgeon General, he gets on TV and he's trying to wrap a cloth around his face and saying, look, you can make your own mask. And it was not ideal, shall we say?

Eric Topol (33:55):

Oh, no. It just led to mass confusion and the anti-science people were having just a field day for them to say that these are nincompoops. And it just really, when you look back, it's sad. Now, I didn't realize the history of the N95 speaking of healthcare workers and fitted masks, and that was back with the fashion from the bra. I mean, can you tell us about that? That's pretty interesting.

Carl Zimmer (34:24):

Yeah. Yeah, it's a fascinating story. So there was a woman who was working for 3M. She was consulting with them on just making new products, and she really liked the technology they used for making these sort of gift ribbons and sort of blown-fiber. And she's like, wow, you should think about other stuff. How about a bra? And so, they actually went forward with this sort of sprayed polyester fiber bra, which was getting much nicer than the kind of medieval stuff that women had to put up with before then. And then she's at the same time spending a lot of time in hospitals because a lot of her family was sick with various ailments, and she was looking at these doctors and nurses who were wearing masks, which just weren't fitting them very well. And she thought, wait a minute, you could take a bra cup and just basically fit it on people's faces.

Carl Zimmer (35:29):

She goes to 3M and is like, hey, what about this? And they're like, hmm, interesting. And at first it didn't seem actually like it worked well against viruses and other pathogens, but it was good on dust. So it started showing up in hardware stores in the 70s, and then there were further experiments that basically figured showed you could essentially kind of amazingly give the material a little static charge. And that was good enough that then if you put it on, it traps droplets that contain viruses and doesn't let them through. So N95s are a really good way to keep viruses from coming into your mouth or going out.

Eric Topol (36:14):

Yeah. Well, I mean it's striking too, because in the beginning, as you said, when there finally was some consensus that masks could help, there wasn't differentiation between cotton masks, surgical masks, KN95s. And so, all this added to the mix of ambiguity and confusion. So we get to the point finally that we understand the transmission. It took way too long. And that kind of tells the Covid story. And towards the end of the book, you're back at the Skagit Valley Chorale. It's a full circle, just amazing story. Now, it also brings up all lessons that we've learned and where we're headed with this whole knowledge of the aerobiome, which is fascinating. I didn't know that we breathe 2000 to 3000 gallons a day of air, each of us.

Every Breath We Take

Eric Topol (37:11):

Wow, I didn't know. Well, of course, air is a vector for disease. And of course, going back to the Wells, the famous Wells that have been, you've brought them back to light about how we're aerial oysters. So these things in the air, which we're going to get to the California fires, for example, they travel a long ways. Right? We're not talking about six feet here. We're talking about, can you tell us a bit about that?

Carl Zimmer (37:42):

Well, yeah. So we are releasing living things into the air with every breath, but we're not the only ones. So I'm looking at you and I see beyond you the ocean and the Pacific Ocean. Every time those waves crash down on the surf, it's spewing up vast numbers of tiny droplets, kind of like the ocean's own lungs, spraying up droplets, some of which have bacteria and viruses and other living things. And those go up in the air. The wind catches them, and they blow around. Some of them go very, very high, many, many miles. Some of them go into the clouds and they do blow all over the place. And so, science is really starting to come into its own of studying the planetary wide pattern of the flow of life, not just for oceans, but from the ground, things come out of the ground all of the time. The soil is rich with microbes, and those are rising up. Of course, there’s plants, we are familiar with plants having pollen, but plants themselves are also slathered in fungi and other organisms. They shed those into the air as well. And so, you just have this tremendous swirl of life that how high it can go, nobody's quite sure. They can certainly go up maybe 12 miles, some expeditions, rocket emissions have claimed to find them 40 miles in the air.

Carl Zimmer (39:31):

It's not clear, but we're talking 10, 20, 30 miles up is where all this life gets. So people call this the aerobiome, and we're living in it. It's like we're in an ocean and we're breathing in that ocean. And so, you are breathing in some of those organisms literally with every breath.

Eric Topol (39:50):

Yeah, no, it's extraordinary. I mean, it really widens, the book takes us so much more broad than the narrow world of Covid and how that got all off track and gives us the big picture. One of the things that happened more recently post Covid was finally in the US there was the commitment to make buildings safer. That is adopting the principles of ventilation filtration. And I wonder if you could comment at that. And also, do you use your CO2 monitor that you mentioned early in the book? Because a lot of people haven't gotten onto the CO2 monitor.

Carl Zimmer (40:33):

So yes, I do have a CO2 monitor. It's in the other room. And I take it with me partly to protect my own health, but also partly out of curiosity because carbon dioxide (CO2) in the room is actually a pretty good way of figuring out how much ventilation there is in the room and what your potential risk is of getting sick if someone is breathing out Covid or some other airborne disease. They're not that expensive and they're not that big. And taking them on planes is particularly illuminating. It's just incredible just how high the carbon dioxide rate goes up when you're sitting on the plane, they've closed the doors, you haven't taken off yet, shoots way up. Once again, the air and the filter system starts up, it starts going down, which is good, but then you land and back up again. But in terms of when we're not flying, we're spending a lot of our time indoors. Yeah, so you used the word commitment to describe quality standards.

Eric Topol (41:38):

What's missing is the money and the action, right?

Carl Zimmer (41:42):

I think, yeah. I think commitment is putting it a little strongly.

Eric Topol (41:45):

Yeah. Sorry.

Carl Zimmer (41:45):

Biden administration is setting targets. They're encouraging that that people meet certain targets. And those people you mentioned like Joe Allen at Harvard have actually been putting together standards like saying, okay, let's say that when you build a new school or a new building, let's say that you make sure that you don't get carbon dioxide readings above this rate. Let's try to get 14 liters per second per person of ventilated fresh air. And they're actually going further. They've actually said, now we think this should be law. We think these should be government mandates. We have government mandates for clean water. We have government mandates for clean food. We don't just say, it'd be nice if your bottled water didn't have cholera on it in it. We'll make a little prize. Who's got the least cholera in their water? We don't do that. We don't expect that. We expect more. We expect when you get the water or if you get anything, you expect it to be clean and you expect people to be following the law. So what Joseph Allen, Lidia Morawska, Linsey Marr and others are saying is like, okay, let's have a law.

Eric Topol (43:13):

Yeah. No, and I think that distinction, I've interviewed Joe Allen and Linsey Marr on Ground Truths, and they've made these points. And we need the commitment, I should say, we need the law because otherwise it's a good idea that doesn't get actualized. And we know how much keeping ventilation would make schools safer.

Carl Zimmer (43:35):

Just to jump in for a second, just to circle back to William and Mildred Wells, none of what I just said is new. William and Mildred Wells were saying over and over again in speeches they gave, in letters they wrote to friends they were like, we've had this incredible revolution in the early 1900s of getting clean water and clean food. Why don't we have clean air yet? We deserve clean air. Everyone deserves clean air. And so, really all that people like Linsey Marr and Joseph Allen and others are doing is trying to finally deliver on that call almost a century later.

Eric Topol (44:17):

Yeah, totally. That's amazing how it's taken all this time and how much disease and morbidity even death could have been prevented. Before I ask about planning for the future, I do want to get your comments about the dirty air with the particulate matter less than 2.5 particles and what we're seeing now with wildfires, of course in Los Angeles, but obviously they're just part of what we're seeing in many parts of the world and what that does, what carries so the dirty air, but also what we're now seeing with the crisis of climate change.

Carl Zimmer (45:01):

So if you inhale smoke from a wildfire, it's not going to start growing inside of you, but those particles are going to cause a lot of damage. They're going to cause a lot of inflammation. They can cause not just lung damage, but they can potentially cause a bunch of other medical issues. And unfortunately, climate change plus the increasing urbanization of these kinds of environments, like in Southern California where fires, it's a fire ecology already. That is going to be a recipe for more smoke in the air. We will be, unfortunately, seeing more fire. Here in the Northeast, we were dealing with really awful smoke coming all the way from Canada. So this is not a problem that respects borders. And even if there were no wildfires, we still have a huge global, terrible problem with particulate matter coming from cars and coal fire power plants and so on. Several million people, their lives are cut short every year, just day in, day out. And you can see pictures in places like Delhi and India and so on. But there are lots of avoidable deaths in the United States as well, because we're starting to realize that even what we thought were nice low levels of air pollution probably are still killing more people than we realized.

Eric Topol (46:53):

Yeah, I mean, just this week in Nature is a feature on how this dirty air pollution, the urbanization that’s leading to brain damage, Alzheimer’s, but also as you pointed out, it increases everything, all-cause mortality, cardiovascular, various cancers. I mean, it's just bad news.

Carl Zimmer (47:15):

And one way in which the aerobiome intersects with what we're talking about is that those little particles floating around, things can live on them and certain species can ride along on these little particles of pollution and then we inhale them. And there's some studies that seem to suggest that maybe pathogens are really benefiting from riding around on these. And also, the wildfire smoke is not just lofting, just bits of dead plant matter into the air. It's lofting vast numbers of bacteria and fungal spores into the air as well. And then those blow very, very far away. It's possible that long distance winds can deliver fungal spores and other microorganisms that can actually cause certain diseases, this Kawasaki disease or Valley fever and so on. Yeah, so everything we're doing is influencing the aerobiome. We're changing the world in so many ways. We're also changing the aerobiome.

Eric Topol (48:30):

Yeah. And to your point, there were several reports during the pandemic that air pollution potentiated SARS-CoV-2 infections because of that point that you're making that is as a carrier.

Carl Zimmer (48:46):

Well, I've seen some of those studies and it wasn't clear to me. I'm not sure that SARS-CoV-2 can really survive like long distances outdoors. But it may be that, it kind of weakens people and also sets up their lungs for a serious disease. I'm not as familiar with that research as I'd like to be.

Eric Topol (49:11):

Yeah, no, it could just be that because they have more inflammation of their lungs that they're just more sensitive to when they get the infection. But there seems like you said, to be some interactions between pathogens and polluted air. I don't know that we want to get into germ warfare because that's whole another topic, but you cover that well, it's very scary stuff.

Carl Zimmer (49:37):

It’s the dark side of aerobiology.

Eric Topol (49:39):

Oh my gosh, yes. And then the last thing I wanted just to get into is, if we took this all seriously and learned, which we don't seem to do that well in some respects, wouldn’t we change the way, for example, the way our cities, the way we increase our world of plants and vegetation, rather than just basically take it all down. What can we do in the future to make our ecosystem with air a healthier one?

Carl Zimmer (50:17):

I think that's a really important question. And it sounds odd, but that's only because it's unfamiliar. And even after all this time and after the rediscovery of a lot of scientists who had been long forgotten, there's still a lot we don't know. So there is suggestive research that when we breathe in air that's blowing over vegetation, forest and so on. That's actually in some ways good for our health. We do have a relationship with the air, and we've had it ever since our ancestors came out the water and started breathing with their lungs. And so, our immune systems may be tuned to not breathing in sterile air, but we don't understand the relationship. And so, I can't say like, oh, well, here's the prescription. We need to be doing this. We don't know.

Eric Topol (51:21):

Yeah. No, it's fascinating.

Carl Zimmer (51:23):

We should find out. And there are a few studies going on, but not many I would have to say. And the thing goes for how do we protect indoor spaces and so on? Well, we kind of have an idea of how airborne Covid is. Influenza, we're not that sure and there are lots of other diseases that we just don't know. And you certainly, if a disease is not traveling through the air at all, you don't want to take these measures. But we need to understand they're spread more and it's still very difficult to study these things.

Eric Topol (52:00):

Yeah, such a great point. Now before we wrap up, is there anything that you want to highlight that I haven't touched on in this amazing book?

Carl Zimmer (52:14):

I hope that when people read it, they sort of see that science is a messy process and there aren't that many clear villains and good guys in the sense that there can be people who are totally, almost insanely wrong in hindsight about some things and are brilliant visionaries in other ways. And one figure that I learned about was Max von Pettenkofer, who really did the research behind those carbon dioxide meters. He figured out in the mid-1800s that you could figure out the ventilation in a room by looking at the carbon dioxide. We call it the Pettenkofer number, how much CO2 is in the room. Visionary guy also totally refused to believe in the germ theory of disease. He shot it tooth in the nail even. He tried to convince people that cholera was airborne, and he did it. He took a vial. He was an old man. He took a vial full of cholera. The bacteria that caused cholera drank it down to prove his point. He didn't feel well afterwards, but he survived. And he said, that's proof. So this history of science is not the simple story that we imagine it to be.

Eric Topol (53:32):

Yeah. Well, congratulations. This was a tour de force. You had to put in a lot of work to pull this all together, and you're enlightening us about air like never before. So thanks so much for joining, Carl.

Carl Zimmer (53:46):

It was a real pleasure. Thanks for having me.

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—how are gut microbiome drives sugar cravings

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—the surprise finding about doctors and A.I.

In this podcast with Dr. Emily Silverman, an internist and founder of The Nocturnists, an award winning podcast and live show, we discuss what inspired her in medicine, what led to her disillusionment, the essentiality of storytelling, of recognizing uncertainty, the limits of A.I., and promoting humanity in medicine. The audio is available on iTunes and Spotify. The full video is linked here, at the top, and also can be found on YouTube.

“Storytelling is medicine's currency. Storytelling is not just an act of self-healing; it may actually create better physicians.”—Emily Silverman

Transcript with links to audio and relevant publications, websites

Eric Topol (00:07):

Well, hello. This is Eric Topol with Ground Truths, and with me, I am delighted to welcome Dr. Emily Silverman, who is Assistant Volunteer Professor of Medicine at UCSF, an old training grounds for me. And we're going to talk about some of the experience she's had there and she is the Founder of the remarkably recognized podcast, The Nocturnists. It's more than a podcast folks. We'll talk about that too. So Emily, welcome.

Emily Silverman (00:40):

Thank you for having me.

Inspiration by Kate McKinnon

Eric Topol (00:42):

Yeah. Well, I thought I would go back to perhaps when we first synapsed, and it goes back to a piece you wrote in JAMA about going to the Saturday Night Live (SNL) with Kate McKinnon. And it was one of my favorite columns, of course, it brought us together kind of simpatico because you were telling a story that was very personal, and a surprise factor added to it. We'll link to it. But it said, ‘Sometime in 2016, I fell in love with SNL comedian Kate McKinnon.’ You wrote, ‘It was something about her slow-mo swagger; her unilateral dimple, flickering in and out of existence; the way she drinks up her characters and sweats them from her pores.’ I mean, you're an incredible writer, no less podcast interviewer, organizer, doctor. And you talked about my sterile clinical life, which was kind of maybe a warning of things to come and about the fact that there's two very different career paths, comedy and medicine. One could argue they are in essence the same. So maybe you could tell us about that experience and about Kate McKinnon who, I mean, she's amazing.

Emily Silverman (02:09):

You're making me blush. Thank you for the kind words about the piece and about the writing, and I'm happy to give you a bit of background on that piece and where it came from. So I was in my internal medicine residency at UCSF and about halfway through residency really found myself hitting a wall. And that is actually what gave birth to The Nocturnists, which is the medical storytelling program that I run. But I think another symptom of my hitting that wall, so to speak, and we can talk more about what exactly that is and what that means, was me really looking outside of medicine and also outside of my typical day-to-day routine to try to find things that were a part of me that I had lost or I had lost touch with those aspects of myself. And one aspect of myself that I felt like I had lost touch to was my humorous side, my sense of humor, my silly side even you could say.

Emily Silverman (03:17):

And throughout my life I have this pattern where when I'm trying to get back in touch with a side of myself, I usually find somebody who represents that and sort of study it, I guess you could say. So in this case, for whatever reason that landed on Kate McKinnon, I just loved the surrealism of her comedy. I loved how absurd she is and loved her personality and so many things. Everything that you just read and really found her and her comedy as an escape, as a way to escape the seriousness of what I was doing on a day-to-day basis in the hospital and reconnect with those humorous sides of myself. So that's the understory. And then the story of the article is, I happened to be traveling to New York for a different reason and found myself standing in line outside of 30 Rock, hoping to get into Saturday Night Live. And there was basically a zero chance that we were going to get in. And part of the reason why is the musical guest that week was a K-pop band called BTS, which is one of the most famous bands in the world. And there were BTS fans like camped out in three circles around 30 Rock. So that week in particular, it was especially difficult to get in. There was just too many people in line. And we were at the very end of the line.

Eric Topol (04:43):

And it was in the pouring rain, too.

Emily Silverman (04:45):

And it was pouring rain. And my husband, God bless him, was there with me and he was like, what are we doing? And I was like, I don't know. I just have a feeling that we should stay in line, just go with it. So we did stay in line and then in the morning we got a number, and the way it works is you get your number and then that evening you show up with your number and our number was some crazy number that we weren't going to get in. But then that evening when we went back with our number to wait in line again to get in, what ended up happening is a young woman in the NBC gift shop, she passed out in the middle of the gift shop and I was right there. And so, I went over to her and was asking her questions and trying to help her out.

Emily Silverman (05:27):

And fortunately, she was fine. I think she just was dehydrated or something, and the security guards were so appreciative. And the next thing I knew, they were sweeping me backstage and up a staircase and in an elevator and they said, thank you so much for your service, welcome to Saturday Night Live. So it became this interesting moment where the very thing that I had been escaping from like medicine and serving and helping people ended up being the thing that gave me access, back to that side of myself, the humorous side. So it was just felt kind of cosmic, one of those moments, like those butterfly wing flapping moments that I decided to write about it and JAMA was kindly willing to publish it.

Eric Topol (06:15):

Well, it drew me to you and recognize you as quite an extraordinary talent. I don't know if you get recognized enough for the writing because it's quite extraordinary, as we'll talk about in some of your other pieces in the New York Times and in other JAMA journals and on and on. But one thing I just would note is that I resort to comedy a lot to deal with hard times, like the dark times we're in right now, so instead of watching the news, I watch Jimmy Kimmel's monologue or Colbert's monologue or the Comedy Show, anything to relieve some of the darkness that we're dealing with right at the moment. And we're going to get back to comedy because now I want to go back, that was in 2019 when you wrote that, but it was in 2016 when you formed The Nocturnists. Now, before you get to that critical path in your career of this new podcast and how it blossomed, how it grew is just beyond belief. But maybe you could tell us about your residency, what was going on while you were a medical resident at UCSF, because I can identify with that. Well, like any medical residency, it's pretty grueling experience and what that was like for you.

Medical Residency

Emily Silverman (07:45):

There were so many wonderful positive aspects of residency and there were so many challenges and difficult aspects of residency. It's all mixed up into this sticky, complicated web of what residency was. On the positive side, some of the most amazing clinicians I've ever met are at UCSF and whether that was seasoned attendings or chief residents who they just seemed to have so many skills, the clinical, the research, the teaching, just amazing, amazing high caliber people to learn from. And of course, the patient population. And at UCSF, we rotate at three different hospitals, the UCSF hospital, the SF General Hospital, which is the public county hospital and the VA hospital. So having the opportunity to see these different patient populations was just such a rich clinical and storytelling opportunity. So there was a lot there that was good, but I really struggled with a few things.

Emily Silverman (08:48):

So one was the fact that I spent so much of my sitting in front of a computer, and that was not something that I expected when I went into medicine when I was young. And I started to learn more about that and how that happened and when that changed. And then it wasn't just the computer, it was the computer and other types of paperwork or bureaucratic hurdles or administrative creep and just all the different ways that the day-to-day work of physicians was being overtaken by nonclinical work. And that doesn't just mean thinking about our patients, but that also means going to the bedside, sitting with our patients, getting to know them, getting to know their families. And so, I started to think a lot about clinical medicine and what it really means to practice and how that's different from how it was 10, 20, 40 years ago.

Emily Silverman (09:43):

And then the other part of it that I was really struggling with was aspects of medical culture. The fact that we were working 80 hour weeks, I was working 28 hour shifts every fourth night, every other month. And the toll that took on my body, and I developed some health issues as a result of that and just felt in a way, here I am a doctor in the business of protecting and preserving health and my own health is kind of being run into the ground. And that didn't make sense to me. And so, I started asking questions about that. So there was a lot there. And at first I thought, maybe this is a me thing or maybe this is a California thing. And eventually I realized this was a national thing and I started to notice headlines, op-eds, articles, even pre-Covid about the epidemic of clinician burnout in this country.

Emily Silverman (10:40):

And there are so many different facets to that. There's the moral injury aspect of it, there's the working conditions and understaffing aspect of it. I learned about how physicians were starting to think about unionizing, which was something that had not really been in the physician, I think consciousness 20, 40 years ago. So just started learning a lot about how medicine had evolved and was continuing to evolve and felt myself wanting to create a space where people could come together and tell stories about what that was like and what their experience was. And that was the birth of The Nocturnists. But I guess that wasn't really your question. Your question was about residency.

Birth of The Nocturnists

Eric Topol (11:20):

That's a good answer actually. It kind of gives the background, lays the foundation of how you took a fork in the road here, which we're going to get into now. We're going to link to The Nocturnists website of course, but you have an intro there about, ‘shatter the myth of the “physician God” reveal the truth: that healthcare workers are human, just like everyone else, and that our humanity is our strength, not our weakness.’ And that's a very deep and important point that you make to get people interested in The Nocturnists. But now you finished your residency, you're now on the faculty, assistant professor at UCSF, and then you have this gathering that you hadn't already named it the Nocturnists yet had you?

Emily Silverman (12:15):

I named it in residency.

Eric Topol (12:17):

Oh, okay in residency. So this was even before you had finished, you started the podcast before you finished?

Emily Silverman (12:25):

Correct. Before we were a podcast, we were a live show. So the very first live show was in 2016, so I consider that the birth year of the program. And then I graduated residency in 2017, so I started it about halfway through residency.

Eric Topol (12:39):

Got it. So tell us about that first live show. I mean, that's pretty amazing. Yeah.

Emily Silverman (12:46):

Yeah. I went to a live taping of The Moth in San Francisco, which some of your listeners may know. The Moth is a live storytelling show in the US, it's often on the radio on NPR. You may have heard it. It's a very ancient way of telling stories. It's more like monologues, people standing up on stage and just spontaneously telling a story the way you would around a campfire or something like that. It's not hyper scripted or anything like that. So I came out of that event feeling really inspired, and I had always loved live performance and live theater. I grew up going to the theater and ended up deciding that I would try that with my community, with the clinicians in my community. So the very first show that we did was in 2016, it was about 40 people in this living room of this Victorian mansion in San Francisco.

Emily Silverman (13:42):

It was a co-op where different people lived. In the living space, they occasionally rented out for meetings and presentations and gatherings, and it was like $90. So I rented that out and people came and residents, physician residents told stories, but a couple of faculty came and told stories as well. And I think that was a really nice way to set the stage that this wasn't just a med student thing or a resident thing, this was for everybody. And there was definitely an electricity in the air at the show. I think a lot of people were experiencing the same thing I was experiencing, which was having questions about the medical system, having questions about medical culture, trying to figure out how they fit into all of that, and in my case, missing my creative side, missing my humorous side. And so, I think that's the reason people came and showed up was that it wasn't just a night out of entertainment and coming was really more out of a hunger to reconnect with some aspect of ourselves that maybe gets lost as we go through our training. So that was the first show, and people kept asking, when are you going to do another one? When are you going to do another one? The rest is history. We have done many shows since then. So that was the beginning.

Eric Topol (14:58):

Well, you've been to many cities for live shows, you sold out hundreds and hundreds of seats, and it's a big thing now. I mean, it's been widely recognized by all sorts of awards, and the podcast and the shows. It's quite incredible. So a derivative of The Moth to medicine, is it always medical people telling stories? Does it also include patients and non-medical people?

Emily Silverman (15:28):

So we're nine years in, and for the first several years, this question came up a lot. What about the patient voice? What about the patient perspective? And the way that I would respond to that question was two ways. First, I would say the line between doctor and patient isn't as bright as you would think. Doctors are also patients. We also have bodies. We also have our own medical and psychiatric conditions and our own doctors and providers who take care of us. So we're all human, we're all patients. That said, I recognize that the doctor, the clinician has its own unique place in society and its own unique perspective. And that's really what I was trying to focus on. I think when you're making art or when you're making a community, people ask a lot about audience. And for me, for those first several years, I was thinking of The Nocturnists as a love letter by healthcare to healthcare. It was something that I was making for and with my community. And in recent months and years, I have been wondering about, okay, what would a new project look like that pulls in the patient voice a bit more? Because we did the clinician thing for several years, and I think there's been a lot of wonderful stories and material that's come out of that. But I'm always itching for the next thing. And it was actually an interview on the podcast I just did with this wonderful person, Susannah Fox.

Eric Topol (17:04):

Oh yeah, I know Susannah. Sure.

Emily Silverman (17:04):

Yeah. She was the chief technology officer at the Department of Health and Human Services from 2015 to 2017, I want to say. And she wrote a book called Rebel Health, which is all about patients who weren't getting what they needed from doctors and researchers and scientists. And so, they ended up building things on their own, whether it was building medical devices on their own, on the fringes or building disease registries and communities, online disease communities on their own. And it was a fabulous book and it was a fabulous interview. And ever since then I've been thinking about what might a project look like through The Nocturnists storytelling ethos that centers and focuses on the patient voice, but that's a new thought. For the first several years, it was much more focused on frontline clinicians as our audience.

Why is Storytelling in Medicine so Important?

Eric Topol (17:55):

And then I mean the storytelling people that come to the shows or listen to the podcast, many of them are not physicians, they're patients, all sorts of people that are not part of the initial focus of who's telling stories. Now, I want to get into storytelling. This is, as you point out in another JAMA piece that kind of was introducing The Nocturnists to the medical community. We’ll link to that, but a few classic lines, ‘Storytelling is medicine's currency. Storytelling is not just an act of self-healing; it may actually create better physicians.’ And then also toward the end of the piece, “Some people also believe that it is unprofessional for physicians to be emotionally vulnerable in front of colleagues. The greater risk, however, is for the healthcare professional to appear superhuman by pretending to not feel grief, suffer from moral distress, laugh at work, or need rest.” And finally, ‘storytelling may actually help to humanize the physician.’ So tell us about storytelling because obviously it's one of the most important, if not the most important form of communication between humans. You nailed it, how important it is in medicine, so how do you conceive it? What makes it storytelling for you?

Emily Silverman (19:25):

It's so surreal to hear you read those words because I haven't read them myself in several years, and I was like, oh, what piece is he talking about? But I remember now. Look, you on your program have had a lot of guests on to talk about the massive changes in medicine that have occurred, including the consolidation of it, the corporatization of it, the ways in which the individual community practice is becoming more and more endangered. And instead what's happening is practices are getting gobbled up and consolidated into these mega corporations and so on and so forth. And I just had on the podcast, the writer Dhruv Khullar, who wrote a piece in the New Yorker recently called the Gilded Age of Medicine is here. And he talks a lot about this and about how there are some benefits to this. For example, if you group practices together, you can have economies of scale and efficiencies that you can't when you have all these scattered individual self-owned practices.

Emily Silverman (20:26):

But I do think there are risks associated with the corporatization of healthcare. The more that healthcare starts to feel like a conveyor belt or a factory or fast food like the McDonald's of healthcare, MinuteClinic, 15 minutes in and out, the more that we risk losing the heart and soul of medicine and what it is; which is it's not as simple as bringing in your car and getting an oil change. I mean, sometimes it is. Sometimes you just need a strep swab and some antibiotics and call it a day. But I think medicine at its best is more grounded in relationships. And so, what is the modern era of medicine doing to those relationships? Those longitudinal relationships, those deeper relationships where you're not just intimately familiar with a patient's creatinine trend or their kidney biopsy results, but you know your patient and their family, and you know their life story a little bit.

Emily Silverman (21:26):

And you can understand how the context of their renal disease, for example, fits into the larger story of their life. I think that context is so important. And so, medicine in a way is, it is a science, but it's also an art. And in some ways it's actually kind of an applied science where you're taking science and applying it to the messy, chaotic truth of human beings and their families and their communities. So I think storytelling is a really important way to think of medicine. And then a step beyond that, not just with the doctor patient interaction, but just with the medical community and medical culture at large. I think helping to make the culture healthier and get people out of this clamped down place where they feel like they have to be a superhuman robot. Let's crack that open a little bit and remind ourselves that just like our patients are human beings, so are we. And so, if we can leverage that, and this is also part of the AI conversation that we're having is like, is AI ever going to fully substitute for a physician? Like, well, what does a physician have that AI doesn't? What does a human being have that a machine doesn’t? And I think these are really deep questions. And so, I think storytelling is definitely related to that. And so, there's just a lot of rich conversation there in those spaces, and I think storytelling is a great way into those conversations.

Eric Topol (22:57):

Yeah. We'll talk about AI too, because that's a fascinating future challenge to this. But while you're talking about it, it reminds me that I'm in clinic every week. My fellow and I have really worked on him to talk to the patients about their social history. They seem to omit that and often times to crack the case of what's really going on and what gets the patient excited or what their concerns are really indexed to is learning about what do they do and what makes them tick and all that sort of thing. So it goes every which way in medicine. And the one that you've really brought out is the one where clinicians are telling their stories to others. Now you've had hundreds and hundreds of these physician related stories. What are some of the ones that you think are most memorable? Either for vulnerability or comedy or something that grabbed you because you’ve seen so many, and heard so many now.

A Memorable Story

Emily Silverman (24:02):

It's true. There have been hundreds of physician stories that have come through the podcast and some non-physician. I mean, we are, because I'm a doctor, I find that the work tends to be more focused around doctors. But we have brought in nurses and other types of clinicians to tell their stories as well, particularly around Covid. We had a lot of diversity of healthcare professionals who contributed their stories. One that stands out is dialogue that we featured in our live show. So most of our live shows up until that point had featured monologues. So people would stand on stage, tell their story one by one, but for this story, we had two people standing on stage and they alternated telling their story. There was a little bit more scripting and massaging involved. There was still some level of improvisation and spontaneity, but it added a really interesting texture to the story.

Emily Silverman (24:58):

And basically, it was a story of these two physicians who during Covid, one of them came out of retirement and the other one I think switched fields and was going to be doing different work during Covid as so many of us did. And they were called to New York as volunteers and ended up meeting in the JFK airport in 2020 and it was like an empty airport. And they meet there and they start talking and they realize that they have all these strange things in common, and they sit next to each other on the plane and they're kind of bonding and connecting about what they're about to do, which is go volunteer at the peak of Covid in New York City, and they end up staying in hotels in New York and doing the work. A lot of it really, really just harrowing work. And they stay connected and they bond and they call each other up in the evenings, how was your day? How was your day? And they stay friends. And so, instead of framing it in my mind as a Covid story, I frame it more as a friendship story. And that one just was really special, I think because of the seriousness of the themes, because of the heartwarming aspect of the friendship and then also because of the format, it was just really unusual to have a dialogue over a monologue. So that was one that stood out. And I believe the title of it is Serendipity in Shutdown. So you can check that out.

Eric Topol (26:23):

That's great. Love it. And I should point out that a lot of these clinical audio diaries are in the US Library of Congress, so it isn't like these are just out there, they're actually archived and it's pretty impressive. While I have you on some of these themes, I mean you're now getting into some bigger topics. You mentioned the pandemic. Another one is Black Voices in Healthcare, and you also got deep into Shame in Medicine. And now I see that you've got a new one coming on Uncertainty in Medicine. Can you give us the skinny on what the Uncertainty in Medicine's going to be all about?

Uncertainty in Medicine

Emily Silverman (27:14):

Yes. So the American Board of Internal Medicine put out a call for grant proposals related to the topic of uncertainty in medicine. And the reason they did that is they identified uncertainty as an area of growth, an area where maybe we don't talk about it enough or we're not really sure how to tolerate it or handle it or teach about it or work with it, work through it in our practice. And they saw that as an area of need. So they put out this call for grants and we put together a grant proposal to do a podcast series on uncertainty in medicine. And we're fortunate enough to be one of the three awardees of that grant. And we've been working on that for the last year. And it's been really interesting, really interesting because the place my mind went first with uncertainty is diagnostic uncertainty.

Emily Silverman (28:07):

And so, we cover that. We cover diagnostic odyssey and how we cope with the fact that we don't know and things like that. But then there's also so many other domains where uncertainty comes up. There's uncertainties around treatment. What do we do when we don't know if the treatment's working or how to assess whether it's working or it's not working and we don't know why. Or managing complex scenarios where it's not clear the best way to proceed, and how do we hold that uncertainty? Prognostic uncertainty is another area. And then all of the uncertainty that pops up related to the systems issues in healthcare. So for example, we spoke to somebody who was diagnosed with colon cancer, metastatic to the liver, ended up having a bunch of radiation of the mets in the liver and then got all this liver scarring and then got liver failure and then needed a liver transplant and saw this decorated transplant surgeon who recommended the transplant was already to have that done.

Emily Silverman (29:06):

And then the insurance denied the liver transplant. And so, dealing with the uncertainty of, I know that I need this organ transplant, but the coverage isn't going to happen, and the spoiler alert is that he ended up appealing several times and moving forward and getting his transplant. So that one has a happy ending, but some people don't. And so, thinking about uncertainty coming up in those ways as well for patients. So for the last year we've been trying to gather these stories and organize them by theme and figure out what are the most salient points. The other exciting thing we've done with the uncertainty series is we've looked to people outside of medicine who navigate high uncertainty environments to see if they have any wisdom or advice to share with the medical community. So for example, we recently interviewed an admiral in the Navy. And this person who was an admiral in the Navy for many years and had to navigate wartime scenarios and also had to navigate humanitarian relief scenarios and how does he think about being in command and dealing with people and resources and it is life or death and holding uncertainty and managing it.

Emily Silverman (30:18):

And he had a lot of interesting things to say about that. Similarly, we spoke to an improvisational dancer who his whole job is to get on stage and he doesn't know what's going to happen. And to me, that sounds terrifying. So it's like how do you deal with that and who would choose that? And so, that's been really fun too, to again, go outside the walls of medicine and see what we can glean and learn from people operating in these different contexts and how we might be able to apply some of those.

Eric Topol (30:51):

Yeah, I mean this is such a big topic because had the medical community been better in communicating uncertainties in medicine, the public trust during the pandemic could have been much higher. And this has led to some of the real challenges that we're seeing there. So I'm looking forward to that series of new additions in The Nocturnists. Now, when you get this group together to have the live show, I take it that they're not rehearsed. You don't really know much about what they're going to do. I mean, it's kind of like the opposite, the un-TED show. TED Talk, whereby those people, they have to practice in Vancouver wherever for a whole week. It's ridiculous. But here, do you just kind of let them go and tell their story or what?

Emily Silverman (31:44):

In the beginning it was more open mic, it was more let them go. And then as the years went on, we moved more toward a TED model where we would pair storytellers with a story coach, and they would work together pretty intensively in the six to eight weeks leading up to the event to craft the story. That said, it was very important to us that people not recite an essay that they memorized word for word, which surprise, surprise physicians really love that idea. We're like, we're so good at memorization and we love certainty. We love knowing word for word what's going to come. And so, it's really more of this hybrid approach where we would help people get in touch with, all right, what are the five main beats of your story? Where are we opening? Where are we closing? How do we get there?

Emily Silverman (32:34):

And so, we'd have a loose outline so that people knew roughly what was going to, but then it wasn't until the night of that we'd fill in the blanks and just kind of see what happens. And that was really exciting because a lot of unexpected things happened. Certain stories that we thought would be really comedic ended up landing with a much more serious and thoughtful tone and vice versa. Some of the stories that we thought were really heavy would unexpectedly get laughs in places that we didn't expect. So I think the magic of live audience is, I guess you could say uncertainty of not quite knowing what's going to happen, and sort of a one time night.

Eric Topol (33:17):

I’d like to have a storytelling coach. That'd be cool. I mean, we could always be better. I mean, it takes me back to the first story you told with the Saturday Night Live and Kate McKinnon, you told the story, it was so great. But to make telling your story, so it's even more interesting, captivating and expressing more emotion and vulnerability and what makes the human side. I mean, that's what I think we all could do, you never could do it perfectly. I mean, that's kind of interesting how you organize that. Alright, well now I want to go back to your career for a moment because you got into The Nocturnists and these shows and you were gradually, I guess here we are in the middle and still a global burnout, depression, suicide among clinicians, especially physicians, but across the board. And you're weaning your time as a faculty member at UCSF. So what was going through your mind in your life at that time? I guess that takes us to now, too.

A Career Move

Emily Silverman (34:36):

Yeah, when I was a little kid, I always wanted to doctor and fully intended when I went to med school and residency to find my way as a physician and didn't really think I would be doing much else. I mean, I'd always love reading and writing and the arts, but I never quite thought that that would become as big of a piece of my career as it has become. But what ended up happening is I finished residency. I took a job in the division of hospital medicine at SF General and worked as a hospitalist for about four years and was doing that and balancing with my medical storytelling nonprofit and eventually realized that it wasn't quite working, it wasn't the right fit. And ended up taking a step back and taking a little break from medicine for a while to try to figure out how am I going to balance this?

Emily Silverman (35:26):

Am I going to shift and go full medicine and retire The Nocturnists? Am I going to go full art, creative journalism, writing and leave clinical medicine behind? Or am I going to continue to proceed in this more hybrid way where I do a little bit of practicing, and I do a little bit of creative on the side? And thus far, I have continued to pursue that middle road. So I ended up starting a new outpatient job, a part-time job that's actually outside of UCSF. I'm still on faculty at UCSF, but my practice now is in private practice. And so, I do that two days a week and it feeds me in a lot of ways and I'm really glad that I've continued to keep that part of myself alive. And then the rest of the days of the week I work from home and some of that is charting and doing clinical work and some of that time is podcasting and working on these other creative projects. So that's where I've landed right now. And I don't know what it will look like in 5, 10, 20 years, but for now it seems to be working.

Taking On Epic

Eric Topol (36:31):

Yeah. Well, I think it's great that you've found the right kind of balance and also the channel for getting your exceptional talent, your niche if you will, in medicine to get it out there because people I think are really deriving a lot of benefit from that. Now, another piece you wrote in the New York Times, I just want to touch on because it is tied to the burnout story. This was a great op-ed, Our Hospital's New Software Frets About My ‘Deficiencies’ and I want to just warn the listeners or readers or watchers that Epic, this company that you wrote about has non-disparaging agreements with hospitals, censors hospitals and doctors to say anything bad about Epic. So when anybody ever writes something, particularly if it's published in a widely read place, the Epic company doesn't like that and they squash it and whatnot. So what was in your mind when you were writing this op-ed about Epic?

Emily Silverman (37:39):

So this came out of personal experience that I had where, and maybe this is some of the reason why the hospital medicine work wore me down so much is the frequent messages and alerts and popups just having a lot of fatigue with that. But also what the popups were saying, the language that they used. So you'd open up your electronic chart and a message would pop up and it would say, you are deficient, or it would say you are a delinquent. And it was this scary red box with an upside down exclamation point or something. And it really started to get to me, and this was definitely in that phase of my life and career where I was peak burnout and just kind of raging into the machine a little bit, you could say, I think right now I'm somewhat past that. I think part of the reason why is, I've been able to get myself out into a more sustainable situation, but ended up, it actually came out of me, this piece poured out of me one night.

Emily Silverman (38:37):

It was like two, three in the morning and my laptop was open and I was laying in bed and my husband was like, go to sleep, go to sleep. And I said, no, this wants to come out, these moments where things just, you just want to give birth, I guess, to something that wants to come out. So I wrote this long piece about Epic and how tone deaf these messages are and how clinicians are, they're working really hard in a really difficult system and just the lack of sensitivity of that language and ended up pitching that to the New York Times. And I think there was something in there that they appreciated about that. There was some humor in there actually. Maybe my Kate McKinnon side came out a little bit. So yes, that piece came out and I think I did get a message or two from a couple folks who worked at Epic who weren't thrilled.

Eric Topol (39:33):

They didn't threaten to sue you or anything though, right?

Emily Silverman (39:35):

They didn't. No

Eric Topol (39:37):

Good.

Emily Silverman (39:37):

Fortunately, yeah.

Medicine and A.I.

Eric Topol (39:38):

Yeah. Wow. Yeah, it was great. And we'll link to that, too. Now, as they say in comedy, we're going to have a callback. We're going to go to AI, which we talked about and touched on. And of course, one of the things AI is thought that it could help reduce the burden of data clerk work that you've talked about and certainly affected you and affects every person in working in medicine. But I wanted to get to this. For me, it was like a ChatGPT moment of November 2022. Recently, I don’t know if you've ever delved into NotebookLM.

Emily Silverman (40:18):

I have.

Eric Topol (40:19):

Okay, so you'll recognize this. You put in a PDF and then you hit audio and it generates a podcast of two agents, a man and a woman who are lively, who accurately take, it could be the most complex science, it could be a book, and you can put 50 of these things in and they have a really engaging conversation that even gets away from some of the direct subject matter and it's humanoid. What do you think about that?

Emily Silverman (40:57):

Well, a lot of what I know about AI, I learned from your book, Eric. And from the subsequent conversation that we had when you came on my podcast to talk about your book. So I'm not sure what I could teach you about this topic that you don't already know, but I think it's a deeply existential question about what it means to be human and how machine intelligence augments that, replaces that, threatens that. I don't really know how to put it. I had Jamie Metzl on the podcast. He's this great historian and science policy expert, and he was saying, I don't like the phrase artificial intelligence because I don't think that's what we're making. I think we're making machine intelligence and that's different from human intelligence. And one of the differences is human beings have physical bodies. So being a human is an embodied experience.

Emily Silverman (41:57):

A machine can’t enjoy, I was going to say a cheeseburger and I was like, wait, I'm talking to a cardiologist. So a machine intelligence being can't enjoy a cucumber salad, a machine intelligence can't feel the endorphins of exercise or have sex or just have all of these other experiences that human beings have because they have bodies. Now, does empathy and emotion and human connection and relationships also fall into that category? I don't know. What is the substrate of empathy? What is the substrate of human connection and relationships and experience? Can it be reduced to zeros and ones or whatever, quantum computing, half zeros and half ones existing simultaneously on a vibrating plane, or is there something uniquely human about that? And I actually don't know the answer or where the edges are. And I think in 5, 10, 20 years, we'll know a lot more about what that is and what that means.

Emily Silverman (42:55):

What does that mean for medicine? I don't know about the human piece of it, but I think just practically speaking, I believe it will transform the way that we do medicine on so many levels. And this is what your book is about. Some of it is image analysis and EKG analysis, X-ray analysis and MRI analysis. And some of it is cognition, like diagnostic reasoning, clinical reasoning, things like that. I already use OpenEvidence all the time. I don't know if you use it. It's this basically a search engine kind of GPT like search engine that's trained on high quality medical evidence. I'm always going to OpenEvidence with questions. And I actually saw a headline recently, oh gosh, I'll have to fish it out and email it to you and you can link it in the show notes. But it's a little bit about how medical education and also medical certification and testing is going to have to quickly bring itself up to speed on this.

Emily Silverman (43:56):

The USMLE Step 1 exam, which all physicians in the US have to pass in order to practice medicine. When I took it anyway, which was back in I think 2012, 2013, was very recall based. It was very much based on memorization and regurgitation. Not all, some of it was inference and analysis and problem solving, but a lot of it was memorization. And as you said, I think Eric on our interview on my podcast, that the era of the brainiac memorizing Doogie Howser physician is over. It's not about that anymore. We can outsource that to machines. That's actually one of the things that we can outsource. So I'm excited to see how it evolves. I hope that medical schools and hospitals and institutions find ways safely, of course, to embrace and use this technology because I think it can do a lot of good, which is also what your book is about, the optimistic lens of your book.

Eric Topol (44:55):

Well, what I like though is that what you're trying to do in your work that you're passionate about is bringing back and amplifying humanity. Enriching the humanity in medicine. Whether that's physicians understanding themselves better and realizing that they are not just to be expected to be superhuman or non-human or whatever, to how we communicate, how we feel, experience the care of patients, the privilege of care of patients. So that's what I love about your efforts to do that. And I also think that people keep talking about artificial general intelligence (AGI), but that's not what we are talking about here today. We're talking about human emotions. Machines don't cry, they don't laugh. They don't really bond with humans, although they try to. I don't know that you could ever, so this fixation on AGI is different than what we're talking about in medicine. And I know you’re destined to be a leader in that you already are. But I hope you'll write a book about medical storytelling and the humanity and medicine, because a natural for this and you're writing it is just great. Have you thought about doing that?

Emily Silverman (46:24):

It's very kind of you to say. I have thought about if I were to embark on a book project, what would that look like? And I have a few different ideas and I'm not sure. I'm not sure. Maybe I'll consult with you offline about that.

Eric Topol (46:42):

Alright, well I'd like to encourage you because having read your pieces that some of them cited here you have it. You really are a communicator extraordinaire. So anyway, Emily, thank you for joining today. I really enjoyed our conversation and your mission not just to be a physician, which is obviously important, but also to try to enhance the humanity in medicine, in the medical community particularly. So thank you.

Emily Silverman (47:14):

Thank you. Thank you for having me.

***************************************

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The Chief Scientific Advisor at Novo Nordisk, Lotte Bjerre Knudsen, was the key force who pushed hard to develop GLP-1 drugs for treating obesity and subsequently for Alzheimer’s. She was recently recognized by the 2024 Lasker Medical Research Award, and the 2024 AAAS Bhaumik Breakthrough of the Year Award. That recognition is richly deserved, since it is unclear if the GLP-1 drug path to obesity treatment, and all of the associated benefits, would have been seen at this time without her influence. That’s especially true given the mystery for why people with Type 2 diabetes (for which these drugs were used for many years) did not exhibit much in the way of weight loss. We discussed that and the future of these drugs, including their potential to prevent neurodegenerative diseases. And about dressing up in pink!

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Our entire conversation can also be seen by video at YouTube along with all of the Ground Truths podcasts. If you like the video format, please subscribe to this channel. Even if you prefer video, please take a look at the transcript with graphics and useful links to citations.

A Video Clip below on the barriers of a woman scientist to push Novo Nordisk to develop GLP-1 for obesity.

“I was always just been a nerdy little scientist who kind of found home here in this company for 35 years.”—Lotte Bjerre Knudsen, 60 Minutes

Transcript with Links to audio and external references

Eric Topol (00:06):

Well, hello, it's Eric Topol with Ground Truths, and I have with me a special guest. She's the Chief Science Officer of Novo Nordisk and it's Lotte Bjerre Knudsen, and we're delighted to have her. She's a recent recipient of the Lasker Award, which I think is considered like the pre-Nobel Award here in the United States. And I was involved with her in terms of researching who was the principal person who brought the GLP-1 drugs to the forefront for obesity, and it turned out to be Lotte. So welcome, Lotte.

Lotte Bjerre Knudsen (00:48):

Thank you very much. And also very, very happy to be here. I'm not the Chief Science Officer for Novo Nordisk, I'm the Chief Scientific Advisor of working for the Chief Science Officer of Novo Nordisk, but maybe too many people, not so different, right?

From Laundry Detergents to GLP-1 Drugs

Eric Topol (01:06):

Yes. Thank you, I actually meant to say advisor, but yes, I'm glad you cleared that up. I know from speaking to some of your colleagues, I actually spoke to Robin yesterday that you are looked to very highly, the most highly regarded person in science there, so not surprisingly. What I want to do is first talk about the glucagon-like peptide-1 (GLP-1) that got its legs back in, I guess 1984. So we're going way back. And what's also interesting is that you go way back at Novo Nordisk to 35 years in 1989. And so, there had been this work with this extraordinary hormone and neurotransmitter with a very short half-life that you knew about. But when you first started in Novo Nordisk, you weren't working on this. As I understand it, you're working on laundry detergent enzymes. How did you make this pivot from the laundry enzymes to getting into the GLP-1 world?

Lotte Bjerre Knudsen (02:16):

Yeah, thank you for that question. I'm from the technical University of Denmark, so I'm trained in biotechnology, and we're a small country, so not that many companies to work for. And I always had my mind set on, I wanted to work for Novo as it was called back then, and it just happened to be in the industrial enzyme part that I got my foot in first. And then I had a very interesting boss at the time. Unfortunately, he's not alive anymore, but he was both a medical doctor as well as a chemist. So he was actually put in charge of actually, let's see if we can do something new in diabetes. And then since he hired me and I had not been there that long, I simply tagged along as the youngest scientist on the team, and then suddenly I became a diabetes researcher. Around the same time, I think you remember that all of pharma was interested in obesity in the early 90s, everyone wanted to do diabetes as well as obesity, but they were separate teams and they all wanted to do small molecules, but it just happens to be so that the best idea we could find at that time was actually GLP-1, because we actually had clinical data relatively early that GLP-1 was a really good candidate as a treatment for diabetes because of the glucose sensitivity of the actions.

(03:43):

So you'd have efficient lowering of glucose through a dual mechanism with increasing insulin, lowering glucagon, and then it was safe because there wasn't this hypoglycemia you get from insulin. But then I had other colleagues who were working on obesity, and I was just kind of listening, right, what's going on there? And then also a colleague that I had, we had, I don’t know if you remember the old Hagedorn Research Institute, but Novo actually had kind of like an academic research institute that was affiliated with us. And there was this group that were working on this glucagon tumor model that produced high levels of glucagon, GLP-1 and PYY. And these rats, they starved themselves to death. And I knew about that from 1994. So that actually inspired my thinking. So when Stephen Bloom's paper came out in January of 1996, and he was the first one to call GLP-1 a neurotransmitter, I think, but I was already way into actually screening these kind of molecules that later then became liraglutide.

No One Else Thought About This [Obesity]

(04:54):

And then I thought, why on earth should we not actually do both things at the same time? If we have an idea that can both work in diabetes in a much safer way than in insulin, and then also at the same time work in obesity. But the reality is that no one else thought about this, or if they thought about it, they didn't really think that it would a good idea. But I think I had the luxury of being in a biotech company, so everyone was working with peptides and proteins. So I don't think I got the same challenge that the other people in the other pharma’s got when they all wanted small molecules.

Eric Topol (05:36):

Well, also just to set the foundation here, which you alluded to, there had been so many attempts to come up with a drug that would work, not just of course in diabetes where there are many classes of drugs, but moreover, to treat the condition of obesity. Actually, I was involved with one of them, Rimonabant and did the large trial, which as you know, led to having to stop the drug, discontinue it because it was associated with suicidal ideation and actual some suicide. So there had been such a long history of checkered inability to come up with a drug. But what was striking is the challenge, and this is one of the first important questions about, when you had the extended half-life of the first GLP-1 drug, that instead of having to take multiple times a day, you could actually, with liraglutide get to a point where you were starting to get to an extended half-life. This is now going back to 1997 with approval in 2010, still 14 years ago. But when you came up with this drug, because this was certainly one of your great contributions, this drug was just a step along the way in this kind of iterative process, wouldn't you say? It wasn't the long half-life and the potency that eventually got us to where we are today. Is that true?

Lotte Bjerre Knudsen (07:15):

Yeah, it was a stepwise process. And what's super interesting about this class of medicines is that they're actually so different. If you talk about a class of medicine where small molecules, they can be different, but they're usually more alike than they're different. And when it comes to this class with these medium-sized peptides, people tried a whole bunch of different things. So they're actually really, really different. Some are simple peptides. So the idea that I came up with was to use this fatty acid isolation principle, and that's then a subclass in the class. And then the first, once weekly, for example, was an antibody-based molecule liraglutide. So they're much, much, much larger molecule compared to the small peptides. So they're very different. And neither the simple peptides nor the really big antibody derived molecules, they don't give a lot of weight loss. So we actually get more weight loss with these kinds of molecules, which is also why you can now see that it has actually kind of inspired a whole industry to kind of try and go and make similar kinds of molecules.

Eric Topol (08:27):

Well, inspired a whole industry is an understatement. It’s become the most extraordinary class of drugs, I think in medical history, having been a student of various, I mean obviously statins have been a major contribution, but this seems to have transcended that already. We're going to talk about more about where things are headed, but this fatty acid acetylation was a major step forward in extending the half-life of the drug, whereby today you can give semaglutide once a week. And this, I think, of course, there are many ways that you might've been able to extend the half-life, but you were starting with a hormone, a natural hormone neurotransmitter that had such an exquisitely short half-life of basically second or minutes rather than that you could give for a week. So I know there were many different ways you could have protected or extended the half-life one way or another, but this seemed to be a breakthrough of many along the chain of breakthroughs. But the question I have is when you were giving this to the diabetics, which was the precedent, that was really what these drugs were first intended, they didn't lose that much weight, and they never, still today when it's looked at for obese non-diabetics versus diabetics, there's a gap in weight loss. Why is that at the exact same dose, with the exact same peptide that the weight loss differs for people with type 2 diabetes as compared to those who have pure obesity?

The Mystery of Why People With Type 2 Diabetes Don’t Lose Weight Like Those With Obesity

Lotte Bjerre Knudsen (10:09):

Yeah, I can't give you a molecular answer to that, right. But I think the notion, I think it's the same for example with metformin, even though it gives less weight loss because that has also been tried in both people with diabetes and people without diabetes. So I think it's just for somehow people with diabetes are more resistant to weight loss. I think it's a really good question that I'm hoping maybe we could get through, for example, with proteomics and actually comparing people with diabetes and people without diabetes and looking at people who have the similar kind of weight loss. That could be really interesting. But I really don't have a good molecular answer for you, but it's just a really, really strong fact. But it also leads me to wanting to say it’s interesting, because if that had been our motivation to actually say, oh, there's weight loss in diabetes, let's pursue it in people with obesity, I don't think we would've done that because the weight loss in people with diabetes wasn't that impressive. So it was very important for our chain of thought and decision early on that we actually knew that GLP-1 had these separate effects and that they could work in the brain and have a separate effect on well-known pathways in the brain. And that was more our motivation to actually continue to invest in obesity.

Eric Topol (11:42):

Yeah, no, I think this is when we did the research on the committee for the American Association for Advancement of Science (AAAS) award, the Mani L. Bhaumik Award, that you were recognized for the breakthrough of the year, this year. We tried to scour all the work and we actually had to hit Danish translations and all sorts of other papers they reviewed. And we learned through that process working on this committee that you were the one to be the champion of pushing this towards obesity, and it would've easily been missed because as we've been discussing, the weight loss in people with diabetes was small, but you push for it. And this was an extraordinarily important push because what it has resulted in, of course, has been spectacular. And obviously as we're going to get into much more than just obesity and obesity related conditions. But before we get to those other conditions, and as you've been known in the medical community as “the mother of GLP-1”, you were dubbed that term. The GLP-1 receptor is expressed in many parts of the body. Maybe you could just tell us about the distribution because this, I think is tied into these central nervous system effects that are not just related to the gut hormone type of axis.

GLP-1 Receptors and the Brain

Lotte Bjerre Knudsen (13:17):

So I spent a lot of time on that together with my amazing colleague, Charles Pyke, who's an histology expert because it turned out to be so very important. In general, when you're trying to make new medicines, understanding the mechanism, sometimes people say, yeah, who cares? But actually, it should matter, I think because where it becomes really important can be an understanding what they do not do. We've had to do a lot of proving the negatives for GLP-1. We went through these issues with thyroid cancer, pancreatitis, pancreas cancer. In all of that work, it was actually really important that we could show where the GLP-1 receptor was not expressed. So in the pancreas, we know that it's primarily on the insulin producing cells, and then we also have them in the intestine where they're probably involved in regulating inflammation and really creating a much healthier gut.

(14:15):

And then we have a lot of receptors in the brain. They're typically expressed on neurons, but they're also on astrocytes, they’re also on smooth muscle cells. We have them on the heart and the sinus node. That's why there's a small increase in heart rate. We have them in the kidney, on again some smooth muscle cells that are renin positive. So there we can start thinking blood pressure and other things. So it turns out that you can go around the body and there are all of these specific GLP-1 receptor population, that you can see how they tie into the pharmacology. But obviously in physiology, they're not as important as they have turned out to be in pharmacology when we suddenly come with 24 hours a day exposure for a day or a week or for as long as the administration interval is. So, but specifically for obesity, I think it's in the vein, it's hard to, you should always be careful.

(15:18):

That's something I've learned to never say never. Of course, there could be a contribution from the peripheral nervous system as well to the effects in obesity. But I do think there are so many important and well described neuronal populations that have the GLP-1 receptor and which are accessible from the periphery. So just to mention, maybe one of the most, well-known is a POMC/CART neuron in the hypothalamus. They have the GLP-1 receptor, they're activated, but there also is an inhibitory tone on the AgRP and NPY neurons, and it fits very well with that. We know that people report that they feel more sated, they feel less hungry. But then there are also effects in the hindbrain and in some of the reward centers also have GLP-1 receptors. And we know that also now, we have really good actually clinical studies that show that there is a change in food choice and people can control their food intake better. So I think that fits very well with effects on the reward system. So it's a whole myriad, or maybe you could say that GLP-1 orchestrates a number of different neuronal populations to have these overall effects that reduce energy intake.

Eric Topol (16:42):

Yeah, it's pretty striking. It's almost like we're all walking around with GLP-1 deficiency, that if we had this present at higher levels around the clock, and of course eventually we'll see things that are well beyond obesity, how well this has an impact. Now, there was an extraordinary review in Cell Metabolism on the brain and GLP-1, and not just the brain, but the essential nervous system, the neurovascular, it's called the “GLP-1 programs and neurovascular landscape.”

(17:20):

And in this review, it got into the brain effects that were well beyond, I think what are generally appreciated. Not only the protection of the integrity of the blood-brain barrier, this whole neuroglial vascular unit, the myelin sheath protection, reducing inflammation within the brain, improving the glymphatic flow, which is of course critical for clearing waste and promoting cerebral vascular remodeling and more, so the brain effects here is what it seems to be. You mentioned the reward circuit, of course, but the brain effects here seem to be diverse, quite a bit of breath and extraordinary. And as we've seen in the clinic now with the work that's been done, we're seeing things about addiction, even gambling, alcohol, drugs, I mean neuropsychiatric impact, it's pretty profound. Maybe you could comment about that.

On to Alzheimer’s and Parkinson’s Diseases

Lotte Bjerre Knudsen (18:23):

Yeah. I haven't read that paper yet, but I just saw it earlier. And I have been following this for about actually more than 10 years because when I was kind of over the big work of actually getting the approval for diabetes and obesity. I thought I had a little bit of capacity to actually look at Alzheimer's and Parkinson's disease because I just thought there's such an insane unmet need and what if GLP-1 could actually make a difference? And the first big paper that talked about this was actually in Nature Medicine in 2003, and it was originally, I think I should credit Nigel Greig. Greig, he's from NIH or from NIA, I can't remember, right. But he was actually the first one, I think to say if GLP-1 has all of these important effects in the pancreas and to protect cells, and there are all these GLP-1 receptors in the brain, maybe it also protects neurons.

(19:25):

So that was the first hypothesis. And the paper on Nature Medicine in 2003 describes how the GLP-1 receptor in the hippocampus is involved in cognition. And then we did a couple of studies in different animal models, and I was, to be honest, really confused. But then there was a new paper in Nature Medicine in 2018 that started to focus in on neuroinflammation. And by that time, I knew much more about inflammation and knew GLP-1 actually lower CRP by about 50% in the different trials. So I was really tuned into the potential importance of that in cardiovascular and kidney disease. But I was like, oh, what if that's also something that is important in the brain? Then it made more sense to me to try and build some evidence for that. So that was how we actually started looking at a hypothesis for Alzheimer's and Parkinson’s.

(20:21):

And we now have a really large phase three study ongoing, but of course, it's a hypothesis, right? And no one has yet, I think, proven that GLP-1 has really important effects on these indications, but we are testing it in 4,000 people with Alzheimer's disease. So our hypothesis is around neuroinflammation, but defined in a way where you could say it's both peripheral inflammation and the effect it has on the vasculature, it's the effect on the blood-brain barrier. It's the astrocytes and the microglia, and there are probably also some T cells that have the GLP-1 receptor that could be important. And then couple that up also with some of the new information from neurons, because there are two papers to think in the last year that has highlighted neurons either in the hindbrain or a little bit further on. Both of them are probably hindbrain populations that actually seem to be really important in regulating both peripheral as well as central information.

(21:27):

So what if neurons are actually also an overlooked mechanism here, and both of these neuronal populations have the GLP-1 receptor and are accessible from the periphery, even though the child super paper in Nature doesn't mention that, but they do have the GLP-1 receptor. So there are all these different mechanisms that GLP-1 can have an impact on the broad definition maybe of neuroinflammation. And maybe the way one should start thinking about it is to say it's not an anti-inflammatory agent, but maybe it induces homeostasis in these systems. I think that could maybe be a good way to think about it, because I think saying that GLP-1 is anti-inflammatory, I think that that's wrong because that's more for agents that have a really strong effect on one particular inflammatory pathway.

Eric Topol (22:22):

That's a very important point you're making because I think we conceive of these drugs as anti-inflammatory agents from these more diverse actions that we've just been reviewing. But I like this restoring homeostasis. It's an interesting way to put it. This brings us, you mentioned about the Parkinson's, and when I reviewed the three randomized Parkinson's trials, they're all small, but it appears to be the first disease modifying drug ever in Parkinson's. Of course, these were done with different drugs that were older drugs. We haven't seen the ones that yet to be with semaglutide or other agents. And I wondered if you pushed, just like you did for obesity within Novo Nordisk, you pushed to go into obesity. Did you also force to push for Alzheimer's?

Lotte Bjerre Knudsen (23:19):

Yes. So that is also me who had to argue for that. I'm happy to do these things. I was born brave. I am happy to do these things.

Eric Topol (23:31):

That's wonderful. Without you, we would be way behind, and it took decades to get to this point. But look where we are now, especially with all the rigorous trials, the large clinical trials. You're into one right now of some 20,000 participants to see whether not just people with prior heart disease, but people without known heart disease to see whether or not this will have an effect. And there's so much data now, of course, already a completed trial with reduction of heart attacks and strokes. But now to extend this to people who are not such high risk, but these large trials, we keep learning more. Like for example, the reduction of inflammatory markers is occurring even before the weight loss that starts to manifest. So we learned a lot from the trials that are just even beyond some of the major primary outcomes. Would you agree about that?

Lotte Bjerre Knudsen (24:34):

So I'm not sure we can say that it comes before the weight loss because the energy intake reduction happens instantly. The glycemic response happens instantly. And all of these improvements will of course also have an effect to dampen inflammation. We do not have data that supports that it comes before because we haven't sampled that much in the beginning.

Eric Topol (25:04):

Okay.

Lotte Bjerre Knudsen (25:05):

I wouldn't be able to say that, and I don't think there are any, well, it's hard to keep up that the entire literature on GLP-1 these days, but I don't think anyone has actually shown that there is a separation because it's super hard to separate when things are occurring at the same time.

Eric Topol (25:24):

Yeah, I'm just citing the heart disease trial where in the New England Journal that point was made. But I think your point also that there was already a change in energy intake immediately is apropos for sure. Now, when we get into this new paper of yours, the proteomics, can you tell us about that because that's really exciting. We're in a high throughput proteomics era right now that we can analyze thousands of plasma proteins in any given individual. What are you learning about proteomics with the GLP-1 drug?

The GLP-1 Drug Impact on Proteomics

Lotte Bjerre Knudsen (26:07):

Yeah, yeah. So I'm also the super excited about omics, right? Because I have worked in a wonderful organization of people who can do these large scale clinical trials, and we used to not collect a lot of samples for future use, but we've done that for some years now. So now we have this amazing collection of samples we can learn from and actually both inform the patients and the physicians, but also inform future research. So we have been doing that in our semaglutide trials, and we've just published the proteomics data from the step one and step two trials. So the phase 3a trials that supported the approval of semaglutide for the treatment of obesity. So one of them in people with obesity and one in people with obesity and diabetes, and those data are now published in Nature Medicine. [3 January 2025]. And we were learning a lot of things because you can compare the proteome effects to what has been done in the decode cohort.

(27:11):

So they have all these disease signature. So that's one thing that you can for sure see, and you can see a lot of things there with hints towards addiction. And then also you can take more predefined signatures also to look into what actually might be driving the cardiovascular risk. So I think there are so many things that you can learn from this, and of course it can also inform when you look at what's actually mediating the effect and probably something around inflammation is important. We have already also shown a more standard mediation analysis that shows that actually the most explainable factor for the effect on MACE [major adverse cardiovascular events] in the select trial is inflammation. It doesn't explain everything, but it actually looks like it's more important than BMI and weight loss. So that's really interesting how much we can learn from there. We're making the data are available at the summary statistic level so people can go and play with them ourselves.

(28:23):

And I think as we have more different kinds of medicines available in obesity, it's also a way to kind of compare how these different medicines work. And as we get more and more better at maybe also characterizing people with obesity, because I think that's a great thing that's going to happen now is there's going to be more funding for obesity research. Because I think that's what the attention that we are seeing right now is also giving. Then we can better start to understand. We always, we've been saying that people probably have different kinds of obesity, but we don't really know. So now we can actually start to understand that much better and maybe also understand how these different classes of medicines will work if we have the proteome data from different trials.

Eric Topol (29:10):

No, I'm absolutely fascinated about the proteomics. I call it a quiet revolution because many people don't know about it. [My recent post on this topic here.]

(29:18):

The ability to assess thousands of proteins in each individual, and it's giving us new insights about cause and effect as you alluded to, the relationship with as you said, MACE (major adverse cardiovascular events) and the actions of this drug class. I mean, there's just so much we can learn here from the proteomics. Another thing that's fascinating about the GLP-1 is its effect on epigenetic clocks. And recently at one of the meetings it was presented, this is Steven Horvath that we had on Ground Truths not long ago. He talked about at this talk that for the first time to see that you could basically slow the epigenetic clock with a GLP-1. Is there any further information about that?

Lotte Bjerre Knudsen (30:16):

Yeah, no. We've never had enough of a sample size to actually be able to look at it, so unfortunately, no. But there is something else, right, because there is this group at the Stanford, Tony Wyss-Coray or something.

Eric Topol (30:33):

Yes, Tony Wyss-Coray.

Lotte Bjerre Knudsen (30:35):

Now he published a paper, is it two years ago? Where he did it using proteomics. He defined an anti-aging signature for various different organs.

Lotte Bjerre Knudsen (30:46):

We are in the process of trying to see if we could take those signatures and apply them on to our data.

Eric Topol (30:55):

Well, what's interesting is we're pretty close friends, and he, not only that paper you mentioned on organ clocks, which is a phenomenal contribution, but he has a paper coming out soon in Nature Medicine, the preprint is up, and what he showed was that the brain and the immune system was the main organ clocks that were associated with longevity. And so, it takes another step further and it's looking at 11,000 plasma proteins. So it's really interesting how this field is evolving because the omics, as you put it, whether it's proteomics, and now we're learning also about the epigenome and what brings us to the potential that this class of drugs would have an impact on health span in all people, not just those who are obese. Would you project that's going to be possible in the years ahead?

Lotte Bjerre Knudsen (32:02):

I don't know about health span, but because certainly there's been so many studies with metformin and there's been a lot of wonderful data showing an effect on the epigenetic clocks, but not really an effect on lifespan because that metformin is so widely used. If that was the case, it would be easy to dig those data out of different registries. But certainly a healthier aging is the most obvious one because when you have one class of medicine that actually has so many different effects. Right now we are looking at them at a one by one case, but we really should be looking at them so you are getting the benefits on the heart and the vasculature on the brain and the kidneys and the diabetes and the knees. You're getting all of that at the same time, and that certainly should lead to much, much healthier lives. And then of course, we just need to get people to eat healthier. Also, maybe we should talk a little bit about the food industry. I heard you did that in some of your podcast, right?

Eric Topol (33:17):

Yes. That is the big food, if you will. It's a big problem, a very big problem, and the ultra-processed foods. And so, lifestyle is not good and trying to compensate for that with a drug intervention strategy is like chasing your tail. So you're absolutely right about that. I mean, I guess what I'm getting into here is that whereas today we keep seeing the effects, whether it's the liver, the kidney, the heart, obesity, and people with diabetes. But for example, in the Alzheimer's trial, do you have to be obese to be enrolled in the Alzheimer's trial, or is it just people who are at risk for developingAlzheimer's?

Lotte Bjerre Knudsen (34:01):

Yeah, no, you do not have to be obese. It's a standard Alzheimer's trial.

GLP-1 Pills

Eric Topol (34:07):

So this will be one of the really important trials to get a readout in people who are not having an obesity background. Now, the future, of course, gets us to oral GLP-1 drugs, which obviously you have there at Novo Nordisk. And it seems to me once that happens, if it can simulate the effects we see with the injectables, that would be another big step forward. What do you think about that?

Lotte Bjerre Knudsen (34:39):

Yeah. Isn't it interesting, what we've learned is that people actually don't mind the injections, right? Also, because I think it's simple, once a week injection and the needles are so small, obviously there are people who really have needle phobia, but take those aside, it's relatively few. I would argue if you close your eyes and somebody else used this needle on you, you would not be able to feel where it was inserted, right? They're so small. So it becomes maybe a personal preference. Would you like to have once a day or maybe twice a day tablets, or are you fine with once a week injection? And I think there probably will be quite a few once they've tried it. And now so many have tried it and they actually, maybe it gives us a simple lifestyle. You don't have to do it every day, right? You can just have a weekly reminder.

Eric Topol (35:46):

Yeah, no, I think that's really interesting what you're bringing up. I never thought we would evolve to a point where injectables were becoming some common, and I even have some physician colleagues that are taking three different injectable drugs.

Lotte Bjerre Knudsen (36:00):

That's also just mentioned Richard DiMarchi, who I shared the Breakthrough Prize with, and also Svetlana Mojsov, who I was one of the other two recipients for the Lasker prize because they both been at Rockefeller, and they both have worked a lot with peptides, and they both say the same thing. They were told so many times, this is not medicines, these kinds of molecules just they're not medicines. Forget about it. It turns out people were wrong. And peptides can be medicines, and they can even be produced also in a sustainable manner with fermentation, which is not a bad way of producing medicines. And people actually don't mind. Maybe some people actually even like it because it's once a week and then it's done.

Confronting Barriers

Eric Topol (36:58):

Yeah, no, that's a very important point. And the quest for the oral, which have more issues with bioavailability versus the peptides that are having such pronounced impact is really interesting to ponder. Well, before we wrap up, it's very clear the impact you've had has been profound, not just obviously at Novo Nordisk, but for the world of advancing health and medicine. And you've mentioned some of the key other people who have made seminal contributions, but I think you stand out because when we went deep into who took this field forward into obesity and who might also wind up being credited for Alzheimer's, it was you. And as a woman in science, especially in an era that you've been at Novo now for three and a half decades, there weren't many women in science leaders. And for one to be, as you said, you're brave for the good old boys to listen to the woman in science. Tell us about that challenge. Was this ever an issue in your career? Because obviously we want to have this whole landscape change. It is in the midst of change, but it's certainly still a ways to go. So maybe you can give us insight about that.

Lotte Bjerre Knudsen (38:27):

Yeah. Well, it for sure was a thing. It was a very male dominated world, and in a way, it might have prevented other people from doing it. But then, as I said, I was born brave for some reason. I'm not really sure why. It actually motivated me to kind of like, yeah, I'm going to show them. I'm going to show them. So it never really got to me that people, not everyone was nice to say. There was the first 10 years of my career, I think they were quite lonely, but then I was really inspired. I was so happy to be allowed to work on this. I thought it was super fun. And I did find people who wanted to play with me. And I also have to say that the CSO back then, Mads Krogsgaard Thomsen, he always supported me. So maybe I didn't get everything I wanted, but I always got what I needed in order to progress.

(39:29):

So on the women's side, and I think that yes, and there's still a change to be made, and I'm actually a little bit on behalf of my generation, maybe not too proud of the change we made because we didn't do a lot of change. It was all the women coming from the arts and the culture. They were the ones who actually make the big change here like 5 or 10 years ago. So I've also started to be more open about sharing my journey and advocating for women in science. So that's why I show up in pink to some of these award sessions just to be a little bit different and to maybe also just show that you don't have to be a certain type in order to fit into a certain job. But there is still a change to be made where people should be better at listening to what a person say and what ideas they say.

(40:28):

And they should be mindful about not always labeling women as passionate. When people call me passionate, I say like, no, thank you. I'm actually not too happy about the mother of either, because men always are being told. They're being told that they're brave and ambitious and courageous and strategic, whereas we we’re, oh, you're so passionate. No, thank you. I'm also brave and strategic and ambitious and all of that. So we simply put different vocabulary on. I don't think people don't do it on purpose. I think we need to be better at actually giving people at work the same kind of vocabulary for their contributions. And I think that would mean that we get listened to in the same way. And that would be important. And then I also have to say that science, whether it comes from men or women, doesn't really matter.

(41:32):

Successful science is always the work of many. And I hope that some of you will actually listen to my last speech because that's what I speak about, how it's always the work of the many. And also, how if you want to do something novel, then you actually have to do it at a time when no one else is doing it, and you should believe in your ideas. So believe in it, listen to the critique, but believe in it, and then come back with new arguments or give up if you can't come up with any new arguments, right?

Eric Topol (42:05):

Well, we'll definitely put a link to the Lasker Awards speech that you gave. And I just want to say that the parallels here, for example, with Kati Karikó , my friend who had the Nobel Award for mRNA, she spent three decades trying to get people to listen to her and never got a grant from the NIH or other places [our conversation here]. And it was a really tough battle. And as you already touched on Svetlana Mojsov, who did some of the seminal work at Rockefeller to isolate the portion of GLP-1, that really was the key part peptide, and it was overlooked for years. And so, it's a tough fight, but you're paving the way here. And I think the contributions you've made are just so extraordinary. And I hope that over the years we will continue to see this momentum because people like what you've done, deserve this extraordinary recognition. I'm glad to see. And the Lasker Award is really capping off some of that great recognition that is so well deserved. We’ve covered a lot of ground today, and I want to make sure if I missed anything that you wanted to get into before we wrap up.

Lotte Bjerre Knudsen (43:30):

I think we've been around all the exciting biology of GLP-1, both in diabetes, obesity, cardiovascular, kidney, potential in Alzheimer's and addiction. We'll see, we need the clinical data and we've put out a message to inspire people to do new science. There's still a lot of unmet need out there. There's a lot of diseases that don't have good treatments. Even in the diseases we've talked about there’s a lot of money for diabetes. There are no disease modifying therapies for diabetes. It's not really changing the course of the disease. So there's a lot of things that needs great scientists.

Eric Topol (44:17):

And I guess just in finishing the discovery of this class of drugs and what it's led to, tells us something about that, there's so much more to learn that is, this has taken on perhaps the greatest obstacle in medicine, which was could you safely treat obesity and have a marked effect. Which decades, many decades were devoted to that and gotten nowhere. It's like a breakthrough in another way is that here you have an ability to triumph over such a frustrating target, just like we've seen with Alzheimer's, of course, which may actually intersect with Alzheimer's, with a graveyard of failed drugs. And the ones that it were approved so far in certain countries, like the US are so questionable as to the safety and efficacy. But it gives us an inspiration about what is natural that can be built on the basic science that can lead to with people like you who push within the right direction, give the right nudges and get the support you need, who knows what else is out there that we're going to be discovering in the years ahead. It's a broad type of lesson for us.

Lotte Bjerre Knudsen (45:38):

Yeah, there is another hormone that's also in phase three clinical development, right? The amylin hormone. We've had pramlintide on the market for years, but we have this long-acting version that is in phase three clinical development. That could be the same kind of story because there's also additional biology on that one.

Eric Topol (45:58):

Yeah, this is what grabs me Lotte, because these gut hormone, we've known about them, and there's several more out there, of course. And look what they're having. They're not just gut hormones, like you said, they're neurotransmitters and they're body-wide receptors waiting to be activated, so it's wild. It's just wild. And I'm so glad to have had this conversation with you. Now, congratulations on all that you've done, and I know the Nature Medicine paper that just came out is going to be just one of many more to come in your career. So what a joy to have the chance to visit with you, and we'll be following the work that you and your colleagues are doing with great interest.

Lotte Bjerre Knudsen (46:45):

And thank you very much, and thank you for your wonderful podcast. They’re really great to listen to on the go. Very easy listening.

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Piezo touch and pressure-sensing ion channels are showing up everywhere as the explanation for physiologic phenomena, both at the macro and micro levels. Ardem Patapoutian, my friend and colleague at Scripps Research, discovered these receptors back in 2010 and was awarded the Nobel Prize in 2021 for his work. As you’ll see/hear from our conversation, the field has exploded. And you’ll get to know Ardem, who is such a fun, charismatic, and down-to-earth person. He also recently got a unique tattoo (videos below) and I wonder (unlikely) if any other Nobel laureates have one related to their discovery?!

Below is a video clip from our conversation. Full videos of all Ground Truths podcasts can be seen on YouTube here. The current one is here. If you like the YouTube format, please subscribe! The audios are also available on Apple and Spotify.

Transcript with links to audio

Eric Topol (00:07):

Well, hello. It's Eric Topol with Ground Truths, and I've really got a special guest today. The first time for the podcast, I've been able to interview a colleague and faculty at Scripps Research, Ardem Patapoutian, who just by the way happens to be the 2021 Nobel Laureate in Physiology or Medicine. So welcome, Ardem. It's so wonderful to have you.

Ardem Patapoutian (00:30):

Thanks so much, Eric. Looking forward to chatting with you.

Eric Topol (00:34):

Well, this has been interesting because although I've known you for several years, I didn't research you. I mean, I had to learn about more than I even do. And of course, one of the great sources of that is on the Nobel Prize website where you tell your whole story. It is quite a story and not to review all of it, but I wanted to go back just before you made the call to move to Los Angeles from Beirut, Lebanon and with the scare that you went through at that time, it seemed like that was just extraordinary that you had to live through that.

Ardem Patapoutian (01:11):

Yeah, so I am of Armenian origin, but I was born in Lebanon and born in 1967, so I was eight years old when the civil war started. So it's a kind of bizarre childhood in the sense that with all the bombs and fighting in Lebanon. So it was tough childhood to have, but it was never personal. It was bombs and such. And so, the event you're talking about is, I happened to be kidnapped while crossing East to West Beirut. They only held me for four or five hours at first asking me questions to see who I am, but I think they pretty soon figured out that I was not a dangerous guy and they ended up letting me go. But before that, that incident really had a huge impact on me so that by the time I got home, I literally said, I'm out of here. I'm going to find a way to leave the country. And so, that's what, very quickly within a few months I packed and came to United States.

Eric Topol (02:19):

And how did you pick LA to be your destination?

Ardem Patapoutian (02:22):

Being from the Armenian community, there's a lot of Armenians in Los Angeles. My cousins already had moved there. They also grew up in Lebanon. And my brother, who's a few years older than me, got admitted to USC graduate school in engineering. So he was going to be there. So it made a lot of sense.

Eric Topol (02:44):

Oh yeah.

Ardem Patapoutian (02:45):

Unlike him, I came with no school or job prospects because it happened so fast that I kind of just left. One year I was at American University of Beirut for one year, but then just left and came here. So worked for a year in various jobs and then started going back to school to UCLA.

Eric Topol (03:07):

Yeah, I saw how there was about a year where you were delivering pizzas and before you got into UCLA, and that must have been an interesting off year, if you will. Well, the story of course, just to fast forward, you did your baccalaureate at UCLA, your PhD at Caltech, postdoc at UCSF, and then you came to Scripps Research 24 years ago along with Pete Schultz, and it's been quite an amazing run that you've had. Now, before we get into PIEZO receptors, the background, maybe you could help me understand, the precursor work seems to be all related to the transient receptor potential (TRP) series, also ion channels. They were of course related to whether it was heat and temperature or somatosensory. How do these channels compare to the ones that you discovered years later?

Background on these Ion Channels

Ardem Patapoutian (04:09):

Yeah, so the somatosensory neurons that innervate your fingertips and everywhere else in your body, their main job is to sense temperature and pressure. And this is very different than any other neuron or any other cell. So when you touch a hot stove that’s burning hot, you need to know about that immediately within milliseconds or something cold. So the opposite side of it is pressure sensing, and it also comes in light touch, which is pleasant or a hammer hitting your finger, which is unpleasant. But all of these have the same characteristic anyway, that is your body has learned at the molecular level to translate a physical stimulus such as temperature and pressure into an electrical signal that neurons use to communicate with each other. But this idea of how you translate physical stimuli into chemical or electrical signal has been a long open question because as you know, most of our cells communicate by chemicals, whether that's hormones or small molecules, we know how that works, receptor bind to ligand, confirmational change and you get a kinase activation and that's enough. But here, how do you sense pressure? How do you sense temperature? It was just, there wasn't much known about that. And that's why our earlier work on TRP channels, which were temperature sensors came before the pressure. And so, they're very related in that sense.

Eric Topol (05:52):

The structure of these, if you were to look at them, do they look pretty similar? What the TRP as you say, and what you did back in the 2010 Science paper, which we'll link to, of course the classic paper where you describe PIEZO1 and PIEZO2, but if you were to look at this structures, would they look pretty similar?

Ardem Patapoutian (06:14):

No, that's a good question. And they absolutely don't. That's why finding these receptors were so hard. So if you go back to other sensory receptors, vision rhodopsin G-protein coupled receptor (GPCRs), larger G-protein coupled receptor look the same. So for example, when it was identified by chemically, that smell also works through G-protein coupled receptor. Richard Axel and Linda Buck, who also won the Nobel Prize, found those receptors by homology to visual GPCRs. The ion channels other than the fact that they crossed the membrane a few times or more, they have nothing else in common. If you looked at their structure, you can't even immediately tell they’re ion channels. So you couldn't find these by structural homology or sequence homology. So you had to do something else. And usually that means functional screens and et cetera.

Eric Topol (07:09):

Well, yeah, and I'm in touch with the screening. We'll get to that and how you dig these up and find them. But the somatosensory ones are really interesting because I don't think a lot of people realize that when you have wasabi or you have Listerine mouthwash and feel the burn and that these are all mediated through these channels, right?

Ardem Patapoutian (07:35):

Yeah. So there's this whole field of chemesthesis, which means senses in your mouth, for example, that are not explained by taste transduction and olfactory. And these are actually by the same somatosensory neurons that help you sense temperature and pressure. And some of these receptors are the same. Their evolution has taken over and used them for many different things. The prime example of this is the capsaicin receptor that David Julius my co-laureate identified, which is also heat receptors. So all languages describe chili peppers as hot, and that's not a coincidence. It actually activates heat activated channel, and that's why we think of it as hot. And so, the same goes to another one of these TRP channels that you mentioned, which is TRPA1, and this one is also activated, but a lot of spicy foods other than the chili pepper active ingredient includes what's in garlic and onions and everything that has this burning sensation and chemicals of this and wasabi and chemicals of this are used in over the counter products like Listerine that cause that burning sensation.

Eric Topol (08:54):

So when you're chopping onions and it makes you cry, is that all part of it as well?

Ardem Patapoutian (08:59):

That’s all TRPA1, yeah.

The Discovery, A Test of Perseverance

Eric Topol (09:01):

It's wild. Now, this was the groundwork. There were these heat temperature and somatic sensory, and then you were starting to wonder what about touch, what about out pressure and proprioception. And so, you went on a hunt, and it's actually kind of an incredible story about how you were able to find out of these cells that you had, screening hundreds or I guess you got to 72 different small interfering RNA blocking that you finally found the one. Is that right?

Ardem Patapoutian (09:37):

That's right. So in retrospect, looking back at it, I think there's such an interesting scientific message there. And so, many of us were looking for this touch pressure sensors and we were all looking in the DRG sensory neurons that are complicated heterogeneous, they don't divide. It's not easy to do a screen on them. And ultimately after a lot of failures, what worked for us is to take a step back and ask a much more simpler question. And that was, can we find one of these cell lines that you could easily homogeneously grow in a culture dish, if they respond to mechanical force, can we find our channel there? And then go back and look if it's relevant in vivo for what process. So I think the message is ask the simplest question to answer the question you're after. And finding what that is, is actually the challenge lots of times.

Ardem Patapoutian (10:36):

But yeah, that's what Bertrand Coste in my lab did is found a simple cell line that neuroscientists had been using for a hundred years and somehow found that they over overexpressed this channel because you can record from them, you can push them and record the currents from them. And then it became a simpler question of finding it. It still took a whole year. He made a list and one by one knocking them out and looking at it. And finally, as you say, number 72 was the hit. When he knocked that out, the current was gone. And that's where we started believing that we have what we were looking for.

Eric Topol (11:12):

Were you all ever about ready to give up at that point?

Ardem Patapoutian (11:16):

Oh yeah. I mean that's another lesson. These are postdocs doing the work, right? And they're here three, four years and this was coming close to end of two years, and he didn't have anything yet. So we started talking about having a backup project and he started that and we said, okay, we were ordering this oligos 30 at a time because they're expensive. And so, the first 30 nothing, the second 30 nothing. And how many more are we going to do before we potentially give up? And we said, well, let's do at least a third and then decide, thank goodness it was in that last set.

Eric Topol (11:54):

Wow, that is so wild. Now what's happened since this discovery, which I guess when you published it in 2010, so it means 14 years ago, but we're on this exponential growth of learning that these piezo receptors are everywhere. They're doing everything. In fact, I recently put on Bluesky, PIEZO ion channels are to human physiology as GLP-1 drugs are to treating many diseases because it's just blowing up. And you've published on some of these of course, on itch and bladder function and vascular function. We'll get to maybe malaria, I mean, but even the cover of Science recently was about wet dog shakes and how animals shake because of water. These receptors are so fundamental to our function. So maybe you could comment, 15 years ago when you were doing the work and you're making this discovery, did you ever envision it was going to blow up like this?

Ardem Patapoutian (12:57):

Not to this level, but I should have. I think that this idea, again, that most of cell communication is through chemicals is of course a lot of it is true.

Ardem Patapoutian (13:12):

But it would be ridiculous for evolution to ignore all the physical forces, the pressures that cells experience. And once they do, you would think you would put an instructive way of sensing this pressure signal and using it beneficially to the system or the cell. And so, when we used to talk about pressure sensing at the beginning, there were a couple of touch, pain, maybe proprioception, hearing are like the poster children of pressure sensing. But I think what these molecules, as you say is enabling us is finding out the much more wider role that pressure sensing is playing in physiology and in disease that no one had thought seriously about. And this is, I compare sometimes the finding the PIEZO molecules. You're going in a dark room, and you need to find a door to get into there. And PIEZO is kind of that finding the door once you get in, now you use that molecule now to find physiology instead of the opposite way around. So by pursuing PIEZO expression and function, we're finding all these new roles that they play in physiology and in disease that we didn't think about. And because they're so specialized to sense tension, membrane tension, they don't do anything else. So if you see them expressed somewhere or if you see a function for them, you can bet that they are playing a role in sensing pressure. A lot of biology has kind of come from this hypothesis.

Eric Topol (15:00):

Well, I mean it is so striking to see the pervasiveness, and I do want to go back just for a second because when you name them PIEZO, you named it after the Greek word. How did you come to that name?

Ardem Patapoutian (15:13):

So Bertrand and I were actually sitting on Google Translate and we were typing pressure and trying to see what it's like in Greek or in Latin or different languages. His native French and my Armenian and píesi in Greek is pressure. And of course, what's really cool is that the word that more people know about this is piezoelectric device.

Eric Topol (15:41):

Oh, right.

Ardem Patapoutian (15:41):

Actually, translates physical force into electricity and vice versa. And in a way, this is a little molecular machine that does the same thing, and he uses this piezoelectric device to actually push on the cell. That's his assay. So it all came together as a very appropriate name for this gene and protein.

Call from the Nobel Committee

Eric Topol (16:04):

Oh really, it’s perfect. And you get to name it, even that's fun too, right? Now we're going to go to getting the call at 2:00 AM, but it didn't come to you because your phone from the Nobel Committee was on ‘do not disturb’ and your 94-year-old father, Sarkis. How did the Nobel Committee know to get ahold of him? How did they reach him in the middle of the night?

Ardem Patapoutian (16:37):

Yeah, so I mean, since receiving it, I've had conversations with various committee members, and they are very resourceful folks, and they have assistants who throughout the year collect information on all potential people who might win. They're also doing last minute searches. So they looked for other Patapoutian’s in California. So they just called my dad who initially yelled at them for disturbing him at 2:00 AM.

Eric Topol (17:17):

And he could get through to you because he was not on your list of ‘do not disturb’ or something like that.

Ardem Patapoutian (17:22):

I didn't even know this. And I don’t know if the policy has changed, but in some phones the ‘do not disturb’ if it's called by someone who's in your contacts or favorites.

Ardem Patapoutian (17:34):

After I think they called twice and they get through, and that's how.

Getting a Tattoo!

Eric Topol (17:39):

That's amazing. Wow. Well, that's quite a way to find out that you're getting recognized like this. Now recently you got a tattoo, which I thought was really remarkable, but we're going to put that of course in the post. Tell us about your decision to get the PIEZO channel on your arm.

Ardem Patapoutian (18:02):

So as you can tell, I'm obsessed about PIEZO and it's been good to me. And I had the idea a while ago, and my very wise wife, Nancy Hong, said that you might be going through midlife crisis. Why don't you wait a year? If you still believe in it, you should do it. And that's what I did. I waited a year, and I was like, I still want to do it. And I guess I could show it. Here it is.

Eric Topol (18:32):

Oh yeah, there it is. Oh wow.

Ardem Patapoutian (18:33):

What’s cool is that I can pretty much flex to show the activation mechanism because the channel is like bent like this in the plasma membrane. When it's stretched, it opens and it actually flattens like this. So I feel like other than being a tattoo, this is both performance art and instructional device. When I'm giving talks without PowerPoint slides, I could give a demonstration how this ion channel works.[Below is from a presentation that Ardem recently gave, the Harvey Lecture, at Rockefeller University.]

Eric Topol (19:04):

It's wild. Now how did you find a tattoo artist that could, I mean, it's pretty intricate. I mean, that's not your typical tattoo.

Ardem Patapoutian (19:14):

Yeah, I put it up on social media that I was thinking of doing this, and many scientists are into tattoos, so I actually got so many recommendations. And one of them was a local here in San Diego, and she is very popular. I waited six months to get this, I was on a waiting list. The appointment was six months off when we made it. So she's very popular and she's very good.

Eric Topol (19:45):

Was it painful to get that done?

Ardem Patapoutian (19:47):

Well, that's actually really cool, right? Because PIEZO2 is involved in pain sensation, and I felt it while it was being tattooed on my arm. The whole day, I was there like six and a half hours.

New Prospect for Pain Medication

Eric Topol (20:00):

Oh my gosh. Wow. Now that gets me to pain because, I'd like you to talk a bit about the people that don't have mutations or loss of function PIEZO receptors and also what your thoughts are in the future as to maybe we could develop a lot better pain medications.

Ardem Patapoutian (20:22):

Yeah, we're working on it. So you're right. One of the great parts of the science story, and this is mainly the work of Alex Chesler and Carsten Bönnemann at the NIH, where they identified people who came to the clinic for undiagnosed conditions, and they were uncoordinated and had difficulty walking. And when they did whole-exome sequencing, they found that they had mutations in PIEZO2, there were loss of function, as you say. So complete loss on both chromosomes. And when they started testing them, they realized that just like we had described them in animal models, humans without PIEZO2 as well, didn't sense touch, don't have proprioception. This sense of where your limbs are, that's so important for balance and most other daily functions that we take it for granted. So they were completely lacking all of those sensations. They also do not feel their bladder filling.

Ardem Patapoutian (21:26):

And so, they have learned to go on a schedule to make sure they don't have accidents. And many of these projects that we've done in the lab collaboration with Alex Chesler, et cetera, have come from the observations of what else these individuals experience. And so, it's been a great kind of collaboration communication between mechanistic animal model studies and the clinic. And so, one of the things that these individuals don't sense in addition to touch, is something called tactile allodynia, which is simply when touch becomes painful. You and I experienced this after small injury or sunburn where just touching your shoulder becomes painful, but for peripheral neuropathy and other neuropathic pain conditions, this is one of the major complaints that individuals have. And we know from the NIH studies that these individuals don't have this tactile allodynia. So touch becomes painful and doesn't apply to them, which tells us that if we block PIEZO2, we can actually get interesting relief from various aspects relative to neuropathic pain on other pain related neuropathies. But given everything we talked about, Eric, about how this is important for touch and proprioception, you don't want to make a pill that blocks PIEZO2 and you take it because this will have some serious on target side effects. But we are developing new compounds that block PIEZO2 and hope that it might be useful, at least as a topical medication pain and other indications. And we're actively working on this, as I said.

Eric Topol (23:15):

Yeah, I mean the topical one sounds like a winner because of peripheral neuropathy, but also I wonder if you could somehow target it to sick cells rather than if giving it in a systemic targeted way. I mean it has tremendous potential because we are on a serious hunt for much better relief of pain than exists today.

Ardem Patapoutian (23:41):

Absolutely.

Eric Topol (23:42):

Yeah. So that's exciting. I mean, that's another potential outgrowth of all this. Just going back, I mean the one that prompted me in November to write that about the human physiology in PIEZO, it was about intestinal stem cell fate decision and maintenance. I mean, it's just everywhere. But the work you've done certainly now has spurred on so many other groups to go after these different and many unanticipated functions. Were there any ones, of course, you've been pretty systematically addressing these that actually surprised you? You said, oh, are you kidding me when you read this? I never would've guessed this, or pretty much they followed suit as things were moving along.

Ardem Patapoutian (24:33):

So one of them is this role in macrophages that I found fascinating that we found a few years ago. So again, this came from human studies where PIEZO1 gain-of-function mutations. So in relation to loss of function, their gain-of-function where there's more activity given a certain amount of pressure. They have dehydrated red blood cells, which I'm not going to talk about right now. But they also have shown that in these patients, individuals, it's not really that pathological. They also have age-onset iron overload. What does that have to do with pressure sensing? And we brought that information into animal models, and we found that macrophages, their rate of phagocytosis depends on PIEZO, so that if you have too little PIEZO, they don't phagocytosis as much. If you have too much PIEZO, the phagocytosis too much. And this increased rate of phagocytosis in the long term because it's constantly eating red blood cells and the iron is circulating more causes long-term effects in iron overload. And again, as you kind of set that up, who would've thought that mechanical sensation is important for this basic hematology type?

Eric Topol (25:52):

Yeah, I mean, because we've been talking about the macro things, and here it is at the cellular level. I mean, it's just wild.

Ardem Patapoutian (25:59):

If you go back and look at a video of a macrophage eating up red blood cells, then you go, oh, I see how this has to do with pressure sensing because it is like extending little arms, feeling things letting go, going somewhere else. So again, I want to bring it back by this simple cell biological function of a cell type, like macrophage, exploring its environment is not just chemical, but very mechanical as well. And so, in retrospect, it is maybe not that surprising, that pressure sensing is important for its physiology.

Career Changing?

Eric Topol (26:33):

Yeah, that's extraordinary. Well, that gets me to how your life has changed since 2021, because obviously this a big effect, big impact sort of thing. And I know that you're the first Armenian, first person from Lebanon to get this recognition. You recognized by the Lebanese Order of Merit. There's even a stamp of you, your picture characterized in 2022.

Eric Topol (27:04):

So if you were to sum up how it's changed because I see no change in you. You're the same person that has a great sense of humor. Often the tries to humor relaxed, calming. You haven't changed any to me, but how has it affected you?

Ardem Patapoutian (27:26):

Thank you, Eric. That's very kind of you. I try very hard for it not to change me. I do get a little bit more attention, a ton more invites, which unfortunately I have to say no to a lot of them because, and I'm sure you're very familiar with that concept and a lot of things are offered to you that I feel like it's so tempting to say yes because they're wonderful opportunities and an honor to be asked. But the end of the day, I'm trying to be very disciplined and not taking things on that I can do as an opportunity. But things that I really want to do. I think that's so hard to do sometimes is to separate those two. Why am I doing this? Is this really important for the goals that I have? So in one way, the answer for that is that I just want to stay in the lab and do my research with my students and postdoc, which is what I enjoy the most. But on the other hand, as you said, being the first Armenian who's received this, literally after the Nobel, I got this whole elementary school, all Armenian kids write to me multiple letters.

Ardem Patapoutian (28:39):

And they said, you look like me. I didn't think I could do this, but maybe I can. So in a sense, to ignore that and say, no, I just want to do my science, I don't want to be involved in any of that is also wrong. So I'm trying to balance being engaged in science outreach and helping to make science understood by the general public, realize that we're just regular people and at the same time how awesome science is. I love science and I like to project that, but leave plenty of time for me to just be a scientist and be in my lab and interact with my colleagues at Scripps, including you.

Immigrant Scientists

Eric Topol (29:21):

Well, we're so lucky to have that chance. And I do want to mention, because you're prototyping in this regard about great immigrant scientists and other domains of course, but every year the Carnegie Foundation names these great immigrants and one year you were of course recognized. And in recent years, there have been more difficulties in people wanting to come to the US to get into science, and they wind up going to other places. It seems like that's a big loss for us. I mean, what if we weren't able to have had you come and so many hundreds, thousands of others that have contributed to this life science community? Maybe you could comment about that.

Ardem Patapoutian (30:10):

Yeah, I think it is tragic, as you say. I think in some circles, immigrants have this negative image or idea of what they bring, but at every level, immigrants have contributed so much to this country. It's a country of immigrants, of course, to start with. And I think it is important to put up a positive image of immigration and science is the ultimate example of that, right? I mean, I think when you go into any laboratory, you probably find if there's a lab of 16 people, you probably find people from 10 different countries. And we all work together. And the idea of also immigrant and especially about science is that I'm a big believer of changing field, changing things because just like that, immigrants have changed their whole life. So they come to a new culture, they bring with them their own way of thinking and their way of seeing things. And then you come into a new environment, and you see it a little bit differently. So that kind of change, whether it's because of physical immigration or immigrating from one field to another in science is really beneficial for science and society. And I think positive examples of this are an important part of highlighting this.

Eric Topol (31:40):

I couldn't agree with you more really.

Bluesky vs Twitter/X

Eric Topol (31:41):

Now, speaking of migration, there's been recently a big migration out of X, formerly Twitter to Bluesky, which I like the metaphor you liken to the Serengeti. Can you tell us about, now I know you're posting on Bluesky and of course so many others that you and I are mutual contacts, and our different networks are. What do you think about this migration outside of what was the platform where a lot of this, we shared things on X or before Musk took over known as Twitter? Thoughts about Bluesky?

Ardem Patapoutian (32:27):

Yeah, I think I use social media for a few reasons. The number one reason should be is to see new science by colleagues. My main point is that, but also, again, having fun in science is a big part of my draw to this. And as you can see from my posts, it's a bit lighthearted, and that's really me.

Eric Topol (32:52):

Right. Yeah.

Ardem Patapoutian (32:52):

I think on Twitter, things start getting a little bit dark and too many negative comments, and it was just not productive. And I just felt like after the elections, I felt like it was time to migrate. And I find Bluesky a great scientific community, and it's remarkable how quickly people have migrated from Twitter to Bluesky. But the counter argument for this is that you should stay in a place where majority of people are, because being in a bubble surrounding yourself by people like you doesn't help society. And so, I get that perspective as well. It just depends on what you're using the platform for and it's a difficult issue. But yeah, I've taken a break probably long-term break from Twitter. I'm on Bluesky now.

Eric Topol (33:48):

Yeah, no, the point you're bringing up about the echo chamber and is there going to be one for people that are leaning one way and they're thinking, and another with a whole different, often politically charged and even extreme views? It's really unfortunate if it does wind up that way. But right now, it seems like that migration is ongoing and it's substantial. And I guess we'll see how it settles out. I share your concern, and so far, I've been trying to keep a foot in both areas because I think if we all were to leave, then we're just kind of caving into a, it's tricky though. It really is because the noxious toxic type of comments, even when you try to avoid comments, you say, only followers can make a comment, they’ll of course, quote your thing and then try to ding you and whatever. It's just crazy stuff, really.

Ardem Patapoutian (34:53):

I mean, what I think is that, that's why I said depends on why. I mean, your presence on social media is such an important part of science education. And I could almost say you can't afford to do what I do, which is I'm just putting my goofy posts and having fun. So we have different purposes in a way, and yeah, that affects what you use and how you use it.

Eric Topol (35:17):

Yeah, no, it's tricky it really is. We covered a lot of ground. Is there anything I missed that you want to get out there? Any part of this, your story and the PIEZO story, science and everything else that I didn't bring up?

The Essentiality of Basic Science

Ardem Patapoutian (35:42):

I just think that the basic science community is really suffering from decreasing amounts of funding and appreciation of doing basic science. And one of my goals, in addition to this immigrant scientist thing, is to remind people that all medicines start with basic science work. And funding this has mainly been through NIH and it's getting harder and harder for basic scientists to secure funding and I'm really worried about this. And we need to find ways to be okay for people to do basic science. And I'll give you one example. Whenever we make a publication and there's a journalist talking to us or some kind of press coverage, they ask, how is this directly affecting patients? And my work actually is very much related to patients, and I answer that question, but I also say, but it's also important to do science for the science sake because you don't know where the applications are going to come from. And we need to, as a society, encourage and fund and support basic science as the seeds of all these translational work. And I think doing that just kind of highlights that this is important too. We should support it, not just things that right now seem very related to translational that directly helps patients.

Eric Topol (37:16):

Well, I'm so glad you emphasized that because I mean, the PIEZO story is the exemplar. Look what's come of it, what might still come of it. In many respects here you are maybe 15 years into the story and there's still many parts of this that are untold, but if it wasn't for the basic science, we wouldn't have these remarkable and diverse insights. And recently you cited, and I think so many people read about the ‘crown jewel’ NIH, front page New York Times, and how it's under threat because the new NIH director doesn't have a regard for basic science. He's actually, he's confirmed, which is likely, he's an economist, physician economist, never practiced medicine, but he doesn't really have a lot of regard for basic science. But as you point out, almost every drug that we have today came out of NIH basic work. And I mean, not just that, but all the disease insights and treatments and so much.

Eric Topol (38:25):

So this is really unfortunate if we have not just an NIH and other supporting foundations that don't see the priority, the fundamental aspect of basic science to then lead to, as we call translational, and then ultimately the way to promote human health, which is I think what we're all very much focused on ultimately. But you can't do it without getting to first base, and that's what you have done. You served it up and it's a great example. Well, Ardem, it's always a pleasure. This is a first time talking through a podcast. I hope we’ll have many, many visits informally that will complement the ones we've already had, and we will follow the PIEZO work. Obviously, you have had just an exceptional impact, but you're still young and who knows what's next, right? I mean, look what happened to Barry Sharpless. He won here. He won two Nobel prizes, so you never know where things are headed.

Ardem Patapoutian (39:36):

Thank you, Eric, and I really appreciate what you do for the biomedical community. I think it's wonderful through your social media and this podcast, we all appreciate it.

***********************************************************************************

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American healthcare is well known for its extreme cost and worst outcomes among industrialized (such as the 38 OECD member) countries, and beyond that to be remarkably opaque. The high cost of prescription drugs contributes, and little has been done to change that except for the government passing the Affordable Insulin Now Act at the end of 2022, enacted in 2023. But in January 2022 Mark Cuban launched Cost Plus Drugs that has transformed how many Americans can get their prescriptions filled at a fraction of the prevailing prices, bypassing pharmacy benefit managers (PBMs) that control 80% of US prescriptions. That was just the beginning of a path of creative destruction (disruptive innovation, after Schumpeter) of many key components American healthcare that Cuban is leading, with Cost Plus Marketplace, Cost Plus Wellness and much more to come. He certainly qualifies as a master disrupter: “someone who is a leader in innovation and is not afraid to challenge the status quo.”

Below is a video clip from our conversation dealing with insurance companies. Full videos of all Ground Truths podcasts can be seen on YouTube here. The current one is here. If you like the YouTube format, please subscribe! The audios are also available on Apple and Spotify.

Transcript with External links to Audio

(00:07):

Hello, it's Eric Topol with Ground Truths, and I have our special phenomenal guest today, Mark Cuban, who I think you know him from his tech world contributions and Dallas Mavericks, and the last few years he's been shaking up healthcare with Cost Plus Drugs. So Mark, welcome.

Mark Cuban (00:25):

Thanks for having me, Eric.

Eric Topol (00:27):

Yeah, I mean, what you're doing, you’ve become a hero to millions of Americans getting them their medications at a fraction of the cost they're used to. And you are really challenging the PBM industry, which I've delved into more than ever, just in prep for our conversation. It's just amazing what this group of companies, namely the three big three CVS Caremark, Optum of UnitedHealth and Express Scripts of Cigna with a market of almost $600 billion this year, what they're doing, how can they get away with all this stuff?

Inner Workings of Pharmacy Benefit Managers

Mark Cuban (01:03):

I mean, they're just doing business. I really don't blame them. I blame the people who contract with them. All the companies, particularly the bigger companies, the self-insured companies, where the CEO really doesn't have an understanding of their healthcare or pharmacy benefits. And so, the big PBMs paid them rebates, which they think is great if you're a CEO, when in reality it's really just a loan against the money spent by your sickest employees, and they just don't understand that. So a big part of my time these days is going to CEOs and sitting with them and explaining to them that you're getting ripped off on both your pharmacy and your healthcare side.

Eric Topol (01:47):

Yeah, it's amazing to me the many ways that they get away with this. I mean, they make companies sign NDAs. They're addicted to rebates. They have all sorts of ways a channel of funds to themselves. I mean, all the things you could think of whereby they even have these GPOs. Each of these companies has a group purchasing organization (I summarized in the Table below).

Mark Cuban (02:12):

Yeah, which gives them, it's crazy because with those GPOs. The GPO does the deal with the pharmacy manufacturer. Then the GPO also does the deal with the PBM, and then the PBM goes to the self-insured employer in particular and says, hey, we're going to pass through all the rebates. But what they don't say is they've already skimmed off 5%, 10%, 20% or more off the top through their GPO. But that's not even the worst of it. That's just money, right? I mean, that's important, but I mean, even the biggest companies rarely own their own claims data.

Mark Cuban (02:45):

Now think about what that means. It means you can't get smarter about the wellness of your employees and their families. You want to figure out the best way to do GLP-1s and figure out how to reduce diabetes, whatever it may be. You don't have that claims data. And then they don't allow the companies to control their own formularies. So we've seen Humira biosimilars come out and the big PBMs have done their own version of the biosimilar where we have a product called Yusimry, which is only $594 a month, which is cheaper than the cheapest biosimilar that the big three are selling. And so, you would think in a normal relationship, they would want to bring on this new product to help the employer. No, they won't do it. If the employer asks, can I just add Cost Plus Drugs to my network? They'll say no, every single time.

Mark Cuban (03:45):

Their job is not to save the employer money, particularly after they've given a rebate. Because once they give that loan, that rebate to the employer, they need to get that money back. It's not a gift. It's a loan and they need to have the rebates, and we don't do rebates with them at all. And I can go down the list. They don't control the formula. They don't control, you mentioned the NDAs. They can't talk to manufacturers, so they can't go to Novo or to Lilly and say, let's put together a GLP-1 wellness program. All these different things that just are common sense. It's not happening. And so, the good news is when I walk into these companies that self-insured and talk to the CEO or CFO, I'm not asking them to do something that's not in their best interest or not in the best interest of the lives they cover. I'm saying, we can save you money and you can improve the wellness of your employees and their families. Where's the downside?

Eric Topol (04:40):

Oh, yeah. Yeah. And the reason they can't see the claims is because of the privacy issues?

Mark Cuban (04:46):

No, no. That's just a business decision in the contract that the PBMs have made. You can go and ask. I mean, you have every right to your own claims. You don't need to have it personally identified. You want to find out how many people have GLP-1s or what are the trends, or God forbid there's another Purdue Pharma thing going on, and someone prescribing lots of opioids. You want to be able to see those things, but they won't do it. And that's only on the sponsor side. It's almost as bad if not worse on the manufacturer side.

Eric Topol (05:20):

Oh, yeah. Well, some of the work of PBMs that you've been talking about were well chronicled in the New York Times, a couple of major articles by Reed Abelson and Rebecca Robbins: The Opaque Industry Secretly Inflating Prices for Prescription Drugs and The Powerful Companies Driving Local Drugstores Out of Business. We'll link those because I think some people are not aware of all the things that are going on in the background.

Mark Cuban (05:39):

You see in their study and what they reported on the big PBMs, it's crazy the way it works. And literally if there was transparency, like Cost Plus offers, the cost of medications across the country could come down 20%, 30% or more.

Cost Plus Drugs

Eric Topol (05:55):

Oh, I mean, it is amazing, really. And now let's get into Cost Plus. I know that a radiologist, Alex Oshmyansky contacted you with a cold email a little over three years ago, and you formed Cost Plus Drugs on the basis of that, right?

Mark Cuban (06:12):

Yep, that's exactly what happened.

Eric Topol (06:15):

I give you credit for responding to cold emails and coming up with a brilliant idea with this and getting behind it and putting your name behind it. And what you've done, so you started out with something like 110 generics and now you're up well over 1,200 or 2,500 or something like that?

Mark Cuban (06:30):

And adding brands. And so, started with 111. Now we're around 2,500 and trying to grow it every single day. And not only that, just to give people an overview. When you go to www.costplusdrugs.com and you put in the name of your medication, let's just say it's tadalafil, and if it comes up. In this case, it will. It'll show you our actual cost, and then we just mark it up 15%. It's the same markup for everybody, and if you want it, we'll have a pharmacist check it. And so, that's a $5 fee. And then if you want ship to mail order, it's $5 for shipping. And if you want to use our pharmacy network, then we can connect you there and you can just pick it up at a local pharmacy.

Eric Topol (07:10):

Yeah, no, it's transparency. We don't have a lot of that in healthcare in America, right?

Mark Cuban (07:15):

No. And literally, Eric, the smartest thing that we did, and we didn't expect this, it's always the law of unintended consequences. The smartest thing we did was publish our entire price list because that allowed any company, any sponsor, CMS, researchers to compare our prices to what others were already paying. And we've seen studies come out saying, for this X number of urology drugs, CMS would save $3.6 billion a year. For this number of heart drugs at this amount per year, for chemotherapy drugs or MS drugs this amount. And so, it's really brought attention to the fact that for what PBMs call specialty drugs, whether there's nothing special about them, we can save people a lot of money.

Eric Topol (08:01):

It's phenomenal. As a cardiologist, I looked up a couple of the drugs that I'm most frequently prescribed, just like Rosuvastatin what went down from $134 to $5.67 cents or Valsartan it went down from $69 to $7.40 cents. But of course, there's some that are much more dramatic, like as you mentioned, whether it's drugs for multiple sclerosis, the prostate cancer. I mean, some of these are just thousands and thousands of dollars per month that are saved, brought down to levels that you wouldn't think would even be conceivable. And this has been zero marketing, right?

Mark Cuban (08:42):

Yeah, none. It's all been word of mouth and my big mouth, of course. Going out there and doing interviews like this and going to major media, but it's amazing. We get emails and letters and people coming up to us almost single day saying, you saved my grandma's life. You saved my life. We weren't going to be able to afford our imatinib or our MS medication. And it went from being quoted $2,000 a month to $33 a month. It's just insane things like that that are still happening.

Eric Topol (09:11):

Well, this is certainly one of the biggest shakeups to occur in US healthcare in years. And what you've done in three years is just extraordinary. This healthcare in this country is with its over 4 trillion, pushing $5 trillion a year of expenditure.[New CMS report this week pegs the number at $4.867 trillion for 2023]

Mark Cuban (09:30):

It's interesting. I think it's really fixable. This has been the easiest industry to the disrupt I've ever been involved in. And it's not even close because all it took was transparency and not jacking up margins to market. We choose to use a fixed margin markup. Some choose to price to market, the Martin Shkreli approach, if you will. And just by being transparent, we've had an impact. And the other side of it is, it's the same concept on the healthcare side. Transparency helps, but to go a little field of pharmacy if you want. The insane part, and this applies to care and pharmacy, whatever plan we have, whether it's for health or whether it's for pharmaceuticals, there's typically a deductible, typically a copay, and typically a co-insurance.

Insurance Companies

Mark Cuban (10:20):

The crazy part of all that is that people taking the default risk, the credit risk are the providers. It's you, it's the hospital, it's the clinics that you work for. Which makes no sense whatsoever that the decisions that you or I make for our personal insurance or for the companies we run, or if we work for the government, what we do with Medicare or Medicare Advantage, the decisions we all make impacts the viability of providers starting with the biggest hospital systems. And so, as a result, they become subprime lenders without a car or a house to go after if they can't collect. And so, now you see a bunch of people, particularly those under the ACA with the $9,000, the bronze plans or $18,000 out-of-pocket limits go into debt, significant medical debt. And it's unfortunate. We look at the people who are facing these problems and think, well, it must be the insurance companies.

Mark Cuban (11:23):

It's actually not even the insurance companies. It's the overall design of the system. But underneath that, it's still whoever picks the insurance companies and sets plans that allow those deductibles, that's the core of the problem. And until we get to a system where the providers aren't responsible for the credit for defaults and dealing with all that credit risk, it's almost going to be impossible to change. Because when you see stories like we've all seen in news of a big healthcare, a BUCA healthcare (Blue Cross Blue Shield (BCBS), UnitedHealth, Cigna, and Aetna/CVS) plan with all the pre-authorizations and denials, typically they're not even taking the insurance risk. They're acting as the TPA (third party administrator) as the claims processor effectively for whoever hired them. And it goes back again, just like I talked about before. And as long as CMS hires or allows or accepts these BUCAs with these plans for Medicare for the ACA (Affordable care Act), whatever it may be, it's not going to work. As long as self-insured employers and the 50 million lives they cover hire these BUCAs to act as the TPAs, not as insurance companies and give them leeway on what to approve and what to authorize and what not to authorize. The system's going to be a mess, and that's where we are today.

Academic Health System Partnerships

Eric Topol (12:41):

Yeah. Well, you've been talking of course to employers and enlightening them, and you're also enlightening the public, of course. That's why you have millions of people that are saving their cost of medications, but recently you struck a partnership with Penn Medicine. That's amazing. So is that your first academic health system that you approached?

Cost Plus Marketplace

Mark Cuban (13:00):

I don't know if it was the first we approached, but it was certainly one of the biggest that we signed. We've got Cost Plus Marketplace (CPM) where we make everything from injectables to you name it, anything a hospital might buy. But again, at a finite markup, we make eight and a half percent I think when it's all said and done. And that saves hospital systems millions of dollars a year.

Eric Topol (13:24):

Yeah. So that's a big change in the way you're proceeding because what it was just pills that you were buying from the pharma companies, now you're actually going to make injectables and you're going to have a manufacturing capability. Is that already up and going?

Mark Cuban (13:39):

That's all up and going as of March. We're taking sterile injectables that are on the shortage list, generic and manufacturing them in Dallas using a whole robotics manufacturing plant that really Alex created. He's the rocket scientist behind it. And we’re limited in capacity now, we're limited about 2 million vials, but we'll sell those to Cost Plus Marketplace, and we'll also sell those direct. So Cost Plus Marketplace isn't just the things we manufacture. It's a wide variety of products that hospitals buy that we then have a minimal markup, and then for the stuff we manufacture, we'll sell those to direct to like CHS was our first customer.

Eric Topol (14:20):

Yeah, that's a big expansion from going from the pills to this. Wow.

Mark Cuban (14:24):

It's a big, big expansion, but it goes to the heart of being transparent and not being greedy, selling on a markup. And ourselves as a company, being able to remain lean and mean. The only way we can sell at such a low markup. We have 20 employees on the Cost Plus side and 40 employees involved with the factories, and that's it.

Eric Topol (14:46):

Wow. So with respect to, you had this phenomenal article and interview with WIRED Magazine just this past week. I know Lauren Goode interviewed you, and she said, Mark, is this really altruistic and I love your response. You said, “how much f*****g money do I need? I'm not trying to land on Mars.” And then you said, “at this point in my life, it’s just like more money, or f**k up the healthcare industry.” This was the greatest, Mark. I mean, I got to tell you, it was really something.

Mark Cuban (15:18):

Yeah.

Eric Topol (15:19):

Well, in speaking of that, of course, the allusion to a person we know well, Elon. He posted on X/Twitter in recent days , I think just three or four days ago, shouldn't the American people be getting their money's worth? About this high healthcare administration costs where the US is completely away from any other OECD country. And as you and I know, we have the worst outcomes and the most costs of all the rich countries in the world. There's just nothing new here. Maybe it's new to him, but you had a fabulous response on both X and Bluesky where you went over all these things point by point. And of course, the whole efforts that you've been working on now for three years. You also mentioned something that was really interesting that I didn't know about were these ERISA lawsuits[Employee Retirement Income Security Act (ERISA) of 1974.] Can you tell us about that?

ERISA Lawsuits

Mark Cuban (16:13):

Yeah, that's a great question, Eric. So for self-insured companies in particular, we have a fiduciary responsibility on a wellness and on a financial basis to offer the members, your employees and their families the best outcomes at the best price. Now, you can't guarantee best outcomes, but you have to be able to explain the choices you made. You don't have to pick the cheapest, but again, you have to be able to explain why you made the choices that you did. And because a lot of companies have been doing, just like we discussed earlier, doing deals on the pharmacy side with just these big PBMs, without accounting for best practices, best price, best outcomes, a couple companies got sued. Johnson and Johnson and Wells Fargo were the first to get sued. And I think that's just the beginning. That's just the writing on the wall. I think they'll lose because they just dealt with the big pharmacy PBMs. And I think that's one of the reasons why we're so busy at Cost Plus and why I'm so busy because we're having conversation after conversation with companies and plenty of enough lawyers for that matter who want to see a price list and be able to compare what they're paying to what we sell for to see if they're truly living up to that responsibility.

Eric Topol (17:28):

Yeah, no, that's a really important thing that's going on right now that I think a lot of people don't know about. Now, the government of the US think because it's the only government of any rich country in the world, if not any country that doesn't negotiate prices, i.e., CMS or whatever. And only with the recent work of insulin, which is a single one drug, was there reduction of price. And of course, it's years before we'll see other drugs. How could this country not negotiate drugs all these years where every other place in the world they do negotiate with pharma?

Mark Cuban (18:05):

Because as we alluded to earlier, the first line in every single pharmaceutical and healthcare contract says, you can't talk about this contract. It’s like fight club. The number one rule of fight club is you can't talk about fight club, and it's really difficult to negotiate prices when it's opaque and everything's obfuscated where you can't really get into the details. So it's not that we're not capable of it, but it's just when there's no data there, it's really difficult because look, up until we started publishing our prices, how would anybody know?

Mark Cuban (18:39):

I mean, how was anybody going to compare numbers? And so, when the government or whoever started to negotiate, they tried to protect themselves and they tried to get data, but those big PBMs certainly have not been forthcoming. We’ve come along and publish our price list and all that starts to change. Now in terms of the bigger picture, there is a solution there, as I said earlier, but it really comes down to talking to the people who make the decisions to hire the big insurance companies and the big PBMs and telling them, no, you're not acting in your own best interest. Here's anybody watching out there. Ask your PBM if they can audit. If you can audit rather your PBM contract. What they'll tell you is, yeah, you can, but you have to use our people. It's insane. And that's from top to bottom. And so, I'm a big believer that if we can get starting with self-insured employers to act in their own best interest, and instead of working with a big PBM work with a pass-through PBM. A pass-through PBM will allow you to keep your own claims, own all your own data, allow you to control your own formulary.

Mark Cuban (19:54):

You make changes where necessary, no NDA, so you can't talk to manufacturers. All these different abilities that just seem to make perfect sense are available to all self-insured employers. And if the government, same thing. If the government requires pass-through PBMs, the price of medications will drop like a rock.

Eric Topol (20:16):

Is that possible? You think that could happen?

Mark Cuban (20:19):

Yes. Somebody's got to understand it and do it. I'm out there screaming, but we will see what happens with the new administration. There's nothing hard about it. And it's the same thing with Medicare and Medicare Advantage healthcare plans. There's nothing that says you have to use the biggest companies. Now, the insurance companies have to apply and get approved, but again, there's a path there to work with companies that can reduce costs and improve outcomes. The biggest challenge in my mind, and I'm still trying to work through this to fully understand it. I think where we really get turned upside down as a country is we try to avoid fraud from the provider perspective and the patient perspective. We're terrified that patients are going to use too much healthcare, and like everybody's got Munchausen disease.

Mark Cuban (21:11):

And we're terrified that the providers are going to charge too much or turn into Purdue Pharma and over-prescribe or one of these surgery mills that just is having somebody get surgery just so they can make money. So in an effort to avoid those things, we ask the insurance companies and the PBMs to do pre-authorizations, and that's the catch 22. How do we find a better way to deal with fraud at the patient and provider level? Because once we can do that, and maybe it's AI, maybe it's accepting fraud, maybe it's imposing criminal penalties if somebody does those things. But once we can overcome that, then it becomes very transactional. Because the reality is most insurance companies aren't insurance companies. 50 million lives are covered by self-insured employers that use the BUCAs, the big insurance companies, but not as insurance companies.

Eric Topol (22:07):

Yeah, I was going to ask you about that because if you look at these three big PBMs that control about 80% of the market, not the pass-throughs that you just mentioned, but the big ones, they each are owned by an insurance company. And so, when the employer says, okay, we're going to cover your healthcare stuff here, we're going to cover your prescriptions there.

Mark Cuban (22:28):

Yeah, it's all vertically integrated.

Mark Cuban (22:36):

And it gets even worse than that, Eric. So they also own specialty pharmacies, “specialty pharmacies” that will require you to buy from. And as I alluded to earlier, a lot of these medications like Imatinib, they'll list as being a specialty medication, but it's a pill. There's nothing special about it, but it allows them to charge a premium. And that's a big part of how the PBMs make a lot of their money, the GPO stuff we talked about, but also forcing an employer to go through the specialty mail order company that charges an arm and the leg.

Impact on Hospitals and Procedures

Eric Topol (23:09):

Yeah. Well, and the point you made about transparency, we've seen this of course across US healthcare. So for example, as you know, if you were to look at what does it cost to have an operation like let's say a knee replacement at various hospitals, you can find that it could range fivefold. Of course, you actually get the cost, and it could be the hospital cost, and then there's the professional cost. And the same thing occurs for if you're having a scan, if you're having an MRI here or there. So these are also this lack of transparency and it's hard to get to the numbers, of course. There seems to be so many other parallels to the PBM story. Would you go to these other areas you think in the future?

Mark Cuban (23:53):

Yeah, we're doing it now. I'm doing it. So we have this thing called project dog food, and what it is, it's for my companies and what we've done is say, look, let's understand how the money works in healthcare.

Mark Cuban (24:05):

And when you think about it, when you go to get that knee done, what happens? Well, they go to your insurance company to get a pre-authorization. Your doctor says you need a knee replacement. I got both my hips replaced. Let's use that. Doctor says, Mark, you need your hips replaced. Great, right? Let's set up an appointment. Well, first the insurance company has to authorize it, okay, they do or they don't, but the doctor eats their time up trying to deal with the pre-authorization. And if it's denied, the doctor's time is eaten up and an assistance's time is eaten up. Some other administrator's time is eaten up, the employer's time is eaten up. So that's one significant cost. And then from there, there's a deductible. Now I can afford my deductible, but if there is an individual getting that hip replacement who can't afford the deductible, now all of a sudden you're still going to be required to do that hip replacement, most likely.

Mark Cuban (25:00):

Because in most of these contracts that self-insured employers sign, Medicare Advantage has, Medicare has, it says that between the insurance company and the provider, in this case, the hospital, you have to do the operation even if the deductibles not paid. So now the point of all this is you have the hospital in this case potentially accumulating who knows how much bad debt. And it's not just the lost amount of millions and millions and billions across the entire healthcare spectrum that's there. It's all the incremental administrative costs. The lawyers, the benefits for those people, the real estate, the desk, the office space, all that stuff adds up to $10 billion plus just because the hospitals take on that credit default risk. But wait, there's more. So now the surgery happens, you send the bill to the insurance company. The insurance company says, well, we're not going to pay you. Well, we have a contract. This is what it says, hip replacement's $34,000. Well, we don't care first, we're going to wait. So we get the time value of money, and then we're going to short pay you.

Mark Cuban (26:11):

So the hospital gets short paid. So what do they have to do? They have to sue them or send letters or whatever it is to try to get their money. When we talk to the big hospital systems, they say that's 2%. That's 2% of their revenue. So you have all these associated credit loss dollars, you've got the 2% of, in a lot of cases, billions and billions of dollars. And so, when you add all those things up, what happens? Well, what happens is because the providers are losing all that money and having to spend all those incremental dollars for the administration of all that, they have to jack up prices.

Eric Topol (26:51):

Yeah. Right.

Mark Cuban (26:53):

So what we have done, we've said, look for my companies, we're going to pay you cash. We're going to pay you cash day one. When Mark gets that hip replacement, that checks in the bank before the operation starts, if that's the way you want it. Great, they're not going to have pre-authorizations. We're going to trust you until you give us a reason not to trust you. We're not short paying, obviously, because we're paying cash right there then.

Mark Cuban (27:19):

But in a response for all that, because we're cutting out all those ancillary costs and credit risk, I want Medicare pricing. Now the initial response is, well, Medicare prices, that's awful. We can't do it. Well, when you really think about the cost and operating costs of a hospital, it's not the doctors, it's not the facilities, it's all the administration that cost all the money. It's all the credit risks that cost all the money. And so, if you remove that credit risk and all the administration, all those people, all that real estate, all those benefits and overhead associated with them, now all of a sudden selling at a Medicare price for that hip replacement is really profitable.

Eric Topol (28:03):

Now, is that a new entity Cost Plus healthcare?

Mark Cuban (28:07):

Well, it's called Cost Plus Wellness. It's not an entity. What we're going to do, so the part I didn't mention is all the direct contracts that we do that have all these pieces, as part of them that I just mentioned, we're going to publish them.

Eric Topol (28:22):

Ah, okay.

Mark Cuban (28:23):

And you can see exactly what we've done. And if you think about the real role of the big insurances companies for hospitals, it's a sales funnel.

Getting Rid of Insurance Companies

Eric Topol (28:33):

Yeah, yeah. Well, in fact, I really was intrigued because you did a podcast interview with Andrew Beam and the New England Journal of Medicine AI, and in that they talked about getting rid of the insurers, the insurance industry, just getting rid of it and just make it a means test for people. So it's not universal healthcare, it's a different model that you described. Can you go over that? I thought it was fantastic.

Mark Cuban (29:00):

Two pieces there. Let's talk about universal healthcare first. So for my companies, for our project dog food for the Mark Cuban companies, if for any employee or any of the lives we cover, if they work within network, anybody we have the direct contract with its single-payer. They pay their premiums, but they pay nothing else out of pocket. That's the definition of single-payer.

Eric Topol (29:24):

Yeah.

Mark Cuban (29:25):

So if we can get all this done, then the initial single-payers will be self-insured employers because it'll be more cost effective to them to do this approach. We hope, we still have to play it all through. So that's part one. In terms of everybody else, then you can say, why do we need insurance companies if they're not even truly acting as insurance companies? You're not taking full risk because even if it's Medicare Advantage, they're getting a capitated amount per month. And then that's getting risk adjusted because of the population you have, and then there's also an index depending on the location, so there's more or less money that occurs then. So let's just do what we need to do in this particular case, because the government is effectively eliminating the risk for the insurance company for the most part. And if you look at the margins for Medicare Advantage, I was just reading yesterday, it's like $1,700 a year for the average Medicare Advantage plan. So it's not like they're taking a lot of risk. All they're doing is trying to deny as many claims as they can.

Eric Topol (30:35):

Deny, Deny. Yeah.

Mark Cuban (30:37):

So instead, let's just get somebody who's a TPA, somebody who does the transaction, the claims processing, and whoever's in charge. It could be CMS, can set the terms for what's accepted and what's denied, and you can have a procedure for people that get denied that want to challenge it. And that's great, there's one in place now, but you make it a little simpler. But you take out the economics for the insurance company to just deny, deny, deny. There's no capitation. There's no nothing.

Mark Cuban (31:10):

The government just says, okay, we're hiring this TPA to handle the claims processing. It is your job. We're paying you per transaction.

Mark Cuban (31:18):

You don't get paid more if you deny. You don't get paid less if you deny. There's no bonuses if you keep it under a certain amount, there's no penalties If you go above a certain amount. We want you just to make sure that the patient involved is getting the best care, end of story. And if there's fraud involved as the government, because we have access to all that claims data, we're going to introduce AI that reviews that continuously.

Mark Cuban (31:44):

So that we can see things that are outliers or things that we question, and there's going to mean mistakes, but the bet was, if you will, where we save more and get better outcomes that way versus the current system and I think we will. Now, what ends up happening on top of that, once you have all that claims data and all that information and everybody's interest is aligned, best care at the best price, no denials unless it's necessary, reduce and eliminate fraud. Once everybody's in alignment, then as long as that's transparent. If the city of Dallas decides for all the lives they cover the 300,000 lives they cover between pharmacy and healthcare, we can usually in actuarial tables and some statistical analysis, we can say, you know what, even with a 15% tolerance, it's cheaper for us just to pay upfront and do this single-pay program, all our employees in the lives we cover, because we know what it's going to take.

Mark Cuban (32:45):

If the government decides, well, instead of Medicare Advantage the way it was, we know all the costs. Now we can say for all Medicare patients, we'll do Medicare for all, simply because we have definitive and deterministic pricing. Great. Now, there's still going to be outlier issues like all the therapies that cost a million dollars or whatever. But my attitude there is if CMS goes to Lilly, Novo, whoever for their cure for blindness that's $3.4 million. Well, that's great, but what we'll say is, okay, give us access to your books. We want to know what your breakeven point is. What is that breakeven point annually? We'll write you a check for that.

Eric Topol (33:26):

Yeah.

Mark Cuban (33:27):

If we have fewer patients than need that, okay, you win. If we have more patients than need that, it's like a Netflix subscription with unlimited subscribers, then we will have whatever it is, because then the manufacturer doesn't lose money, so they can't complain about R&D and not being able to make money. And that's for the CMS covered population. You can do a Netflix type subscription for self-insured employers. Hey, it's 25 cents per month per employee or per life covered for the life of the patent, and we'll commit to that. And so, now all of a sudden you get to a point where healthcare starts becoming not only transparent but deterministic.

Eric Topol (34:08):

Yeah. What you outline here in these themes are extraordinary. And one of the other issues that you are really advocating is patient empowerment, but one of the problems we have in the US is that people don't own their data. They don't even have all their data. I expect you'd be a champion of that as well.

Mark Cuban (34:27):

Well, of course. Yeah. I mean, look, I've got into arguments with doctors and public health officials about things like getting your own blood tested. I've been an advocate of getting my own blood tested for 15 years, and it helped me find out that I needed thyroid medication and all of these things. So I'm a big advocate. There's some people that think that too much data gives you a lot of false positives, and people get excited in this day and age to get more care when it should only be done if there are symptoms. I'm not a believer in that at all. I think now, particularly as AI becomes more applicable and available, you'll be able to be smarter about the data you capture. And that was always my final argument. Either you trust doctors, or you don't. Because even if there's an aberrational TSH reading and minus 4.4 and it's a little bit high, well the doctor's going to say, well, let's do another blood test in a month or two. The doctor is still the one that has to write the prescription. There's no downside to trusting your doctor in my mind.

Eric Topol (35:32):

And what you're bringing up is that we're already seeing how AI can pick up things even in the normal range, the trends long before a clinician physician would pick it up. Now, last thing I want to say is you are re-imagining healthcare like no one. I mean, there's what you're doing here. It started with some pills and it's going in a lot of different directions. You are rocking it here. I didn't even know some of the latest things that you're up to. This seems to be the biggest thing you've ever done.

Mark Cuban (36:00):

I hope so.

Mark Cuban (36:01):

I mean, like we said earlier, what could be better than people saying our healthcare system is good. What changed? That Cuban guy.

Eric Topol (36:10):

Well, did you give up Shark Tank so you could put more energy into this?

Mark Cuban (36:16):

Not really. It was more for my kids.

Eric Topol (36:19):

Okay, okay.

Mark Cuban (36:20):

They go hand in hand, obviously. I can do this stuff at home as opposed to sitting on a set wondering if I should invest in Dude Wipes again.

Eric Topol (36:28):

Well, look, we're cheering for you. This is, I've not seen a shakeup in my life in American healthcare like this. You are just rocking. It's fantastic.

Mark Cuban (36:37):

Everybody out there that's watching, check out www.costplusdrugs.com, check out Cost Plus Marketplace, which is business.costplusdrugs.com and just audit everything. What I'm trying to do is say, okay, if it's 1955 and we're starting healthcare all over again, how would we do it? And really just keep it simple. Look to where the risk is and remove the risk where possible. And then it comes down to who do you trust and make sure you trust but verify. Making sure there aren't doctors or systems that are outliers and making sure that there aren't companies that are outliers or patients rather that are outliers. And so, I think there's a path there. It's not nearly as difficult, it's just starting them with corporations, getting those CEOs to get educated and act in their own best interest.

Eric Topol (37:32):

Well, you're showing us the way. No question. So thanks so much for joining, and we'll be following this with really deep interest because you're moving at high velocity, and thank you.

**************************************************

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Footnote

The PBMS (finally) are under fire—2 articles from the past week

A leader for conducting rigorous randomized trials of humans along with animal models for understanding nutrition and metabolism, Dr. Kevin Hall is a Senior Investigator at the National Institutes of Health, and Section Chief of the Integrative Physiology Section, NIDDK. In this podcast, we reviewed his prolific body of research a recent publications. The timing of optimizing our diet and nutrition seems apropos, now that we’re in in the midst of the holiday season!

Below is a video snippet of our conversation on his ultra-processed food randomized trial.

Full videos of all Ground Truths podcasts can be seen on YouTube here. The current one is here. If you like the YouTube format, please subscribe! The audios are also available on Apple and Spotify.

Note: I’ll be doing a Ground Truths Live Chat on December 11th at 12 N EST, 9 AM PST, so please mark your calendar and join!

Transcript with links to publications and audio

Eric Topol (00:05):

Well, hello. This is Eric Topol with Ground Truths, and I'm really delighted to have with me today, Dr. Kevin Hall from the NIH. I think everybody knows that nutrition is so important and Kevin is a leader in doing rigorous randomized trials, which is not like what we usually see with large epidemiologic studies of nutrition that rely on food diaries and the memory of participants. So Kevin, it's really terrific to have you here.

Kevin Hall (00:34):

Thanks so much for the invitation.

Ultra-Processed Foods

Eric Topol (00:36):

Yeah. Well, you've been prolific and certainly one of the leaders in nutrition science who I look to. And what I thought we could do is go through some of your seminal papers. There are many, but I picked a few and I thought we'd first go back to the one that you published in Cell Metabolism. This is ultra-processed diets cause excessive caloric intake and weight gain. (Main results in graph below.) So maybe you can take us through the principle findings from that trial.

Kevin Hall (01:10):

Yeah, sure. So that was a really interesting study because it's the first randomized control trial that's investigated the role of ultra-processed foods in potentially causing obesity. So we've got, as you mentioned, lots and lots of epidemiological data that have made these associations between people who consume diets that are very high in ultra-processed foods as having greater risk for obesity. But those trials are not demonstrating causation. I mean, they suggest a strong link. And in fact, the idea of ultra-processed foods is kind of a new idea. It's really sort of appeared on the nutrition science stage probably most prominently in the past 10 years or so. And I first learned about this idea of ultra-processed foods, which is really kind of antithetical to the way most nutrition scientists think about foods. We often think about foods as nutrient delivery vehicles, and we kind of view foods as being the fraction of carbohydrates versus fats in them or how much sodium or fiber is in the foods.

Kevin Hall (02:17):

And along came this group in Brazil who introduced this new way of classifying foods that completely ignores the nutrient composition and says what we should be doing is classifying foods based on the extent and purpose of processing of foods. And so, they categorize these four different categories. And in the fourth category of this so-called NOVA classification scheme (see graphic below) , they identified something called ultra-processed foods. There's a long formal definition and it's evolved a little bit over the years and continues to evolve. But the basic ideas that these are foods that are manufactured by industries that contain a lot of purified ingredients made from relatively cheap agricultural commodity products that basically undergo a variety of processes and include additives and ingredients that are not typically found in home kitchens, but are typically exclusively in manufactured products to create the wide variety of mostly packaged goods that we see in our supermarkets.

Kevin Hall (03:22):

And so, I was really skeptical that there was much more about the effects of these foods. Other than that they typically have high amounts of sugar and saturated fat and salt, and they're pretty low in fiber. And so, the purpose of this study was to say, okay, well if there's something more about the foods themselves that is causing people to overconsume calories and gain weight and eventually get obesity, then we should do a study that's trying to test for two diets that are matched for these various nutrients of concern. So they should be matched for the macronutrients, they should be matched for the sugar content, the fat, the sodium, the fiber, and people should just be allowed to eat whatever they want and they shouldn't be trying to change their weight in any way. And so, the way that we did this was, as you mentioned, we can't just ask people to report what they're eating.

Kevin Hall (04:19):

So what we did was we admitted these folks to the NIH Clinical Center and to our metabolic ward, and it's a very artificial environment, but it's an environment that we can control very carefully. And so, what we basically did is take control over their food environment and we gave them three meals a day and snacks, and basically for a two-week period, they had access to meals that were more than 80% of calories coming from ultra-processed foods. And then in random order, they either received that diet first and give them simple instructions, eat as much as little as you want. We're going to measure lots of stuff. You shouldn't be trying to change your weight or weight that gave them a diet that had no calories from ultra-processed foods. In fact, 80% from minimally processed foods. But again, both of these two sort of food environments were matched for these nutrients that we typically think of as playing a major role in how many calories people choose to eat.

Kevin Hall (05:13):

And so, the basic idea was, okay, well let's measure what these folks eat. We gave them more than double the calories that they would require to maintain their weight, and what they didn't know was that in the basement of the clinical center where the metabolic kitchen is, we had all of our really talented nutrition staff measuring the leftovers to see what it was that they didn't eat. So we knew exactly what we provided to them and all the foods had to be in our nutrition database and when we compute what they actually ate by difference, so we have a very precise estimate about not only what foods they chose to ate, but also how many calories they chose to eat, as well as the nutrient composition.

And the main upshot of all that was that when these folks were exposed to this highly ultra-processed food environment, they spontaneously chose to eat about 500 calories per day more over the two-week period they were in that environment then when the same folks were in the environment that had no ultra-processed foods, but just minimally processed foods. They not surprisingly gained weight during the ultra-processed food environment and lost weight and lost body fat during the minimally processed food environment. And because those diets were overall matched for these different nutrients, it didn't seem to be that those were the things that were driving this big effect. So I think there's a couple of big take homes here. One is that the food environment really does have a profound effect on just the biology of how our food intake is controlled at least over relatively short periods of time, like the two-week periods that we were looking at. And secondly, that there's something about ultra-processed foods that seem to be driving this excess calorie intake that we now know has been linked with increased risk of obesity, and now we're starting to put some of the causal pieces together that really there might be something in this ultra-processed food environment that's driving the increased rates of obesity that we've seen over the past many decades.

Eric Topol (07:18):

Yeah, I mean I think the epidemiologic studies that make the link between ultra-processed foods and higher risk of cancer, cardiovascular disease, type 2 diabetes, neurodegenerative disease. They're pretty darn strong and they're backed up by this very rigorous study. Now you mentioned it short term, do you have any reason to think that adding 500 calories a day by eating these bad foods, which by the way in the American diet is about 60% or more of the average American diet, do you have any inkling that it would change after a few weeks?

Kevin Hall (07:54):

Well, I don't know about after a few weeks, but I think that one of the things that we do know about body weight regulation and how it changes in body weight impact both metabolism, how many calories were burning as well as our appetite. We would expect some degree of moderation of that effect eventually settling in at a new steady state, that's probably going to take months and years to achieve. And so the question is, I certainly don't believe that it would be a 500 calorie a day difference indefinitely. The question is when would that difference converge and how much weight would've been gained or lost when people eventually reached that new plateau? And so, that's I think a really interesting question. Some folks have suggested that maybe if you extrapolated the lines a little bit, you could predict when those two curves might eventually converge. That's an interesting thought experiment, but I think we do need some longer studies to investigate how persistent are these effects. Can that fully explain the rise in average body weight and obesity rates that have occurred over the past several decades? Those are open questions.

Eric Topol (09:03):

Yeah. Well, I mean, I had the chance to interview Chris van Tulleken who wrote the book, Ultra-Processed People and I think you might remember in the book he talked about how he went on an ultra-processed diet and gained some 20, 30 pounds in a short time in a month. And his brother, his identical twin brother gained 50, 60 pounds, and so it doesn't look good. Do you look at all the labels and avoid all this junk and ultra-processed food now or are you still thinking that maybe it's not as bad as it looks?

Kevin Hall (09:38):

Well, I mean I think that I certainly learned a lot from our studies, and we are continuing to follow this up to try to figure out what are the mechanisms by which this happen. But at the same time, I don't think we can throw out everything else we know about nutrition science. So just because we match these various nutrients in this particular study, I think one of the dangers here is that as you mentioned, there's 60% of the food environment in the US and Great Britain and other places consist of these foods, and so they're unavoidable to some extent, right? Unless you're one of these privileged folks who have your backyard garden and your personal chef who can make all of your foods, I'm certainly not one of those people, but for the vast majority of us, we're going to have to incorporate some degree of ultra-processed foods in our day-to-day diet.

Kevin Hall (10:24):

The way I sort of view it is, we really need to understand the mechanisms and before we understand the mechanisms, we have to make good choices based on what we already know about nutrition science, that we should avoid the foods that have a lot of sugar in them. We should avoid foods that have a lot of saturated fat and sodium. We should try to choose products that contain lots of whole grains and legumes and fruits and vegetables and things like that. And there's some of those, even in the ultra-processed food category. I pretty regularly consume a microwavable ready meal for lunch. It tends to be pretty high in whole grains and legumes and low in saturated fat and sugar and things like that. But to engineer a food that can heat up properly in a microwave in four minutes has some ultra-processing technology involved there. I would be pretty skeptical that that's going to cause me to have really poor health consequences as compared to if I had the means to eat homemade French fries every day in tallow. But that's the kind of comparison that we have to think about.

Eric Topol (11:36):

But I think what you're touching on and maybe inadvertently is in that NOVA class four, the bad ultra-processed foods, there's a long, long list of course, and some of those may be worse than others, and we haven't seen an individual ranking of these constituents. So as you're alluding to what's in that microwave lunch probably could be much less concerning than what's in these packaged snacks that are eaten widely. But I would certainly agree that we don't know everything about this, but your study is one of the most quoted studies ever in the ultra-processed food world. Now, let me move on to another trial that was really important. This was published in Nature Medicine and it's about a plant-based diet, which is of course a very interesting diet, low-fat versus an animal-based ketogenic diet. Also looking at energy intake. Can you take us through that trial?

Plant-Based, Low Fat Diet vs Animal-Based, Low Carbohydrate Ketogenic Diet

Kevin Hall (12:33):

Sure. So it's actually interesting to consider that trial in the context of the trial we just talked about because both of these diets that we tested in this trial were relatively low in ultra-processed foods, and so both of them contained more than a kilogram of non-starchy vegetables as a base for designing these, again, two different food environments. Very similar overall study design where people again were exposed to either diets that were vegan plant-based diet that was really high in starches and was designed to kind of cause big insulin increases in the blood after eating the meals. And the other diet had very, very few carbohydrates of less than 10% in total, and we built on that kind of non-starchy vegetable base, a lot of animal-based products to kind of get a pretty high amount of fat and having very low carbohydrates. Both diets in this case, like I mentioned, were pretty low in ultra-processed foods, but what we were really interested in here was testing this idea that has come to prominence recently, that high carbohydrate diets that lead to really large glucose excursions after meals that cause very high insulin levels after meals are particularly obesogenic and should cause you to be hungrier than compared to a diet that doesn't lead to those large swings in glucose and insulin and the prototypical case being one that's very low in carbohydrate and might increase the level of ketones that are floating around in your blood, which are hypothesized to be an appetite suppressant. Same sort of design, these minimally processed diets that one was very high in carbs and causes large swings in insulin and the other that's very low in carbs and causes increases in ketones.

Kevin Hall (14:22):

We ask people, again, while you're in one food environment or the other, don't be trying to gain weight or lose weight, eat as much or as little as you'd like, and we're going to basically measure a lot of things. They again, don't know what the primary outcome of the study is. We're measuring their leftovers afterwards. And so, the surprise in this particular case was that the diet that caused the big swings in glucose and insulin did not lead to more calorie consumption. In fact, it led to about 700 calories per day less than when the same people were exposed to the ketogenic diet. Interestingly, both food environments caused people to lose weight, so it wasn't that we didn't see the effect of people over consuming calories on either diet, so they were reading fewer calories in general than they were when they came in, right. They're probably eating a pretty ultra-processed food diet when they came in. We put them on these two diets that varied very much in terms of the macronutrients that they were eating, but both were pretty minimally processed. They lost weight. They ended up losing more body fat on the very low-fat high carb diet than the ketogenic diet, but actually more weight on the ketogenic diet than the low-fat diet. So there's a little bit of a dissociation between body fat loss and weight loss in this study, which was kind of interesting.

Eric Topol (15:49):

Interesting. Yeah, I thought that was a fascinating trial because plant-based diet, they both have their kind of camps, you know.

Kevin Hall (15:57):

Right. No, exactly.

Immune System Signatures for Vegan vs Ketogenic Diets

Eric Topol (15:58):

There are people who aren't giving up on ketogenic diet. Of course, there's some risks and some benefits and there's a lot of interest of course with the plant-based diet. So it was really interesting and potentially the additive effects of plant-based with avoidance or lowering of ultra-processed food. Now, the more recent trial that you did also was very interesting, and of course I'm only selecting ones that I think are particularly, there are a lot of trials you've done, but this one is more recent in this year where you looked at vegan versus ketogenic diets for the immune signature, immune response, which is really important. It's underplayed as its effect, and so maybe you can take us through that one.

[Link to a recent Nature feature on this topic, citing Dr. Hall’s work]

Kevin Hall (16:43):

Yeah, so just to be clear, it's actually the same study, the one that we just talked about. This is a secondary sort of analysis from a collaboration we had with some folks at NIAID here at the NIH to try to evaluate immune systems signatures in these same folks who wonder what these two changes in their food environment. One is vegan, high carbohydrate low-fat diet and the other, the animal-based ketogenic diet. And again, it was pretty interesting to me that we were able to see really substantial changes in how the immune system was responding. First of all, both diets again seem to have improved immune function, both adaptive and innate immune function as compared to their baseline measurements when they came into the study. So when they're reading their habitual diet, whatever that is typically high in ultra-processed foods, they switched to both of these diets.

Kevin Hall (17:39):

We saw market changes in their immune system even compared to baseline. But when we then went and compared the two diets, they were actually divergent also, in other words, the vegan diet seemed to stimulate the innate immune system and the ketogenic diet seemed to stimulate the adaptive immune system. So these are the innate immune system can be thought of. Again, I'm not an immunologist. My understanding is that this is the first line defense against pathogens. It happens very quickly and then obviously the adaptive immune system then adapts to a specific pathogen over time. And so, this ability of our diet to change the immune system is intriguing and how much of that has to do with influencing the gut microbiota, which obviously the gut plays a huge role in steering our immune system in one direction versus another. I think those are some really intriguing mechanistic questions that are really good fodder for future research.

Eric Topol (18:42):

Yeah, I think it may have implications for treatment of autoimmune diseases. You may want to comment about that.

Kevin Hall (18:51):

Yeah, it's fascinating to think about that the idea that you could change your diet and manipulate your microbiota and manipulate your gut function in a way to influence your immune system to steer you away from a response that may actually be causing your body damage in your typical diet. It's a fascinating area of science and we're really interested to follow that up. I mean, it kind of supports these more anecdotal reports of people with lupus, for example, who've reported that when they try to clean up their diet for a period of time and eliminate certain foods and eliminate perhaps even ultra-processed food products, that they feel so much better that their symptoms alleviate at least for some period of time. Obviously, it doesn't take the place of the therapeutics that they need to take, but yeah, we're really interested in following this up to see what this interaction might be.

Eric Topol (19:46):

Yeah, it's fascinating. It also gets to the fact that certain people have interesting responses. For example, those with epilepsy can respond very well to a ketogenic diet. There's also been diet proposed for cancer. In fact, I think there's some even ongoing trials for cancer of specific diets. Any comments about that?

Kevin Hall (20:10):

Yeah, again, it's a really fascinating area. I mean, I think we kind of underappreciate and view diet in this lens of weight loss, which is not surprising because that's kind of where it's been popularized. But I think the role of nutrition and how you can manipulate your diet and still you can have a very healthy version of a ketogenic diet. You can have a very healthy version of a low-fat, high carb diet and how they can be used in individual cases to kind of manipulate factors that might be of concern. So for example, if you're concerned about blood glucose levels, clearly a ketogenic diet is moderating those glucose levels over time, reducing insulin levels, and that might have some positive downstream consequences and there's some potential downsides. Your apoB levels might go up. So, you have to kind of tune these things to the problems and the situations that individuals may face. And similarly, if you have issues with blood glucose control, maybe a high carbohydrate diet might not be for you, but if that's not an issue and you want to reduce apoB levels, it seems like that is a relatively effective way to do that, although it does tend to increase fasting triglyceride levels.

Kevin Hall (21:27):

So again, there's all of these things to consider, and then when you open the door beyond traditional metabolic health markers to things like inflammation and autoimmune disease as well as some of these other things like moderating how cancer therapeutics might work inside the body. I think it's a really fascinating and interesting area to pursue.

Eric Topol (21:55):

No question about it. And that also brings in the dimension of the gut microbiome, which obviously your diet has a big influence, and it has an influence on your brain, brain-gut axis, and the immune system. It's all very intricate, a lot of feedback loops and interactions that are not so easy to dissect, right?

Kevin Hall (22:16):

Absolutely. Yeah, especially in humans. That's why we rely on our basic science colleagues to kind of figure out these individual steps in these chains. And of course, we do need human experiments and carefully controlled experiments to see how much of that really translates to humans, so we need this close sort of translational partnership.

On the Pathogenesis of Obesity, Calories In and Calories Out

Eric Topol (22:35):

Yeah. Now, you've also written with colleagues, other experts in the field about understanding the mechanisms of pathogenesis of obesity and papers that we'll link to. We're going to link to everything for what we've been discussing about calories in, calories out, and that's been the longstanding adage about this. Can you enlighten us, what is really driving obesity and calories story?

Kevin Hall (23:05):

Well, I co-organized a meeting for the Royal Society, I guess about a year and a half ago, and we got together all these experts from around the world, and the basic message is that we have lots of competing theories about what is driving obesity. There's a few things that we all agree on. One is that there is a genetic component. That adiposity in a given environment is somewhere between 40% to 70% heritable, so our genes play a huge role. It seems like there's certain genes that can play a major role. Like if you have a mutation in leptin, for example, or the leptin receptor, then this can have a monogenic cause of obesity, but that's very, very rare. What seems to be the case is that it's a highly polygenic disease with individual gene variants contributing a very, very small amount to increased adiposity. But our genes have not changed that much as obesity prevalence has increased over the past 50 years. And so, something in the environment has been driving that, and that's where the real debates sort of starts, right?

Kevin Hall (24:14):

I happen to be in the camp that thinks that the food environment is probably one of the major drivers and our food have changed substantially, and we're trying to better understand, for example, how ultra-processed foods which have risen kind of in parallel with the increased prevalence of obesity. What is it about ultra-processed foods that tend to drive us to overconsume calories? Other folks focus maybe more on what signals from the body have been altered by the foods that we're eating. They might say that the adipose tissue because of excess insulin secretion for example, is basically driven into a storage mode and that sends downstream signals that are eventually sensed by the brain to change our appetite and things like that. There's a lot of debate about that, but again, I think that these are complementary hypotheses that are important to sort out for sure and important to design experiments to try to figure out what is more likely. But there is a lot of agreement on the idea that there's something in our environment has changed.

Kevin Hall (25:17):

I think there's even maybe a little bit less agreement of exactly what that is. I think that there's probably a little bit more emphasis on the food environment as opposed to there are other folks who think increased pollution might be driving some of this, especially endocrine disrupting chemicals that have increased in prevalence. I think that's a viable hypothesis. I think we have to try to rank order what we think are the most likely and largest contributors. They could all be contributing to some extent and maybe more so in some people rather than others, but our goal is to try to, maybe that's a little simple minded, but let's take the what I think is the most important thing and let's figure out the mechanisms of that most important thing and we'll, number one, determine if it is the most important thing. In my case, I think something about ultra-processed foods that are driving much of what we're seeing. If we could better understand that, then we could both advise consumers to avoid certain kinds of foods because of certain mechanisms and still be able to consume some degree of ultra-processed foods. They are convenient and tasty and relatively inexpensive and don't require a lot of skill and equipment to prepare. But then if we focus on the true bad guys in that category because we really understand the mechanisms, then I think that would be a major step forward. But that's just my hypothesis.

Eric Topol (26:43):

Well, I’m with you actually. Everything I've read, everything I've reviewed on ultra-processed food is highly incriminating, and I also get frustrated that nothing is getting done about it, at least in this country. But on the other hand, it doesn't have to be either or, right? It could be both these, the glycemic index story also playing a role. Now, when you think about this and you're trying to sort out calories in and calories out, and let's say it's one of your classic experiments where you have isocaloric proteins and fat and carbohydrate exactly nailed in the different diets you're examining. Is it really about calories or is it really about what is comprising the calorie?

Kevin Hall (27:29):

Yeah, so I think this is the amazing thing, even in our ultra-processed food study, if we asked the question across those people, did the people who ate more calories even in the ultra-processed diet, did they gain more weight? The answer is yes.

Kevin Hall (27:44):

There's a very strong linear correlation between calorie intake and weight change. I tend to think that I started my career in this space focusing more on the metabolism side of the equation, how the body's using the calories and how much does energy expenditure change when you vary the proportion of carbs versus fat, for example. The effect size is there, they might be there, but they're really tiny of the order of a hundred calories per day. What really struck me is that when we just kind of changed people's food environments, the magnitude of the effects are like we mentioned, 500 to 700 calories per day differences. So I think that the real trick is to figure out how is it that the brain is regulating our body weight in some way that we are beginning to understand from a molecular perspective? What I think is less well understood is, how is that food intake control system altered by the food environment that we find ourselves in?

The Brain and GLP-1 Drugs

Kevin Hall (28:42):

There are a few studies now in mice that are beginning to look at how pathways in the brain that have been believed to be related to reward and not necessarily homeostatic control of food intake. They talk to the regions of the brain that are related to homeostatic control of food intake, and it's a reciprocal sort of feedback loop there, and we're beginning to understand that. And I think if we get more details about what it is in our foods that are modulating that system, then we'll have a better understanding of what's really driving obesity and is it different in different people? Are there subcategories of obesity where certain aspects of the food environment are more important than others, and that might be completely flipped in another person. I don't know the answer to that question yet, but it seems like there are certain common factors that might be driving overall changes in obesity prevalence and how they impact this reward versus homeostatic control systems in the brain, I think are really fascinating questions.

Eric Topol (29:43):

And I think we're getting much more insight about this circuit of the reward in the brain with the food intake, things like optogenetics, many ways that we're getting at this. And so, it's fascinating. Now, that gets me to the miracle drug class GLP-1, which obviously has a big interaction with obesity, but of course much more than that. And you've written about this as well regarding this topic of sarcopenic obesity whereby you lose a lot of weight, but do you lose muscle mass or as you referred to earlier, you lose body fat and maybe not so much muscle mass. Can you comment about your views about the GLP-1 family of drugs and also about this concern of muscle mass loss?

Kevin Hall (30:34):

Yeah, so I think it's a really fascinating question, and we've been trying to develop mathematical models about how our body composition changes with weight gain and weight loss for decades now. And this has been a long topic, one of the things that many people may not realize is that people with obesity don't just have elevated adiposity, they also have elevated muscle mass and lean tissue mass overall. So when folks with obesity lose weight, and this was initially a pretty big concern with bariatric surgery, which has been the grandfather of ways that people have lost a lot of weight. The question has been is there a real concern about people losing too much weight and thereby becoming what you call sarcopenic? They have too little muscle mass and then they have difficulties moving around. And of course, there are probably some people like that, but I think what people need to realize is that folks with obesity tend to start with much higher amounts of lean tissue mass as well as adiposity, and they start off with about 50% of your fat-free mass, and the non-fat component of your body is skeletal muscle.

Kevin Hall (31:45):

So you're already starting off with quite a lot. And so, the question then is when you lose a lot of weight with the GLP-1 receptor agonist or with bariatric surgery, how much of that weight loss is coming from fat-free mass and skeletal muscle versus fat mass? And so, we've been trying to simulate that using what we've known about bariatric surgery and what we've known about just intentional weight loss or weight gain over the years. And one of the things that we found was that our sort of expectations for what's expected for the loss of fat-free mass with these different drugs as well as bariatric surgery, for the most part, they match our expectations. In other words, the expected amount of fat loss and fat free mass loss. The one outlier interestingly, was the semaglutide study, and in that case, they lost more fat-free mass than would be expected.

Kevin Hall (32:44):

Now, again, that's just raising a little bit of a flag that for whatever reason, from a body composition perspective, it's about a hundred people underwent these repeated DEXA scans in that study sponsored by Novo Nordisk. So it's not a huge number of people, but it's enough to really get a good estimate about the proportion of weight loss. Whether or not that has functional consequences, I think is the open question. There's not a lot of reports of people losing weight with semaglutide saying, you know what? I'm really having trouble actually physically moving around. I feel like I've lost a lot of strength. In fact, it seems to be the opposite, right, that the quality of the muscle there seems to be improved. They seem to have more physical mobility because they've lost so much more weight, that weight had been inhibiting their physical movement in the past.

Kevin Hall (33:38):

So it's something to keep an eye on. It's an open question whether or not we need additional therapies in certain categories of patients, whether that be pharmacological, there are drugs that are interesting that tend to increase muscle mass. There's also other things that we know increase muscle mass, right? Resistance exercise training, increase this muscle mass. And so, if you're really concerned about this, I certainly, I'm not a physician, but I think it's something to consider that if you go on one of these drugs, you might want to think about increasing your resistance exercise training, maybe increasing the protein content of your diet, which then can support that muscle building. But I think it's a really interesting open question about what the consequences of this might be in certain patient populations, especially over longer periods of time.

Dietary Protein, Resistance Exercise, DEXA Scans

Eric Topol (34:30):

Yeah, you've just emphasized some really key points here. Firstly, that resistance exercise is good for you anyway. And get on one of these drugs, why don't you amp it up or get it going? The second is about the protein diet, which it'd be interesting to get your thoughts on that, but we generally have too low of a protein diet, but then there are some who are advocating very high protein diets like one gram per pound, not just one gram per kilogram. And there have been studies to suggest that that very high protein diet could be harmful, but amping up the protein diet, that would be a countering thing. But the other thing you mentioned is a DEXA scan, which can be obtained very inexpensively, and because there's a variability in this muscle mass loss if it's occurring, I wonder if that's a prudent thing or if you just empirically would just do the things that you mentioned. Do you have any thoughts about that?

Kevin Hall (35:32):

Yeah, that's really a clinical question that I don't deal with on a day-to-day basis. And yeah, I think there's probably better people suited to that. DEXA scans, they're relatively inexpensive, but they're not readily accessible to everyone. I certainly wouldn't want to scare people away from using drugs that are now known to be very effective for weight loss and pretty darn safe as far as we can tell, just because they don't have access to a DEXA scanner or something like that.

Eric Topol (36:00):

Sure. No, that makes a lot of sense. I mean, the only reason I thought it might be useful is if you're concerned about this and you want to track, for example, how much is that resistant training doing?

Kevin Hall (36:13):

But I think for people who have the means to do that, sure. I can't see any harm in it for sure.

Continuous Glucose Sensors?

Eric Topol (36:19):

Yeah. That gets me to another metric that you've written about, which is continuous glucose tracking. As you know, this is getting used, I think much more routinely in type one insulin diabetics and people with type 2 that are taking insulin or difficult to manage. And now in recent months there have been consumer approved that is no prescription needed, just go to the drugstore and pick up your continuous glucose sensor. And you've written about that as well. Can you summarize your thoughts on it?

Kevin Hall (36:57):

Yeah, sure. I mean, yeah, first of all, these tools have been amazing for people with diabetes and who obviously are diagnosed as having a relative inability to regulate their glucose levels. And so, these are critical tools for people in that population. I think the question is are they useful for people who don't have diabetes and is having this one metric and where you target all this energy into this one thing that you can now measure, is that really a viable way to kind of modulate your lifestyle and your diet? And how reliable are these CGM measurements anyway? In other words, do they give the same response to the same meal on repeated occasions? Does one monitor give the same response as another monitor? And those are the kinds of experiments that we've done. Again, secondary analysis, these trials that we talked about before, we have people wearing continuous glucose monitors all the time and we know exactly what they ate.

Kevin Hall (37:59):

And so, in a previous publication several years ago, we basically had two different monitors. One basically is on the arm, which is the manufacturer's recommendation, the other is on the abdomen, which is the manufacturer's recommendation. They're wearing them simultaneously. And we decided just to compare what were the responses to the same meals in simultaneous measurements. And they were correlated with each other thankfully, but they weren't as well predictive as you might expect. In other words, one device might give a very high glucose reading to consuming one meal and the other might barely budge, whereas the reverse might happen for a different meal. And so, we asked the question, if we were to rank the glucose spikes by one meal, so we have all these meals, let's rank them according to the glucose spikes of one device. Let's do the simultaneous measurements with the other device.

Kevin Hall (38:53):

Do we get a different set of rankings? And again, they're related to each other, but they're not overlapping. They're somewhat discordant. And so, then the question becomes, okay, well if I was basically using this one metric to kind of make my food decisions by one device, I actually start making different decisions compared to if I happen to have been wearing a different device. So what does this really mean? And I think this sort of foundational research on how much of a difference you would need to make a meaningful assessment about, yeah, this is actionable from a lifestyle perspective, even if that is the one metric that you're interested in. That sort of foundational research I don't think has really been done yet. More recently, we asked the question, okay, let's ignore the two different devices. Let's stick to the one where we put it on our arm, and let's ask the question.

Kevin Hall (39:43):

We've got repeated meals and we've got them in this very highly regimented and controlled environment, so we know exactly what people ate previously. We know the timing of the meals, we know when they did their exercise, we know how much they were moving around, how well they slept the night before. All of these factors we could kind of control. And the question that we asked in that study was, do people respond similarly to the same meal on repeated occasions? Is that better than when you actually give them very different meals? But they match overall for macronutrient content, for example. And the answer to that was surprisingly no. We had as much variability in the glucose response to the same person consuming the same meal on two occasions as a whole bunch of different meals. Which suggests again, that there's enough variability that it makes it difficult to then recommend on for just two repeats of a meal that this is going to be a meal that's going to cause your blood glucose to be moderate or blood glucose to be very high. You're going to have to potentially do this on many, many different occasions to kind of figure out what's the reliable response of these measurements. And again, that foundational research is typically not done. And I think if we're really going to use this metric as something that is going to change our lifestyles and make us choose some meals other than others, then I think we need that foundational research. And all we know now is that two repeats of the same meal is not going to do it.

Eric Topol (41:21):

Well, were you using the current biosensors of 2024 or were you using ones from years ago on that?

Kevin Hall (41:27):

No, we were using ones from several years ago when these studies were completed. But interestingly, the variability in the venous measurements to meal tests is also very, very different. So it's probably not the devices per se that are highly variable. It's that we don't really know on average how to predict these glucose responses unless there's huge differences in the glycemic load. So glycemic load is a very old concept that when you have very big differences in glycemic load, yeah, you can on average predict that one kind of meal is going to give rise to a much larger glucose excursion than another. But typically these kind of comparisons are now being made within a particular person. And we're comparing meals that might have quite similar glycemic loads with the claim that there's something specific about that person that causes them to have a much bigger glucose spike than another person. And that we can assess that with a couple different meals.

Eric Topol (42:31):

But also, we know that the spikes or the glucose regulation, it's very much affected by so many things like stress, like sleep, like exercise. And so, it wouldn't be at all surprising that if you had the exact same food, but all these other factors were modulated that it might not have the same response. But the other thing, just to get your comment on. Multiple groups, particularly starting in Israel, the Weizmann Institute, Eran Segal and his colleagues, and many subsequent have shown that if you give the exact same amount of that food, the exact same time to a person, they eat the exact same amount. Their glucose response is highly heterogeneous and variable between people. Do you think that that's true? That in fact that our metabolism varies considerably and that the glucose in some will spike with certain food and some won’t.

Kevin Hall (43:29):

Well, of course that's been known for a long time that there's varying degrees of glucose tolerance. Just oral glucose tolerance tests that we've been doing for decades and decades we know is actually diagnostic, that we use variability in that response as diagnostic of type 2 diabetes.

Eric Topol (43:49):

I'm talking about within healthy people.

Kevin Hall (43:53):

But again, it's not too surprising that varying people. I mean, first of all, we have a huge increase in pre-diabetes, right? So there's various degrees of glucose tolerance that are being observed. But yeah, that is important physiology. I think the question then is within a given person, what kind of advice do we give to somebody about their lifestyle that is going to modulate those glucose responses? And if that's the only thing that you look at, then it seems like what ends up happening, even in the trials that use continuous glucose monitors, well big surprise, they end up recommending low carbohydrate diets, right? So that's the precision sort of nutrition advice because if that's the main metric that's being used, then of course we've all known for a very long time that lower carbohydrate diets lead to a moderated glucose response compared to higher carbohydrate diets. I think the real question is when you kind of ask the issue of if you normalize for glycemic load of these different diets, and there are some people that respond very differently to the same glycemic load meal compared to another person, is that consistent number one within that person?

Kevin Hall (45:05):

And our data suggests that you're going to have to repeat that same test multiple times to kind of get a consistent response and be able to make a sensible recommendation about that person should eat that meal in the future or not eat that meal in the future. And then second, what are you missing when that becomes your only metric, right? If you're very narrowly focused on that, then you're going to drive everybody to consume a very low carbohydrate diet. And as we know, that might be great for a huge number of people, but there are those that actually have some deleterious effects of that kind of diet. And if you're not measuring those other things or not considering those other things and put so much emphasis on the glucose side of the equation, I worry that there could be people that are being negatively impacted. Not to mention what if that one occasion, they ate their favorite food and they happen to get this huge glucose spike and they never eat it again, their life is worse. It might've been a complete aberration.

Eric Topol (46:05):

I think your practical impact point, it's excellent. And I think one of the, I don't know if you agree, Kevin, but one of the missing links here is we see these glucose spikes in healthy people, not just pre-diabetic, but people with no evidence of glucose dysregulation. And we don't know, they could be up to 180, 200, they could be prolonged. We don't know if the health significance of that, and I guess someday we'll learn about it. Right?

Kevin Hall (46:36):

Well, I mean that's the one nice thing is that now that we have these devices to measure these things, we can start to make these correlations. We can start to do real science to say, what a lot of people now presume is the case that these spikes can't be good for you. They must lead to increased risk of diabetes. It's certainly a plausible hypothesis, but that's what it is. We actually need good data to actually analyze that. And at least that's now on the table.

Eric Topol (47:04):

I think you're absolutely right on that. Well, Kevin, this has been a fun discussion. You've been just a great leader in nutrition science. I hope you'll keep up your momentum because it's pretty profound and I think we touched on a lot of the uncertainties. Is there anything that I didn't ask you that you wish I did?

Kevin Hall (47:23):

I mean, we could go on for hours, I'm sure, Eric, but this has been a fascinating conversation. I really appreciate your interest. Thank you.

Eric Topol (47:30):

Alright, well keep up the great stuff. We'll be following all your work in the years ahead, and thanks for joining us on Ground Truths today.

**************************************

Footnote, Stay Tuned: Julia Belluz and Kevin Hall have a book coming out next September titled “WHY WE EAT?

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Below is a brief video snippet from our conversation. Full videos of all Ground Truths podcasts can be seen on YouTube here. The current one is here. If you like the YouTube format, please subscribe! This one has embedded one of my favorite TikTok’s from Will. There are several links to others in the transcript. The audios are also available on Apple and Spotify.

Transcript with links to both audio and videos, commencement addresses, NEJM article coverage

Eric Topol (00:06):

Hi, it's Eric Topol from Ground Truths, and I've got an amazing couple with me today. It's Will Flanary and Kristin Flanary, the Glaucomfleckens. I've had the chance to get to know them a bit through Knock Knock, Hi! which is their podcast. And of course, everyone knows Dr. Glaucomflecken from his TikTok world and his other about 4 million followers on Instagram and Twitter and all these other social media, and YouTube. So welcome.

Will Flanary (00:43):

Thanks for having us.

Kristin Flanary (00:44):

Thank you. Happy to be here.

By Way of Background

Eric Topol (00:45):

Yeah. Well, this is going to be fun because I'm going to go a quick background so we can go fast forward because we did an interview back in early 2022.

Kristin Flanary (00:56):

Yes.

Eric Topol (00:57):

And what you've been doing since then is rocking it. You're like a meteoric, right. And it was predictable, like rarefied talent and who couldn't love humor, medical humor, but by way of background, just for those who are not up to speed. I guess you got your start, Will, as a class clown when your mother was a teacher in the sixth grade.

Will Flanary (01:22):

Yep, yep. I misbehaved a little bit. It helped that I still made good grades, but I cut up a bit in class.

Eric Topol (01:32):

And then you were already in the comedy club circuits doing standup in Houston as an 18-year-old.

Will Flanary (01:40):

It was all amateur stuff, nothing, just dabble in it and trying to get better. I was always kind of naturally funny just with my friend group and everything. I loved making people laugh, but doing standups is a whole different ball game. And so, I started doing that around Houston as a high school senior and kept that going through college and a little bit into med school.

Kristin Flanary (02:02):

Houston was a good training ground, right? That where Harris Wittels was also coming up.

Will Flanary (02:07):

Yeah. A lot of famous comedians have come through Houston. Even going back to Bill Hicks back in the, was that the 80s, I think? Or 90s?

Eric Topol (02:17):

Well, and then of course, it was I think in 2020 when you launched Dr. Glaucomflecken, I think. Is that right?

Will Flanary (02:28):

That's when it really started to take off. I was on Twitter telling jokes back in 2016.

Kristin Flanary (02:39):

GomerBlog before that, that's actually where it was born.

Will Flanary (02:41):

I was doing satire writing. I basically do what I'm doing now, but in article form, trying to be The Onion of medicine. And then the pandemic hit, started doing video content and that's really with lockdown. That's when, because everybody was on social media, nobody had anything else to do. So it was right place, right time for me and branching out into video content.

On to Medical School Commencement Addresses

Eric Topol (03:11):

Alright, so that's the background of some incredible foundation for humor. But since we last got together, I'll link the Medicine and the Machine interview we did back then. What has been happening with you two is nothing short of incredible. I saw your graduation speeches, Will. Yale in 2022, I watched the UCSF in 2023 and then the University of Michigan in 2024. Maybe there's other ones I don't even know.

Kristin Flanary (03:45):

There’s a few others.

Will Flanary (03:45):

There's a few. But I feel like you've done, I'm sure your fair share of commencement addresses as well. It's kind of hard to come up with different ways to be inspirational to the next generation. So fortunately, we have together, we have some life experiences and learned a thing or two by doing all of this social media stuff and just the things we've been through that I guess I have enough things to say to entertain an interest.

Eric Topol (04:18):

Well, you're being humble as usual, but having watched those commencement addresses, they were the best medical commencement addresses I've ever seen. And even though you might have told us some of the same jokes, they were so great that it was all right. Yeah, and you know what is great about it is you've got these, not the students, they all love you of course, because they're probably addicted to when's your next video going to get posted.

(04:44):

But even the old professors, all the family members, it's great. But one of the things I wanted to get at. Well, I'll start with the graduation speeches, because you were such an inspiration, not just with humor, but your message. And this gets back to you as a couple and the tragedies you've been through. So you really, I think, got into this co-survivor story and maybe Kristin, since you are the co-survivor of two bouts of Will’s testicular cancer, and then the sudden cardiac death. I mean, people don't talk about this much, so maybe you could help enlighten us.

Tragedies and Being a Co-Survivor

Kristin Flanary (05:26):

Yeah, it’s funny because the experience of being a co-survivor is nothing new. It’s as long as we've had human beings, we've had co-survivors. But the concept around it and giving it a name and a label, a framework to be able to think about it, that is what I think is new and what people haven't talked about before. So co-survivor is just this idea that when a medical trauma happens to a patient, the patient has their experience and if they survive it, they are a survivor and they have a survivor experience. And also, most people are closely attached to at least one other person, if not many. And those people are co-surviving the medical event along with the survivor. That event is happening in their lives as was happening to them too. If someone comes in with a patient to the hospital, that person, you can just assume by default that their lives are pretty intimately or profoundly intertwined or else why would that person be there? And so, thinking of it as there's the patient and then there's also a co-patient, that family members in the past have only been thought of as caregivers if they've been thought of at all. And that is certainly one aspect of the role, but it's important to remember that whatever it is that's happening to the patient is also affecting the family members' lives in a really deep and profound way.

Eric Topol (07:04):

That's really helpful. Now, the fact that you recognize that in your graduation speech, Will, I think is somewhat unique. And of course, some of the other things that you touched on like playing to your creativity and the human factors, I mean, these are so important messages.

Will Flanary (07:23):

Well, in the discussion about co-survivorship and because I talk about that whenever I do my keynotes and when I do the commencement addresses, but all credit goes to Kristin for really being the driving force of this idea for me and for many others because as a physician, we take care of patients. Our focus is always on the patient. And it really wasn't until this happened to me and my family and Kristin in particular that I started to understand exactly what she's talking about and this idea. And so, Kristin gets a lot of credit for just really bringing that term and that idea to the forefront.

Eric Topol (08:09):

Yeah, well, you saved his life. It's just not many have that bond. And then the other thing I just want to mention now, you've been recognized by the American Heart Association and a whole bunch of other organizations awarded because of your advocacy for CPR. And you even mentioned that I think in one of your commencement addresses.

Will Flanary (08:31):

Yeah, I tried to get the crowd to do CPR. Like team up, partner up, and it kind of fell flat. It wasn't quite the right time, I think, to try to do a mass class on CPR. So maybe next time.

Eric Topol (08:47):

Right. Well, so you had this foundation with the Glaucomflecken General Hospital and taking on 37 specialties and all these incredible people that became part of the family, if you will, of spoof on medicine and your alter ego and these videos that you would do. And sometimes you have three or four different alter egos in there playing out, but now you've branched into new things. So one which is an outgrowth of what we were just talking about. You've been on this country tour, Wife & Death.

“Wife and Death,” A Nationwide Tour

Kristin Flanary (09:28):

Yes.

Eric Topol (09:29):

Wife and death. I mean, yeah, I guess we can make the connect of how you named it that, but what is it you've been selling out in cities all over the country, and by the way, I'm really upset you haven't come to San Diego, but tell us about wife and death.

Will Flanary (09:44):

Yeah. Well, we have this amazing story and all these medical challenges we've been through, and then developing the Glaucomflecken brand and universe, and we've done keynotes together for years, and then we thought, let's have more fun with it. Let's do keynotes. They're great. We can get our message out, but sometimes they're just a bit stuffy. It's an academic environment.

Kristin Flanary (10:15):

They're usually at seven in the morning also, so that's the downside.

Will Flanary (10:21):

So we thought, let's just put together our own live show. Let's put together something that we could just creatively, we can do whatever we want with it. I could dress up as characters, Kristin, who has these beautiful writing and monologues that she's put together around her experience and just to create something that people can come into a theater and just experience this wide range of emotions from just laughter to tears of all kinds, and just have them feel the story and enjoy this story. Fortunately, it has a happy ending because I'm still alive and it's been so much fun. The audiences have been incredible. Mostly healthcare, but even some non-healthcare people show up, and we've been blown away by the response. Honestly, we should have done bigger theaters. That's our lesson for the first go round.

Eric Topol (11:21):

I saw you had to do a second show in Pittsburgh.

Will Flanary (11:24):

We did.

Kristin Flanary (11:26):

That one sold out too. Something about Pittsburgh, that was a good crowd, and there was a lot of them.

Will Flanary (11:33):

It was almost like in Pittsburgh, they rarely ever get any internet comedian ophthalmologists that come through. I don't know.

Eric Topol (11:41):

Well, I see you got some still to come in Denver and Chicago. This is amazing. And I wondered who was coming and I mean, it's not at all surprising that there'd be this phenomenal popularity. So that's one thing you've done that's new, which is amazing. And of course, it's a multidimensional story. The one that shocked me, I have to tell you, shocked me, was the New England Journal partnership. The New England Journal is the most stodgy, arrogant, I mean so difficult. And not only that.

Kristin Flanary (12:17):

You said that. Not us.

Partnering with the New England Journal of Medicine!

Eric Topol (12:19):

Yeah, yeah. They'll get this too. They know we don't get along that well, but that's okay. You even made fun of journals. And now you're partnering with the New England Journal, God's greatest medical journal, or whatever. Tell us about that.

Will Flanary (12:39):

Well, so one thing that I really enjoy doing, and I've done it with my US healthcare system content is almost like tricking people into learning things. And so, if you make something funny, then people will actually sit there and listen to what you have to say about deductibles and physician-owned hospitals and all these inner workings. DIR fees and pharmacy, all these things that are really dry topics. But if you can make them funny, all of a sudden people will actually learn and listen to it. And the New England Journal of Medicine, they approached me with an idea. Basically just to take one or two of their trials per month. And I just make a skit out of that trial with the idea being to help disseminate some of the research findings that are out there, because I guess it's getting harder and harder for people to actually read, to sit down and read a journal article.

(13:43):

And so, I have to credit them for having this idea and thinking outside the box of a different way to get medical information and knowledge out to the masses. And you're absolutely right, that I have been critical of journals, and particularly I've been critical of the predatory nature of some of the larger journals out there, like Elsevier. I've specifically named Elsevier, Springer, these journals that have a 40% profit margin. And I certainly thought about that whenever I was looking into this partnership. And the reason I was okay with doing it with the New England Journal is because they're a nonprofit, first of all, so they're run by the Massachusetts Medical Society. That's the publisher for that journal. And so, I feel okay partnering with them because I feel like they're doing it in a much better way than some of the bigger journal corporations out there.

Kristin Flanary (14:54):

Well, and also part of the deal that we negotiated was that those articles that you make skits about those will be available open access.

Will Flanary (15:03):

Oh yeah. That was a prerequisite. Yes. It was like, if I'm going to do this, the articles that I'm talking about need to be free and readily available. That's part of it.

Eric Topol (15:14):

I think you've done about five already, something like that. And I watched them, and I just was blown away. I mean, the one that got me where I was just rolling on the floor, this one, the Belantamab Mafodotin for Multiple Myeloma. And when you were going on about the Bortezomib, Dexamethasone. We'll link to this. I said, oh my God.

Will Flanary (15:40):

Yeah. The joke there is, you don't have any idea how long it took me to say those things that quickly. And so, I was writing this skit and I'm like, wouldn't it be funny if somehow that triggered a code stroke in the hospital because this person is saying all these random words that don't have any meaning to anybody. Man, I tell you, I am learning. Why would I ever need to know any of this information as an ophthalmologist? So it's great. I know all this random stuff about multiple myeloma that I probably would never have learned otherwise.

Kristin Flanary (16:21):

It's the only way, you won't read a journal either.

Eric Topol (16:23):

Well, and if you read the comments on the post. These doctors saying, this is the only way they want to get journal information from now on.

Will Flanary (16:33):

Which is double-edged sword, maybe a little bit. Obviously, in a 90 second skit, there's no way I'm going to cover the ins and outs of a major trial. So it's really, in a lot of ways, it's basically like, I call it a comedy abstract. I’m not going much further than an abstract, but hopefully people that are actually interested in the topic can have their interest piqued and want to read more about it. That's kind of the idea.

Eric Topol (17:06):

Yeah. Well, they're phenomenal. We'll link to them. People will enjoy them. I know, because I sure did. And tenecteplase for stroke and all that you've done. Oh, they're just phenomenal.

Will Flanary (17:20):

Every two weeks we come out with a new one.

Eric Topol (17:24):

And that is basically between the fact that you are now on the commencement circuit of the top medical schools and doing New England Journal videos on their articles. You've crossed a line from just making fun of insurance companies and doctors of specialties.

Kristin Flanary (17:44):

Oh, he has crossed many lines, Dr. Topol.

Eric Topol (17:46):

Yeah. Oh yeah. Now you've done it, really. Back two years ago when we convened, actually it's almost three, but you said, when's it going to be your Netflix special?

Will Flanary (18:02):

Oh, gosh.

Eric Topol (18:02):

Is that in the works now?

Will Flanary (18:04):

Well, I'll tell you what's in the works now.

Kristin Flanary (18:06):

Do you know anyone at Netflix?

Will Flanary (18:09):

A New Animated Series

No. We're working on an animated series.

Eric Topol (18:12):

Oh, wow. Wow.

Will Flanary (18:13):

Yeah. All these characters. It's basically just this fictional hospital and all these characters are very cartoonish, the emergency physician that wears the bike helmet and everything. So it's like, well, what do we have together? What do we, Kristin and I have time for? And it wasn't like moving to LA and trying to make a live action with actors and do all, which is something we probably could have tried to do. So instead, we were like, let's just do an animated series.

Kristin Flanary (18:48):

Let's have someone else do the work and draw us.

Will Flanary (18:51):

So we've worked with a writer for the first time, which was a fun process, and putting together a few scripts and then also an animator. We learned a lot about that process. Kristin and I are doing the voiceovers. And yeah, it's in process.

Kristin Flanary (19:10):

We're the only actors we could afford.

Will Flanary (19:12):

Right, exactly.

Eric Topol (19:13):

I can't wait to see it. Now when will it get out there?

Will Flanary (19:17):

Well, we're hoping to be able to put it out on our YouTube channel sometime early next year. So January, February, somewhere around there. And then we can't fund the whole thing ourselves. So the idea is that we do this, we do this pilot episode, and then we'll see what kind of interest we can generate.

Eric Topol (19:37):

Well, there will be interest. I am absolutely assured of that. Wow.

Will Flanary (19:42):

Let us know if you know anybody at the Cartoon Network.

Kristin and Will Flanary (19:45):

Yeah, we're open to possibilities. Whatever, Discovery channel. I don't know.

Eric Topol (19:51):

You've gotten to a point now where you're ready for bigger things even because you're the funniest physician couple in medicine today.

Kristin Flanary (20:05):

Well, that's a very low bar, but thank you.

Will Flanary (20:08):

There are some funny ones out there, but yeah, I appreciate that.

Eric Topol (20:11):

Well, I'm a really big comedy fan. Every night I watch the night before, since I'm old now, but of Colbert and Jimmy Kimmel, just to hear the monologues. Trevor Noah, too. And I can appreciate humor. I'll go to see Sebastian Maniscalco or Jim Gaffigan. That's one of the things I was going to ask you about, because when you do these videos, you don't have an audience.

Will Flanary (20:39):

Oh yeah.

Eric Topol (20:40):

You're making it as opposed to when you are doing your live shows, commencement addresses and things like that. What's the difference when you're trying to be humorous, and you have no audience there?

Will Flanary (20:55):

Well, whenever I'm filming a skit, it's just all production. In fact, I feel like it's funny. I think it's funny, but it's really not until I see the response to it, or I show Kristin, or what I have is where I really know if it's going to work. It's great to put the content out there and see the responses, but there's nothing like live interaction. And that's why I keep coming back to performing. And Kristin's been a performer too in her life. And I think we both really enjoy just the personal interaction, the close interaction, the response from people to our story.

Kristin Flanary (21:36):

We do most of our work alone in this room. I do a lot of writing. He does a lot of playing.

Will Flanary (21:44):

Dress up.

Kristin Flanary (21:44):

All the people in his head, and we do that very isolated. And so, it's very lovely to be able to actually put names to faces or just see human bodies instead of just comments on YouTube.

Will Flanary (21:59):

Meet people.

Kristin Flanary (21:59):

It's really nice.

Will Flanary (22:01):

We’ve been doing meet and greets at the live shows and seeing people come up wearing their costumes.

Eric Topol (22:07):

Oh, wow.

Will Flanary (22:11):

Some of them talk about how they tell us their own stories about their own healthcare and talk about how the videos help them get through certain parts of the pandemic or a difficult time in their life. And so, it reinforces that this means something to a lot of people.

Kristin Flanary (22:29):

It's been really fun for me, and probably you too, but to get to see the joy that he has brought so many people. That's really fun to see in person especially.

Eric Topol (22:42):

No question. Now, when you're producing it together, do you ever just start breaking into laughter because it's you know how funny this is? Or is it just you're on kind of a mission to get it done?

Will Flanary (22:54):

Well, the skits I do by myself. And sometimes when I'm writing out the skit, when I'm writing the skit itself, I will laugh at myself sometimes. Not often, but sometimes they're like, oh, I know that's really funny. I just wrote a skit that I'm actually going to be debuting. I'm speaking at the American Academy of PM&R, so the big PM&R conference. I'm writing a skit, it's How to Ace your PM&R residency interview.

Will Flanary (23:28):

I was writing up that skit today and kind of chuckling to myself. So sometimes that happens, but whenever we do our podcast together, we definitely have outtakes.

Kristin Flanary (23:38):

Oh yeah, we've got some.

Will Flanary (23:40):

We crack each other up.

Kristin Flanary (23:41):

We do.

Will Flanary (23:42):

Sometimes we're getting a little punchy toward the end of the day.

Eric Topol (23:47):

And how is the Knock Knock, Hi! podcast going?

Will Flanary (23:51):

It's awesome. Yeah.

Kristin Flanary (23:52):

Yeah. It's a really fun project.

Will Flanary (23:54):

We still enjoy. You can work with your spouse and in close proximity and still be happily married. So it's doable everyone.

Kristin Flanary (24:06):

That's right. And we're in that phase of life that's really busy. We've got kids, we've got a gazillion jobs. House, my parents are around, and so it's like the only time all week that we actually get to sit down and talk to each other. So it's actually kind of like a part of our marriage at this point.

Will Flanary (24:28):

We’re happy to involve the public in our conversations, but we couldn't do it because we have all these things going on, all our hands and all these little places. We can't do it without a team.

Kristin Flanary (24:41):

Yeah, absolutely.

Will Flanary (24:41):

And that's the thing that I've learned, because I've always been a very loner type content creator. I just wanted to do it all myself. It's in my head and I have trouble telling others, describing what's in my head. And Kristin and our producers have helped me to be able to give a little bit of control to others who are really good at what they do. And that's really the only way that we've been able to venture out into all these different things we've talked about.

Eric Topol (25:12):

Well, I think it comes down to, besides your ability to get to people in terms of their laughter receptors, you have this incisive observer capability. And that's one of the things I don't, I can't fathom because when you can understand the nuances of each specialty or of each part of healthcare, and you haven't necessarily interacted with these specialists or at least in recent years, but you nail it every time. I don't know how you do it, really that observational, is that a central quality of a comedian, you think?

Will Flanary (25:52):

There's definitely a big part of that. You got to get the content from somewhere. But for the specialties, it's really first about just getting the personalities down. And that doesn't change over time.

Kristin Flanary (26:08):

Or around the world.

Will Flanary (26:09):

Or around the world. We hear from people from all over the world about, oh, it's the same in Guatemala as it is in the US.

Kristin Flanary (26:18):

Surgeons are the same.

Will Flanary (26:19):

Yeah.

Kristin Flanary (26:20):

Emergency is the same.

Will Flanary (26:21):

Which has been really cool to see. But so, I draw on my experience interacting with all these specialties back in my med school and intern days. You're right, as an ophthalmologist, we don't get out very much.

Eric Topol (26:33):

No.

Will Flanary (26:35):

So very few people have ever seen an ophthalmologist. We do exist. But then beyond that, I do have to include some actual medical things. And so, I actually, I do a lot of research. I find myself learning more about other fields sometimes than I do in my own field. So especially the further out I get from med school, I know less and less.

Eric Topol (27:00):

Yeah, that's what I was thinking. But you're always spot on. It's interesting to get that global perspective from both of you. Now you're still doing surgery and practicing ophthalmology. Have you reduced it because this has just been taking off so much more over the recent years or keeping it the same?

Will and Kristin Flanary (27:21):

Nope, I’m still. Do you know how many years I had to come along on all of this medical training? He is not allowed to give this up.

Will Flanary (27:29):

I know there's something called a sunk cost fallacy, but this is no fallacy. There's enough of a sunk cost. I got to stick with it. No, I still enjoy it. That's the thing. It actually, it informs my comedy, it grounds me. All of the social media stuff is built upon this medical foundation that I have. And if I stopped practicing, I guess I could maybe cut back. But I'm not planning on doing that. If I stop practicing medicine, I feel like it would make my content less.

Kristin Flanary (28:07):

Authentic.

Will Flanary (28:08):

Less authentic, yeah. That's a good way to put it.

Eric Topol (28:09):

Yeah, no, that makes a lot of sense. That's great you can get that balance with all the things you're doing.

Will Flanary (28:17):

And if I stop practicing medicine, they're not going to invite me to any more commencement addresses, Dr. Topol. So I got to draw the line somewhere.

Eric Topol (28:28):

One of the statements you made at some point earlier was, it was easier to go to become a doctor than to try to be a comedian. And yeah, I mean you proven that.

Will Flanary (28:38):

A lot of ways. That's true.

Eric Topol (28:40):

Wow. I am pretty awestruck about the rarefied talent that you bring and what you both have done for medicine today. And the thing is, you're so young, you have so much time ahead to have an impact.

Will Flanary (28:57):

You hear that Kristin, we're young. Look at that.

Kristin Flanary (29:00):

That's getting less and less true.

Will Flanary (29:01):

Kristin, she just turned 40. It's right around the corner for me. So I don't know.

Will Flanary (29:11):

We got some years left.

Eric Topol (29:12):

You're like young puppies. Are you kidding? You're just getting started. But no, I think that what you brought to medicine in terms of comedy, there's no other entity, no person or people like you have done. And just the last thing I want to ask you about is, you have a platform for advocacy. You've been doing that. We talked about co-survivor. We talked about nurturing the human qualities in physicians like creativity and also taking on the insurance companies, which are just monstrous. I'll link a couple of those, but the brain MRI one or the Texaco.

Will Flanary (29:54):

Texaco Mike.

Eric Topol (29:55):

Yeah, that one is amazing. But there is so many. I mean, you've just taken them apart and they deserve every bit of it. Do you have any other targets for advocacy or does that just kind of come up as things go?

Will Flanary (30:08):

It kind of comes up as things go. There's things I keep harping on. The prior authorization reform, which I've helped in a couple of different states. There's a lot of good people around the country doing really good work on prior authorization and reforming that whole process. And I've been able to just play a small part in that in a couple of different ways. And it's been really fun to do that. And so, I do plan on continuing that crusade as it were. There's certain things I'd like to see. I've been learning more about what pharmacists are dealing with as well as a physician. Unfortunately, we are very separate in a lot of ways and just how we come up in medicine. And so, I have had my eyes opened a lot to what community pharmacists are dealing with. For all the terrible things that we have to deal with as physicians in the healthcare system. Pharmacists have just as much, if not more of the things that they're doing that are threatening their livelihoods. And so, I had love to see some more reform on the PBM side of things, pharmacy benefit managers, Caremark, Optum, all of them. They're causing lots of problems.

Eric Topol (31:24):

I couldn't agree with you more. In fact, I'm going to have Mark Cuban on in a few weeks and we're going to get into that. But the pharmacists get abused by these chains.

Will Flanary (31:33):

Oh, it's bad. It's really bad.

Eric Topol (31:35):

Horrible, horrible. I feel, and every time I am in a drugstore working with one of them, I just think what a tough life they have to deal with.

Will Flanary (31:45):

I guess from an advocacy standpoint, the good news is that there's never a shortage of terrible injustices that are being foisted upon the public and physicians and healthcare workers.

Kristin Flanary (31:59):

Yes. The US healthcare system is ripe for advocacy.

Will Flanary (32:01):

Yes. And that's a lesson that I tell people too, and especially the med students coming up, is like, there's work to be done and get in touch with your state societies and there's always work to be done.

Eric Topol (32:18):

Now you've stayed clear of politics. Totally clear, right?

Will Flanary (32:24):

For the most part, yeah. Yeah. It depends on what you consider politics. It depends on what you consider politics.

Eric Topol (32:32):

It being election day, you haven't made any endorsements.

Will Flanary (32:36):

I haven't. And I don't know. I can only handle so much. I've got my things that I really care about. Of course I'm voting, but I want to talk on the things that I feel like I have the expertise to talk about. And I think there's nothing wrong with that. Everybody can't have an opinion on everything, and it means something. So I am happy to discuss the things that I have expertise about, and I'm always on the side of the patient and wanting to make life better for our patients. And that's the side I'm on.

Kristin Flanary (33:25):

I think also he never comes out and explicitly touches on certain topics, but it's not hard to tell where he falls.

Will Flanary (33:34):

If you really want read into it all.

Kristin Flanary (33:38):

It's not like it's a big secret.

Eric Topol (33:40):

I thought that too. I'm glad you mentioned it, Kristin. But it doesn't come out wide open. But yeah, it's inferred for sure.

Eric Topol (33:49):

I think the point being there is that because you have a reach, I think there's no reach that it has 4 million plus people by your posts and no less the tours and keynotes and everything else. So you could go anywhere but sticking to where you're well grounded, it makes a lot of sense. And anyway, I am going to be staying tuned. This is our two-year checkup. I'm hoping you're going to come to San Diego on your next tour.

Kristin Flanary (34:21):

We're working on 2025 plans.

Will Flanary (34:23):

Oh, we got more shows coming up. And we'll hit up other parts of the country too.

Eric Topol (34:28):

I feel like I got to meet you in person, give you a hug or something. I just feel like I'm missing out there. But it's just a joy to have had a chance to work with you on your podcast. And thanks for coming back on one of mine. There's lots of podcasts out there, but having you and joining you is such fun. So thank you.

Will Flanary (34:54):

This has been great. Thank you for having us.

Kristin Flanary (34:55):

Yeah, thank you.

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