Ground Truths

Azeem Azharis an award-wining entrepreneur and innovator in technology, especially A.I., a member of the editorial board of Harvard Business Review, and an outstanding communicator which makes him a frequent media guest and often featured in The Economist, WSJ, and Financial Times. Exponential View by Azeem Azharis chock full of interesting analyses and podcasts on tech and A.I.

Here’s his summary of our extended and fun discussion

I hope you find our conversation interesting and informative.

A snippet of our conversation below

Transcript of our conversation 8 January 2023, edited for accuracy, with external links

Eric Topol

It’s a pleasure for me to have Liv Boeree as our Ground Truths podcast guest today. I met her at the TED meeting in October dedicated to AI. I think she's one of the most interesting people I’ve met in years and the first time I've ever interviewed a professional poker player who has won world championships and we're going to go through that whole story, so welcome Liv.

Liv Boeree

Thanks for having me, Eric.

Eric Topol

You have an amazing background having been at the University of Manchester in physics and astrophysics. Back around in 2005 you landed into the poker world. Maybe you could help us understand how you went from physics to poker.

From Physics to Poker

Liv Boeree

Ah, yeah. It's a strange story, I graduated as you said in 2005 and I had student debt and needed to get a job I had plans to continue in academia. I wanted to do a masters and then a PhD to work in astrophysics in some way, but I needed to make some money, so I started applying for TV game shows and it was on one of these game shows that I first learned how to play poker. They were looking for beginners and the loose premise of the show was which personality type is best suited for learning the game and even though I didn't win that particular show we were playing for a winner take all prize of £100,000 which was a life changing amount of money had I won it at the time. It was like a light bulb moment just the game and I’ve always been a very competitive person, but poker in particular really spoke to my soul. I always wanted to play in games where it was often considered a boy’s game and I could be a girl beating the boys at their own game. I hadn't played that much cards in particular, but I just loved any game that was very cutthroat which poker certainly is. From that point onwards I was like you know what I'm going to put physics on hold and see if I can make it in this poker world instead and then never really looked back.

Eric Topol

Well, you sure made it in that world. I know you retired back in about 2019, but that was after you won all sorts of world and European championships and beat a lot of men. No less. What were some of the things that that made you such a phenomenal player?

Liv Boeree

The main thing with poker is well the most important ingredient if you really want to make it as a professional is you have to be extremely competitive. I have not met any top pros who don't have that degree of killer instinct when it comes to the game that doesn't mean it means you're competitive in everything else in life, but you have to have a passion for looking someone in the eye, mentally modeling them, thinking how to outwit them and put them into difficult situations within the game and then take pleasure in that. So, there’s a certain personality type that tends to enjoy that. The other key facet is you have to be comfortable with thinking in terms of probability. The cards are shuffled between every hand so there's this inherent degree of randomness. On the scale of pure roulette which is all luck no skill to a game like chess which has almost no luck (close to 100% skill as you can get) poker lies somewhere in the middle and of course the more you play the bigger the skill edge and the smaller the luck factor. That's why professionals can exist. It's a game of both luck and skill which I think is what makes it so interesting because that's what life is really, right? We're trying to get our business off the ground, we're trying to compete in the dating market. Whatever it is. We're doing our strategy, the role of luck life can throw your curved balls that you can do everything right and still things don't go the way you intended them to or vice versa, but there's also strategies we can employ to improve our chances of success. Those are the sort of skills that poker players particularly this idea of gray scale probabilistic thinking that you really have to hone. I've always wondered whether having a background in science or at least you know studying having ah a scientific degree helped in that regard because of course the scientific method is about understanding variables and minimizing uncertainty as much as possible and understanding what cofounding factors can bias the outcome of your results. Again, that's always going on in a poker player's mind, you'll have concurrent hypotheses. Oh, this guy just made a huge bet into me when that ace came out, is it because he actually has an ace or is it because he's pretending to have an ace and so you've got to weigh all the bits of information up as unbiased as possible in an unbiased way as possible to come to a correct conclusion. Even then you can never be certain, so this idea of understanding biases understanding probabilities I think that’s why a lot of top poker players have backgrounds in scientific degrees a very good friend of mine he had a PhD in in physics. Especially over time poker has become a much more sort of scientific pursuit. When I first allowed to play it was very much a game of street smarts and intuition in part because we didn't have the technological tools to understand really the mechanics of the game as well. You couldn't record all your playing data if you were playing just in a casino unless you were writing down your hands. Otherwise, this information wasn't getting stored anywhere, but then online poker came along which meant that you could store all this data on your laptop and then build tools to analyze that data and so the game became a much more technical scientific pursuit.

Eric Topol

That actually gets to kind of the human side of poker. Not the online version —especially since we're going to be mainly talking about AI the term “poker face” the ability to bluff is that a big part of this?

Liv Boeree

Oh, absolutely. You can't be a good poker player if you don't ever bluff because your opponents will start to notice that so that means you're only ever putting your money on the line when you have a good hand so why would they ever pay you off. The point of poker is to maximize the deception to your opponents so you have to use strategies where some of the time you might be having a strong hand and some of the time you might be bluffing where you might have a weak hand. The key is this is getting into the technical sort of game theory side of it, but you want to be doing these bluffs versus what we call value bets as in betting with a good hand with the right to sort of frequency. You need these right ratios between them, so bluffing is a very core part of the game and yes having a poker face obviously helps because you want to be as inscrutable to your opponents as possible. At the same time online poker is an enormously popular game where you can't see your opponent's faces.

Eric Topol

Right, right.

Liv Boeree

Yet you can still bluff which could actually lead us into this topic of AI because now the best players in the world are actually AIs.

Eric Topol

Well, it's interesting because it takes out that human component of being able to bluff and it may be good for people who don't have a poker face. They can play online poker and be good at it because they don't have that disguise if you will.

Liv Boeree

Right.

Game Theory and Moloch Traps

Eric Topol

That gets me to game theory and a big part of the talk you gave at the TED conference about something that I think a lot of the folks listening aren't familiar with— Moloch traps. Could you enlighten us about that because what the talk which of course we’ll link to is so illuminating and apropos to the AI landscape that we face today?

Liv Boeree

Yeah, I’ll leave it for people to go and watch the TED talk because that's going to be much more succinct than me to explain the backstory of how it came to be called a Moloch trap because Moloch is a sort of biblical figure a demon and it seems strange that you would be applying such a concept to …

The science to advance our understanding of the aging process—and to potentially slow it down—has made important strides. One of the leading scientists responsible for this work is Professor Tony Wyss-Coray, whose work has particularly focused on brain aging but has implications for all organs. I believe his December 2023 Nature paper on blood proteins that can track aging for 11 of our organs is one of the most important aging reports yet.

Here is the audio and transcript of our conversation, recorded 20 December 2023, with a few relevant external links.

This is the last Ground Truths post for 2023 and I hope you’ll find it informative. I look forward to sharing many more exciting, cutting-edge biomedical advances with you in 2024!

00:10.38

Eric Topol

Hello this is Eric Topol and for this edition of Ground Truths. I'm so delighted to have with me Professor Tony Wyss-Coray of Stanford, a Distinguished Professor at Stanford and who directs the Knight Initiative for Brain Resilience. So welcome Tony.

00:30.19

Tony Wyss-Coray

Thank you, thank you for having me, Eric.

00:32.84

Eric Topol

Well, I've been following your career and your work for decades I have to say and what you just published a couple weeks ago in Nature. The cover paper about internal organ clocks. It blew me away. I mean it's a built on a foundation of extraordinary work. I thought we could start with that because to me that's really a breakthrough in that when we think of aging and how to gauge a person aging with things like the Horvath clock of methylation markers or telomeres or —not at all specific to any part of the body, just overall, l but you published an extraordinary work about plasma proteins for 11 organs that predicted the outcomes things like heart failure and Alzheimer's so maybe you could tell us about this.  Seems to be a big deal to me.

01:28.41

Tony Wyss-Coray

Thank you so much I'm honored. Really, you know I think if you work on this stuff, especially for several years it feels sort of obvious to do it? But I think you know it is in a way. It is. Pretty simple. So what we argued is that the thousands of proteins that you know are present in our blood. They must originate from somewhere now a lot of proteins are you know, produced by cells throughout the body. But some proteins are very specifically produced. For example, only in the brain or only in the liver or only in the heart because they have specialized functions and we have you know being taking advantage of that in clinical medicine where you measure. Often you know one of these proteins to sort of diagnose pathology in a tissue, but we took this It's just a level further and said, well, let's just find out of thousands of proteins that we can measure assign them to specific organs and tissues. And then see whether they change with age and many of them turn out to change. We found you know about 1500 proteins or so in the study that we did although that number can grow dramatically if we you know keep.

03:01.11

Tony Wyss-Coray

Improving our technologies or techniques to measure them and many of them come from the brain or from other tissues and because they change with age. They tell us something about the aging of that organ. And as others have shown in the field including Steve Horvath is that that prediction of the age if it doesn't really match exactly your actual age contains information about the state the physiological state or the risk to develop. Organ-specific disease.

03:37.75

Eric Topol

Right. And you found that about 1 in 5 people had evidence of accelerated aging of 1 organ which of course is really starting to nail down ability to detect aging you know to localize it and um. What strikes me Tony is that now because we're seeing at the cusp of advancing in the science of aging a field that you have done so much to propel forward and one of the issues has been well, how are we going to prove it. We can't wait for 20 years to show that. Whatever intervention led to promotion of healthy aging. But when you have a marker like this of organ specificity, it seems like the chances of being able to show that intervention makes a difference is enhanced would you say so?

04:29.28

Tony Wyss-Coray

Yeah, absolutely I think that's one of the most exciting aspects of this that we can now start looking at interventions whether they are you know a specific intervention that tries to target the aging process, or you know just that. Let's say a cholesterol lowering drug or blood pressure lowering drug does that have a beneficial effect on the heart. For example, on the kidney or you can also start thinking of lifestyle interventions where they actually have an effect right? If you started exercising you collect your blood before and then a year after you have an exercise regimen does that actually change the age that we can measure with these different clocks.

05:22.55

Eric Topol

Right? Well I mean it's really a striking advance and by a marker of aging so that gets me to your other work. You've done well over 10 years which is that you could identify that given young blood. First of course in mice and then later verified in people could improve cognitive function in older whether it's experimental models or in people. So what are your thoughts about that is that if that's something you've been ruminating on for many years and I’m sure there are places around the world that are trying to do this sort of thing. What do you think of that potential?

06:11.40

Tony Wyss-Coray

Yeah, so there really this recent observation or study really came out of you know that finding that young blood can change the age of different organs and you know we. We were not the first to show this. We showed it for the brain but Tom Rando who studied muscle stem cell aging showed this you know a few years earlier in the muscle and we worked with Tom to explore this for the brain, but it shows sort of that this you know the composition of the blood. It is really not just reflecting the age of organs and tissues. But it actually also affects them. It directs them in a way and so you can speculate that you know if you had an organ that shows accelerated aging. Because some of the factors end up in the blood. They might actually induce aging in other tissues and so promote the aging process and people in the field have also shown that this is true for specific cells. We call them senescence cells. So these are a specific type of cell that seem to somehow stop dividing and assume the state that releases inflammatory factors these cells too. They seem to almost infect the neighborhood where they live in with an age promoting sort of.

07:41.95

Tony Wyss-Coray

The secretome , as we call it, so they release factors that seem to promote aging locally but potentially across the organism and interfering in that could potentially have rejuvenating effects and so that brings us back to this observation that.

08:01.23

Tony Wyss-Coray

Young blood could potentially rejuvenate organs We know old blood can accelerate it at least in mice. So could we neutralize the age promoting factors in people and could we deliver sort of the rejuvenating factors. Now what's been frustrating for me is that it has been incredibly challenging to identify the key factors.

08:33.30

Tony Wyss-Coray

I think we became to realize as a field that there is not 1 factor. There's not 1 magic factor that will keep us young or keep our organs young but rather different cells and different organs in our body seem to respond in different ways actually to this young blood. Can show this with molecular tools. We can show that every cell actually responds. So if you take a mouse an old mouse and you give it young blood every cell in that mouse shows a transcription of the response to the young blood.

09:10.80

Tony Wyss-Coray

Some of them may regenerate mitochondria and others activate other pathways. We see that stem cells respond particularly well the stem cells of the Immune system hematopoietic stem cells um while other cell…

David Liu is an gifted molecular biologist and chemist who has pioneered major refinements in how we are and will be doing genome editing in the future, validating the methods in multiple experimental models, and establishing multiple companies to accelerate their progress.

The interview that follows here highlights why those refinements beyond the CRISPR Cas9 nuclease (used for sickle cell disease) are vital, how we can achieve better delivery of editing packages into cells, ethical dilemmas, and a future of somatic (body) cell genome editing that is in some ways is up to our imagination, because of its breadth, over the many years ahead.

Recorded 29 November 2023 (knowing the FDA approval for sickle cell disease was imminent)

Annotated with figures, external links to promote understanding, highlights in bold or italics, along with audio links (underlined)

Eric Topol (00:11):

Hello, this is Eric Topol with Ground Truths and I'm so thrilled to have David Liu with me today from the Broad Institute, Harvard, and an HHMI Investigator. David was here visiting at Scripps Research in the spring, gave an incredible talk which I'll put a link to. We're not going to try to go over all that stuff today, but what a time to be able to get to talk with you about what's happening, David. So welcome.

David Liu (00:36):

Thank you, and I'm honored to be here.

Eric Topol (00:39):

Well, the recent UK approval (November 16, 2023) of the first genome editing after all the years that you put into this, along with many other colleagues around the world, is pretty extraordinary. Maybe you can just give us a sense of that threshold that's crossed with the sickle cell and beta thalassemia also imminently [FDA approval granted for sickle-cell on 8 December 2023] likely to be getting that same approval here in the U.S.

David Liu (01:05):

Right? I mean, it is a huge moment for the field, for science, for medicine. And just to be clear and to give credit where credit is due, I had nothing to do with the discovery or development of CRISPR Cas9 as a therapeutic, which is what this initial gene editing CRISPR drug is. But of course, the field has built on the work of many scientists with respect to CRISPR Cas9, including Emmanuel Charpentier and Jennifer Doudna and George Church and Feng Zhang and many, many others. But it is, I think surprisingly rapid milestone in a long decade’s old effort to begin to take some control over our genetic features by changing DNA sequences of our choosing into sequences that we believe will offer some therapeutic benefit. So this initial drug is the CRISPR Therapeutics /Vertex drug.

Now we can say it's actually a drug approved drug, which is a Crispr Cas9 nuclease programmed to cut a DNA sequence that is involved in silencing fetal hemoglobin genes. And as you know, when you cut DNA, you primarily disrupt the sequence that you cut. And so if you disrupt the DNA sequence that is required for silencing your backup fetal hemoglobin genes, then they can reawaken and serve as a way to compensate for adult hemoglobin genes like the defective sickle cell alleles that sickle cell anemia patients have. And so that's the scientific basis of this initial drug.

Eric Topol (03:12):

So as you aptly put— frame this—this is an outgrowth of about a decade's work and it was using a somewhat constrained, rudimentary form of editing. And your work has taken this field considerably further with base and prime editing whereby you're not just making a double strand cut, you're doing nicks, and maybe you can help us understand this next phase where you have more ways you can intervene in the genome than was possible through the original Cas9 nucleases.

David Liu (03:53):

Right? So gene editing is actually a several decades old field. It just didn't quite become as popular as it is now until the discovery of CRISPR nucleases, which are just much easier to reprogram than the previous programmable zinc finger or tail nucleases, for example. So the first class of gene editing agents are all nuclease enzymes, meaning enzymes that take a piece of DNA chromosome and literally cut it breaking the DNA double helix and cutting the chromosome into two pieces. So when the cell sees that double strand DNA break, it responds by trying to get the broken ends of the chromosome back together. And we think that most of the time, maybe 90% of the time that end joining is perfect, it just regenerates the starting sequence. But if it regenerates the starting sequence perfectly and the nuclease is still around, then it can just cut the rejoin sequence again.

(04:56):

So this cycle of cutting and rejoining and cutting and rejoining continues over and over until the rejoining makes the mistake that changes the DNA sequence at the cut site because when those mistakes accumulate to a point that the nuclease no longer recognizes the altered sequence, then it's a dead end product. That's how you end up with these disrupted genes that result from cutting a target DNA sequence with a nuclease like Crispr Cas9. So Crispr Cas9 and other nucleases are very useful for disrupting genes, but one of their biggest downsides is in the cells that are most relevant to medicine, to human therapy like the cells that are in your body right now, you can't really control the sequence of DNA that comes out of this process when you cut a DNA double helix inside of a human cell and allow this cutting and rejoining process to take place over and over again until you get these mistakes.

(06:03):

Those mistakes are generally mixtures of insertions and deletions that we can't control. They are usually disruptive to a gene. So that can be very useful when you're trying to disrupt the function of a gene like the genes that are involved in silencing fetal hemoglobin. But if you want to precisely fix a mutation that causes a genetic disease and convert it, for example, back into a healthy DNA sequence, that's very hard to do in a patient using DNA cutting scissors because the scissors themselves of course don't include any information that allows you to control what sequence comes out of that repair process. You can add a DNA template to this cutting process in a process called HDR or Homology Directed Repair (figure below from the Wang and Doudna 10-year Science review), and sometimes that template will end up replacing the DNA sequence around the cut site. But unfortunately, we now know that that HDR process is very inefficient in most of the types of cells that are relevant for human therapy.

(07:12):

And that explains why if you look at the 50 plus nuclease gene editing clinical trials that are underway or have taken place, all but one use nucleases for gene disruption rather than for gene correction. And so that's really what inspired us to develop base editing in 2016 and then prime editing in 2019. These are methods that allow you to change a DNA sequence of your choosing into a different sequence of your choosing, where you get to specify the sequence that comes out of the editing process. And that means you can, for the first time in a general way, programmable change a DNA sequence, a mutation that causes a genetic disease, for example, into a healthy sequence back into the normal, the so-called wild type sequence, for example. So base editors work by actually performing chemistry on an individual DNA base, rearranging the atoms of that base to become a different base.

(08:22):

So base editors can efficiently and robustly change A's into G's G's, into A's T's into C's or C's into T's. Those four changes. And those four changes for interesting biochemical reasons turn out to be four of the most common ways that our DNA mutates to cause disease. So base editors can be used and have been used in animals and now in six clinical trials to treat a wide variety of diseases, high cholesterol and sickle cell disease, and T-cell leukemia for example. And then in prime editors we developed a few years…

This is one of the most enthralling and fun interviews I’ve ever done (in 2 decades of doing them) and I hope that you’ll find it stimulating and provocative. If you did, please share with your network.

And thanks for listening, reading, and subscribing to Ground Truths.

Recorded 4 December 2023

Transcript below with external links to relevant material along with links to the audio

ERIC TOPOL (00:00):

This is for me a real delight to have the chance to have a conversation with Geoffrey Hinton. I followed his work for years, but this is the first time we've actually had a chance to meet. And so this is for me, one of the real highlights of our Ground Truths podcast. So welcome Geoff.

GEOFFREY HINTON (00:21):

Thank you very much. It's a real opportunity for me too. You're an expert in one area. I'm an expert in another and it's great to meet up.

ERIC TOPOL (00:29):

Well, this is a real point of conversion if there ever was one. And I guess maybe I'd start off with, you've been in the news a lot lately, of course, but what piqued my interest to connect with you was your interview on 60 Minutes with Scott Pelley. You said: “An obvious area where there's huge benefits is healthcare. AI is already comparable with radiologists understanding what's going on in medical images. It's going to be very good at designing drugs. It already is designing drugs. So that's an area where it's almost entirely going to do good. I like that area.”

I love that quote Geoff, and I thought maybe we could start with that.

GEOFFREY HINTON (01:14):

Yeah. Back in 2012, one of my graduate students called George Dahl who did speech recognition in 2009, made a big difference there. Entered a competition by Merck Frost to predict how well particular chemicals would bind to something. He knew nothing about the science of it. All he had was a few thousand descriptors of each of these chemicals and 15 targets that things might bind to. And he used the same network as we used for speech recognition. So he treated the 2000 descriptors of chemicals as if they were things in a spectrogram for speech. And he won the competition. And after he'd won the competition, he wasn't allowed to collect the $20,000 prize until he told Merck how he did it. And one of their questions was, what qsar did you use? So, he said, what's qsar? Now qsar is a field, it has a journal, it's had a conference, it's been going for many years, and it's the field of quantitative structural activity relationships. And that's the field that tries to predict whether some chemical is going to bind to something. And basically he'd wiped out that field without knowing its name.

ERIC TOPOL (02:46):

Well, it's striking how healthcare, medicine, life science has had somewhat of a separate path in recent AI with transformer models and also going back of course to the phenomenal work you did with the era of bringing in deep learning and deep neural networks. But I guess what I thought I'd start with here with that healthcare may have a special edge versus its use in other areas because, of course, there's concerns which you and others have raised regarding safety, the potential, not just hallucinations and confabulation of course a better term or the negative consequences of where AI is headed. But would you say that the medical life science AlphaFold2 is another example of from your colleagues Demis Hassabis and others at Google DeepMind where this is something that has a much more optimistic look?

GEOFFREY HINTON (04:00):

Absolutely. I mean, I always pivot to medicine as an example of all the good it can do because almost everything it's going to do there is going to be good. There are some bad uses like trying to figure out who to not insure, but they're relatively limited almost certainly it's going to be extremely helpful. We're going to have a family doctor who's seen a hundred million patients and they're going to be a much better family doctor.

ERIC TOPOL (04:27):

Well, that's really an important note. And that gets us to a paper preprint that was just published yesterday, on arXiv, which interestingly isn't usually the one that publishes a lot of medical preprints, but it was done by folks at Google who later informed me was a model large language model that hadn't yet been publicized. They wouldn't disclose the name and it wasn't MedPaLM2. But nonetheless, it was a very unique study because it randomized their LLM in 20 internists with about nine years of experience in medical practice for answering over 300 clinical pathologic conferences of the New England Journal. These are the case reports where the master clinician is brought in to try to come up with a differential diagnosis. And the striking thing on that report, which is perhaps the best yet about medical diagnoses, and it gets back Geoff to your hundred million visits, is that the LLM exceeded the clinicians in this randomized study for coming up with a differential diagnosis. I wonder what your thoughts are on this.

GEOFFREY HINTON (05:59):

So in 2016, I made a daring and incorrect prediction was that within five years, the neural nets were going to be better than radiologists that interpreting medical scans, it was sometimes taken out of context. I meant it for interpreting medical scans, not for doing everything a radiologist does, and I was wrong about that. But at the present time, they're comparable. This is like seven years later. They're comparable with radiologists for many different kinds of medical scans. And I believe that in 10 years they'll be routinely used to give a second opinion and maybe in 15 years they'll be so good at giving second opinions that the doctor's opinion will be the second one. And so I think I was off by about a factor of three, but I'm still convinced I was completely right in the long term.

(06:55):

So this paper that you're referring to, there are actually two people from the Toronto Google Lab as authors of that paper. And like you say, it was based on the large language PaLM2 model that was then fine-tuned. It was fine-tuned slightly differently from MedPaLM2  I believe, but the LLM [large language model] by themselves seemed to be better than the internists. But what was more interesting was the LLMs when used by the internists made the internists much better. If I remember right, they were like 15% better when they used the LLMs and only 8% better when they used Google search and the medical literature. So certainly the case that as a second opinion, they're really already extremely useful.

ERIC TOPOL (07:48):

It gets again, to your point about that corpus of knowledge that is incorporated in the LLM is providing a differential diagnosis that might not come to the mind of the physician. And this is of course the edge of having ingested so much and being able to play back those possibilities and the differential diagnosis. If it isn't in your list, it's certainly not going to be your final diagnosis. I do want to get back to the radiologist because we're talking just after the annual massive Chicago Radiologic Society of North America RSNA meeting. And at those meetings, I wasn't there, but talking to my radiology colleagues, they say that your projection is already happening. Now that is the ability to not just read, make the report. I mean the whole works. So it may not have been five years when you said that, which is one of the most frequent quotes in all of AI and medicine of course, as you probably know, but it's approximating your prognosis. Even now

GEOFFREY HINTON (09:02):

I've learned one thing about medicine, which is just like other academics, doctors have egos and saying this stuff is going to replace them is not the right move. The right move is to say it's going to be very good at giving second opinions, but the doctor's still going to be in charge. And that's clearly the way to sell things. And that's fine, just I actually believe that after a while of that, you'll be listening to the AI system, not the doctors. And of course the…

“A.I. is not the problem; it’s the solution.”—Andrew Ng at TED, 17 October 2023

Recorded 21 November 2023

Transcript with relevant links and links to audio file

Eric Topol (00:00):

Hello, it's Eric Topol with Ground Truths, and I'm really delighted to have with me Andrew Ng, who is a giant in AI who I've gotten to know over the years and have the highest regard. So Andrew, welcome.

Andrew Ng (00:14):

 Hey, thanks Eric. It's always a pleasure to see you.

Eric Topol (00:16):

Yeah, we've had some intersections in multiple areas of AI. The one I wanted to start with is that you've had some direct healthcare nurturing and we've had the pleasure of working with Woebot Health, particularly with Alison Darcy, where the AI chatbot has been tested in randomized trials to help people with depression and anxiety. And, of course, that was a chatbot in the pre-transformer or pre-LLM era. I wonder if you could just comment about that as well as your outlook for current AI models in healthcare.

Andrew Ng (01:05):

So Alyson Darcy is brilliant. It's been such a privilege to work with her over the years. One of the exciting things about AI is a general purpose technology. It's not useful for one thing. And I think in healthcare and more broadly across the world, we're seeing many creative people use AI for many different applications. So I was in Singapore a couple months ago and I was chatting with some folks, Dean Chang and one of his doctors, Dr. M, about how they're using AI to read EHRs in a hospital in Singapore to try to estimate how long a patient's going to be in the hospital because of pneumonia or something. And it was actually triggering helpful for conversations where a doctor say, oh, I think this patient will be in for three days, but the AI says no, I'm guessing 15 days. And this triggers a conversation where the doctor takes a more careful look. And I thought that was incredible. So all around the world, many innovators everywhere, finding very creative ways to apply AI to lots of different problems. I think that's super exciting.

Eric Topol (02:06):

Oh, it's extraordinary to me. I think Geoff Hinton has thought that the most important application of current AI is in the healthcare/ medical sphere. But I think that the range here is quite extraordinary. And one of the other things that you've been into for all these years with Coursera starting that and all the courses for deep learning.AI —the democratization of knowledge and education in AI. Since this is something like all patients would want to look up on whatever GPT-X about their symptoms different than of course a current Google search. What's your sense about the ability to use generative AI in this way?

Andrew Ng (02:59):

I think that instead of seeing a doctor as a large language model, what's up with my symptoms, people are definitely doing it. And there have been anecdotes of this maybe saving a few people's lives even. And I think in the United States we're privileged to have some would say terrible, but certainly better than many other country’s healthcare system. And I feel like a lot of the early go-to market for AI enabled healthcare may end up being in countries or just places with less access to doctors. The definitely countries where you can either decide do you want to go see if someone falls sick? You can either send your kid to a doctor or you can have your family eat for the next two weeks, pick one. So with families made these impossible decisions, I wish we could give everyone in the world access to a great doctor and sometimes the alternatives that people face are pretty harsh. I think any hope, even the very imperfect hope of LLM, I know it sounds terrible, it will hallucinate, it will give bad medical advice sometimes, but is that better than no medical advice? I think there's really some tough ethical questions are being debated around the world right now.

Eric Topol (04:18):

Those hallucinations or confabulation, won't they get better over time?

Andrew Ng (04:24):

Yes, I think LLM technology is advanced rapidly. They still do hallucinate, they do still mix stuff up, but it turns out that I think people still have an impression of LLM technology from six months ago. But so much has changed in the last six months. So even in the last six months, it is actually much harder now to get an LMM, at least many of the public ones offered by launch companies. It's much harder now compared to six months ago to get it to give you deliberately harmful advice or if you ask it for detailed instructions on how to commit a crime. Six months ago it was actually pretty easy. So that was not good. But now it's actually pretty hard. It's not impossible. And I actually ask LLMs for strange things all the time just to test them. And yes, sometimes I can get them when I really try to do something inappropriate, but it's actually pretty difficult.

(05:13):

But hallucination is just a different thing where LLMs do mix stuff up and you definitely don't want that when it comes to medical advice. So it'll be an interesting balance I think of when should we use web search for trust authoritative sources. So if I have a sprained ankle, hey, let me just find a webpage on trust from a trusted medical authority on how to deal with sprained ankle. But there are also a lot of things where there is no one webpage that just gives me an answer. And then this is an alternative for generating a novel thing that's need to my situation. In non-healthcare cases, this has clearly been very valuable in just the healthcare, given the criticality of human health and human life. I think people are wrestling with some challenging questions, but hallucinations are slowly going down.

Eric Topol (05:59):

Well, hopefully they'll continue to improve on that. And as you pointed out the other guardrails that will help. Now that gets me to a little over a month ago, we were at the TED AI program and you gave the opening talk, which was very inspirational, and you basically challenged the critics of the negativism on AI with three basic issues: amplifying our worst impulses, taking our jobs and wiping out humanity. And it was very compelling and I hope that that will be posted soon. And of course we'll link it, but can you give us a skinny of your antidote to the doomerism about AI?

Andrew Ng (06:46):

Yeah, so I think AI is a very beneficial technology on average. I think it comes down to do we think the world is better off or worse off with more intelligence in it, be it human intelligence or artificial intelligence? And yes, intelligence can be used for nefarious purposes and it has been in history, I think a lot of humanity has progress through humans getting smarter and better trained and more educated. And so I think on average the world is better off with more intelligence in it. And as for AI wiping oiut humanity, I just don't get it. I’ve spoken with some of the people with this concern, but their arguments for how AI could wipe up humanity are so vague that they boil down to it could happen. And I can't prove it won't happen any more than I can prove a negative like that. I can't prove that radio wave is being emitted from earth won't cause aliens to find us and space aliens to wipe us out. But I'm not very alarmed about space aliens, maybe I should be. I don't know. And I find that there are real harms that are being created by the alarmist narrative on AI. One thing that's quite sad was chatting with they're now high school students that are reluctant to enter AI because they heard they could lead to human extinction and they don't want any of that. And that's just tragic that we're causing high school students to make a decision that's bad for themselves and bad for humanity because of really unmerited alarms about human extinction.

Eric Topol (08:24):

Yeah, no question about that. You had, I think a very important quote is “AI is not the problem, it's the solution” during that. And I think that gets us to the recent flap, if you will, with…

If you care about what you eat, you won’t want to miss this conversation! Chris Van Tulleken is an infectious disease physician-scientist in the UK’s National Health Service who has written a deeply researched masterpiece book on food—ULTRA-PROCESSED PEOPLE. It’s not just about these synthetic and artificial UPF substances, that carry many health hazards, but also about our lifestyle and diet, challenging dogma about low carbs/glycemic index and the impact of exercise.

Chris ate an 80% UPF diet for a month with extensive baseline and follow-up assessments including MRI brain scans. He has an identical twin brother who at times is 20 kg heavier than him. Why? What can be done to get limit pervasive UPF ingestion and its multitude of adverse effects on our health?

For additional background to the book, here are some Figures and a Table from a recent BMJ piece by Mathilde Touvier and colleagues.

Consumption of UPFs are highest in the USA and UK

A Table summarizing some of the health hazards and magnitude of increased risk

In his book Chris gets into the evidence for risks that are much broader than cardio- metabolic, including cancer, dementia, inflammatory bowel disease, and other chronic conditions.

A schematic for how UPFs increase the risk of cardiometabolic diseases

Here is the transcript of our conversation, unedited, with links to the audio podcast.

Recorded October 20, 2023.

Eric Topol (00:00):

It's Eric Topol here with Ground Truths. And what a delight for me to welcome Chris van Tulleken, who has written a masterpiece. It's called Ultra-processed People, and it's actually much more beyond ultra-processed food as I learned. We're going to get into how it covers things like exercise, nutrition in general, all sorts of things. Welcome, Chris.

Christoffer van Tulleken (00:27):

It's such a pleasure to be here. And there's no one I would rather say that about my book than you, so that means a huge amount.

Eric Topol (00:35):

Well, I was kind of blown away, but I have to tell you, and it's probably going to affect my eating behavior and other things as we'll discuss for years to come. You're going to be stuck in my head. So what's interesting, before we get into the thick of it, your background, I mean as a molecular virologist turned into a person that devoted so much to food science, and you go through that in the book, how you basically got into rigorous reviews of papers and demand for high quality science and then somehow you migrated into this area. Maybe you could just give us a little bit of background on that.

Christoffer van Tulleken (01:20):

So I suppose it feels a tenuous thing. I'm an infectious diseases clinician, but the only people who get infections are disadvantaged people. For the most part, rich people well off people get cardiometabolic disease. And so I worked a lot in very low income settings in South Asia and Pakistan in the hills and in Central and West Africa. And the leading cause of death in the kids I was seeing in the infants was the marketing of food companies. So food, particularly formula, but also baby food was being made up with filthy water. And so these children were getting this triple jeopardy where they were having bugs, they were ingesting bugs from filthy water. Their parents were becoming poor because they couldn't afford the food and they lacked the immune system of breast milk in the very young. And so it sort of presented itself, although I was treating infections that the root of the problem was the food companies. And now my work has sort of expanded to understanding that poor diets has overtaken tobacco or it's depending on the number set you look at, but the Lancet Global health data shows that poor diets overtaken tobacco is the leading cause of early death globally. And so we need to start thinking about this problem in terms of the companies that cause it. So that's how I still treat patients with infections, but that was my route into being interested in what we call the commercial determinants of health.

Eric Topol (02:52):

Yeah, well you've really done it. I have 15 pages of highlights and notes that I got from the book and book. I mean, wow. But I guess the summary statement that somebody said to you during the course of the book, because you researched it heavily, not just through articles, but talking to experts that ultra-processed foods is not food, it's an industrial produced edible substance, and really it gets graphic with the bacteria that's slime and anthem gum and I mean all this stuff, I mean everywhere I look, I see. And I mean all these, I mean just amazing stuff. So before we get into the nitty gritty of some of these additives and synthetic crap, you did an experiment and with the great University College in London where you took I guess 80% of your diet for a month of up pfs. So can you tell us about that experiment, what it did for you, what you learned from it?

Christoffer van Tulleken (04:04):

Yeah, so it wasn't just a stunt for the book. I was the first patient in a big study that I'm now running. It's a clinical trial of ultra-processed food. And so I was a way of gathering data. I mean, you know how these things work, Eric. I was teaming up with my neuroscience colleagues to do MRI scans my metabolic colleagues instead of going, look, if we put patients on this diet, how would it all look and what should we be investigating if we do MRI scans, will we see anything? And so I ate various news outlets have portrayed this as kind of me heroically putting my body on the line for science. I ate a completely normal diet for many American adults. About one in five Americans eats the diet of 80% of their calories. It's a very typical diet for a British or an American teenager or young person.

(04:52):

So it wasn't arduous. And I was really looking forward to this diet because like most 45 year old doctors, I have started because of my marriage and my children, you start to eat in a rather healthy way. And this was amazing opportunity to go back to eating the garbage that I'd eaten as a teenager. I was going back to these foods I loved. So I guess there were kind of four things that happened. There were these three physical effects on my body. I gained a huge amount of weight and I wasn't force-feeding myself. And that really chimes with the epidemiological data that we have and from the clinical trial data run by Kevin Hall at the NIH, that this is food that gets around your body's evolved mechanisms that say, stop eating, you're full. Now the second thing that happened is we did some brain scans and I thought, well, the brain scan we're not going to see anything in a month of normal food.

(05:43):

So I switched from about 20% to 80% and we saw enormous changes in connectivity between the habit, automatic behavior bits at the back in the cerebellum and the reward addiction bits in the middle in the limbic system and associated regions. So that was very significant in me. And we did follow-up scans and those changes were robust and we really have no idea what is happening in children who are eating this stuff from birth to their brains, but it's concerning. And then the most intriguing thing was I ate a standard meal at the beginning of the diet and we measured my hormonal response to the food. And I think people are more and more familiar with some of these hormones because we've got drugs like semaglutide or wegovy that are interrupting these fullness or these hunger hormone pathways. And what we saw was that my hunger hormone response to a standard meal, my hunger hormones remain sky high at the end of the diet.

(06:41):

So this is food that is fiddling with your body's ability to say I'm done. But the most amazing thing was that this experience I had where the food became disgusting, there was this moment talking to a friend in Brazil called Fernanda Rabu. She's an incredible scientist, and she was the one who said, it's not food, Chris. It's an industrially produced edible substance. And I sat down…

In July, I reviewed Peter’s Outlive book here in Ground Truths and hoped I’d be able to interview him about my concerns. Here’s that conversation, recorded October 16th. I hope you’ll find it informative and stimulating!

The AI generated transcript (unedited) below with links to the audio recording

Eric Topol (00:01):

Peter, it's really great to see you. I haven't been chance to visit since early 2020, and you introduced me to Topo Chico as a great way to get carbonated water. Are you still into those?

Peter Attia (00:15):

Very much so, yeah. Although I have a different drink today because, well, I don't know why I grabbed for different drinks.

Eric Topol (00:22):

Yeah, well it's kind of amazing. Distinct from the rest of the waters, fizzy waters. At any rate, since that time, that memorable visit we had, you published an incredible book Outlive, and I think it sold more than a million, well over a million copies, which is amazing. So congratulations.

Peter Attia (00:41):

Thank you so much.

Eric Topol (00:42):

It's a great book. And you may have written my review, which I really thought it offers just a great information resource and it must've taken so many years to put it all together.

Peter Attia (00:54):

Yeah, I think it probably took seven years in total.

Eric Topol (00:57):

Well, I think it was well worth, and I think it's helping a lot of people. And in fact, I first became aware of it just because these patients were coming into me and saying, well, that's not what Dr. Attia says, or What do you think of Dr. Attia’s book ? So that's prompted me to give it a really close read, and I learned a lot from all your work. I thought what we'd start off with, I think you framed it really well with this Medicine, 1.0, 2.0, 3.0 and the shift to the right. So maybe you could explain the concept on that. Sure.

Peter Attia (01:34):

So Medicine 1.0 is kind of a placeholder for a time before there really was medicine, or at least before, there was sort of a scientific method and an understanding of science and the natural world around us. But of course, from a timescale perspective, it's what dominated all of our civilization. So humans have been around for 250,000 years and until very, very, very recently on that timescale, we didn't really have the tools intellectually to understand science. So we couldn't understand cause and effect. We didn't have a scientific method, let alone capacity to do experiments. And so most of what we did as far as medicine was based on things that we look back at today and think are completely ridiculous. Illness was brought on by the gods or bad humors or things like that. And really then when we start to think about medicine in the way we think about it today, we're really thinking about Medicine 2.0.

(02:33):

And this is something that was obviously a many, many year transition. Technically I would argue it took place over hundreds of years, beginning with Francis Bacon in the late 17th century or the mid 17th century, but really accelerating in the latter part of the 19th century with germ theory. So we can think about lister, I wrote a little bit about them, and ultimately really a more concrete set of tools including physical tools such as the light microscope, ssid, Muer G writes very elegantly about the importance of the light microscope in the understanding of the cell. And of course a big part of understanding the cell was understanding bacteria, their role in disease. And then we have the advent of antimicrobial agents. So it's this sort of collective set of tools that allow us to basically double without exaggeration human lifespan in a matter of three generations.

(03:31):

So this is kind of a remarkable trajectory. I think it would be surprising for most people to learn, however, that in this doubling of human lifespan about, well, I would say virtually all of it has come through the reduction of and or elimination of infectious diseases and communicable diseases. And none of that has really come, or very little of that has come by addressing chronic diseases. And so as we've now lived longer by not dying due to the sort of usual infant mortality and infectious disease route, we're instead dying of these chronic diseases. And I think Medicine 2.0 has been largely unsuccessful in that arena with perhaps one exception and that exception is vaccination. So vaccination is in some ways a medicine 3.0 tool because it's a tool of prevention, meaning you treat before a person is sick, whereas most of the success of medicine 2.0 is treat once the patient is ill.

(04:39):

And that tool doesn't work for cancer, for dementia, and for atherosclerosis for those diseases, you actually have to treat if you will, long before the patient is sick to prevent or at least delay the onset of. So in some ways that is one of the most important pillars of Medicine 3.0, there are several others. So another very important pillar of it is an equal if not greater focus on health span over lifespan where the description and definition of health span are much more rigorous. So the Medicine 2.0 definition of health span is the period of time in which you are free of disability and disease. I kind of reject that definition is not very helpful because I'm as free of disability and disease today at 50 as I was when I was 20, I'm clearly not in as good a shape, I'm not as strong, I'm not as cardio respiratory fit, I'm not as cognitively sharp. So my health span has already declined. But by focusing on metrics of health span in a very detailed way, we're going to get a lot of lifespan benefits for free. And then there's the component of personalizing medicine. So again, it's a term that is rather glib, but it is kind of true. And so we think of evidence-based medicine as the foundation of medicine 2.0, and I think that evidence-informed medicine needs to be the pinnacle or the pillar of medicine 3.0 for reasons I'm sure we'll discuss.

Eric Topol (06:10):

Yeah. So I buy into the medicine 3.0 concept because we've never fulfilled the fantasy or dream of prevention really as you get to. And the four horsemen that you laid out so well, cancer, neurodegenerative disease, cardiovascular and metabolic dysfunction, all play into that, that we could actually prevent these. One of the questions on that was you shifted to the right better health span, but do you then fall off the cliff that is you have this great health span and you don't have the chronic disease, or do you wind up just basically delaying the chronicity? What are your thoughts about that?

Peter Attia (06:51):

Well, I think what happens is we want to model ourselves after the centenarian. So centenarians on average are living two decades if not a little bit more than the average person, so slightly more than two decades beyond the average person. And interestingly, they kind of die of the same diseases as the rest of us do. They just have a much more compressed period of morbidity, and they have this phase shift in time for the first brush with disease X. So they're going to die pretty quickly of cancer when cancer sets in, they just get cancer 20 years later. On average, their first brush with cardiovascular disease is also 20 to 25 years later. So if you think about cardiovascular disease in non centenarians, 50% of men, as you probably know, and maybe the audience doesn't, but 50% of men who are going to have a major adverse cardiac event will have it before the age of 65 and 33% of women who will have a major adverse cardiac event in their life will have, so before the age of 65 when we're talking about centenarians, they're into their eighties and nineties when they're having their first major adverse cardiac event.

(08:07):

And so in an ideal world, which is a theoretical world, you would square the longevity curve, right? You would have perfection and optimization of health span until you are pick your age, you might say 9,100, and then you die in your sleep sort of thing, or you die while running around the track…

Recorded 11 October 2023

Beyond being a brilliant scientist, Fyodor is an extraordinary communicator as you will hear/see with his automotive metaphors to explain genome editing and gene therapy. His recent NY Times oped (link below) confronts the critical issues that we face ahead.

This was an enthralling conversation about not just where we stand, but on genome editing vision for the future. I hope you enjoy it as much as I did.

Transcript with key links

Eric Topol (00:00):

Well for me, this is really a special conversation with a friend, Professor Fyodor Urnov , someone who I had a chance to work with for several years on genome editing of induced pluripotent stem cells --a joint project while he was the Chief Scientific Officer at Sangamo Therapeutics, one of the pioneering genome editing companies. Before I get into it, I just want to mention a couple of things. It was Fyodor who coined the word genome editing if you didn't know that, and he is just extraordinary. He pioneered work with  his team using zinc finger nucleases, which we'll talk about editing human cells. And his background is he grew up in Moscow. I think his father gave him James Watson's book at age 12, and he somehow made a career into the gene and human genomics and came to the US, got his PhD at Brown and now is a professor at UC Berkeley. So welcome Fyodor.

Fyodor Urnov (01:07):

What an absolute treat to be here and speak with you.

Eric Topol (01:11):

Well, we're going to get into this topic on a day or a week that's been yet another jump forward with the chickens that were made with genome editing to be partially resistant to avian flu. That was yesterday. Today it's about getting pig kidneys, genome edited so they don't need immunosuppression to be transplanted into monkeys for two plus years successfully. And this is just never ending, extraordinary stuff. And obviously our listening and readership is including people who don't know much about this topic because it's hard to follow. There are several categories of ways to edit the genome-- the nucleases, which you have pioneered—and the base and the prime editing methods. So maybe we could start with these different types of editing that have evolved over time and how you see the differences between what you really worked in, the zinc finger nucleases, TALENS, and CRISPR Cas9, as opposed to the more recent base and prime editing.

Fyodor Urnov (02:32):

Yeah, I think a good analogy would be with transportation. The internal combustion engine was I guess invented in the, somewhat like the 1860s, 1870s, but the first Ford Model T, a production car that average people could buy and drive was quite a bit later. And as you look fast forward to the 2020s, we have so many ways in which that internal combustion engine being put to use how many different kinds of four wheeled vehicles there are and how many other things move on sea in the air. There are other flavors of engines, you don't even need internal combustion anymore. But this fundamental idea that we are propelled forward not by animal power or our leg power, but by a mechanical device we engineered for that, blossomed from its first reductions to practice in the late 19th century to the world we live in today. The dream of changing human DNA on demand is actually quite an old one.

(03:31):

We've wanted to change DNA for some time and largely to treat inborn errors of ourselves. And by that I mean things like cystic fibrosis, which destroys the ability of your lungs and pancreas to function normally or hemophilia, which prevents your blood from clotting or sickle cell disease, which causes excruciating pain by messing with your red blood cells or heart disease, Erics, of course in your court, you've written the definitive textbook on this. Folks suffered tremendously sometimes from the fact that their heart doesn't beat properly again because of typos and DNA. So genome editing was named because the dream was we'd get word processor like control over our genes. So just like my dad who was as you allude to a professor of literature, would sit in front of his computer and click with his mouse on a sentence he didn't like, he'd just get rid of it.

(04:25):

We named genome editing because we dreamt of a technology that would ultimately allow us that level of control about over our sequence. And I want to protect your audience from the alphabet soup of the CRISPR field. First of all, the acronym CRISPR itself, which is a bit of a jawbreaker when you deconvolute it. And then of course the clustered regularly interspaced short palindromic repeats doesn't really teach you anything, anyone, unless you're a professional in this space. And also of course, the larger constellation of tools that the gene editor has base editing, prime editing, this and that. And I just want to say one key thing. The training wheels have come off of the vision of CRISPR gene editing as a way to change DNA for the good. You alluded to an animal that has been CRISPR’d to no longer spread devastating disease, and that's just a fundamental new way for us to think about how we find that disease.

(05:25):

The list of people who are waiting for an organ transplant is enormous and growing. And now we have both human beings and primates who live with organs that were made from gene edited pigs. Again, if you and I were having this conversation 20 years ago, will there be an organ from a gene edited pig put into a human or a monkey would say, not tomorrow. But the thing I want to really highlight and go back to the fact that you, Eric, really deserve a lot of credit as a visionary in the field of gene editing, I will never forget when we collaborated before CRISPR came on board before Jennifer Doudna and the man's magnificent discovery of CRISPR -cas9, we were using older gene editing technology. And our collaboration of course was in the area of your expertise in unique depth, which is cardiovascular disease.

(06:17):

And we were able to use these relatively simple tools to change DNA at genes that make us susceptible to heart disease. And you said to me, I will never forget this, Fyodor. What I want to do is I want to cut heart disease out of my genome. And you know what? That's happened. That is happening clinically. Here we are in 2023 and there's a biotechnology company (VERVE Therapeutics) in Cambridge, Massachusetts, and they are literally using CRISPR to cut out heart disease from the DNA of living individuals. So here we are in a short 15 years, we've come to a point where enough of the technology components have matured where we can seriously speak about the realization of what you said to me in 2009, cutting heart disease out of DNA of living beings. Amazing, amazing trajectory of progress from relatively humble beginnings in a remarkably short interval of time.

Eric Topol (07:17):

Well, it's funny, I didn't even remember that well. You really brought it back. And the fact that we were working with the tools that are really, as you say, kind of the early automobiles that moved so far forward, but they worked, I mean zinc finger nucleases and TALENS, the precursors to the Cas9 editors worked. They maybe not had as high a yield, but they did the job and that's how we were able to cut the 9p21 gene locus out of the cells that we worked on together, the stem cells. Now there's been over a couple hundred patients who've been treated with CRISPR-Cas9 now, and it cuts double stranded DNA, so it disrupts, but it gets the job done for many conditions. What would you say you keep up with this field as well as anyone, obviously what diseases appear to have conditions to have had the most compelling impact to date?

Fyodor Urnov (08:35):

So I really love the way you framed this Eric by pointing out the fact that the kind of editing that is on the clinic today is actually relatively straightforward conceptually, which is you take this remarkable molecular machine that came out of bacteria actually and you re-engineer it again, congratul…

Dr. Peter Hotez is a veritable force. He has been the tip of the spear among physicians and scientists for taking on anti-science and has put himself and his family at serious risk.Along with Dr. Maria Bottazzi, he developed the Corbevax Covid vaccine —without a patent— that has already been given to over 10 million people, and was nominated for the Nobel Peace Prize. Here an uninhibited, casual and extended conversation about his career, tangling with the likes of RFK Jr, Joe Rogan, Tucker Carlson, Steve Bannon, and an organized, funded, anti-science mob, along with related topics.

Today is publication day for his new book, The Deadly Rise of Anti-Science.

Transcript (AI generated)

Eric Topol (00:00):

Hello, this is Eric Topol with Ground Truths, and I'm with my friend and colleague who's an extraordinary fellow, Dr. Peter Hotez. He's the founding dean of the National School of Tropical Medicine and University professor at Baylor, also at Texas Children's founding editor of the Public Library Science and Neglected Tropical Disease Journal. and I think this is Peter, your fifth book.

Peter Hotez (00:28):

That's my fifth single author book. That's right, that's right.

Eric Topol (00:32):

Fifth book. So that's pretty amazing. Peter's welcome and it's great to have a chance to have this conversation with you.

Peter Hotez (00:39):

Oh, it's great to be here and great to be with you, Eric, and you know, I've learned so much from you during this pandemic, and my only regret is not getting to know you before the pandemic. My life would've been far richer. And

Peter Hotez (00:53):

I think, I think I first got to really know about you. You were are my medical school, Baylor College of Medicine, awarded you an honorary doctorate, and that's when I began reading about it. Oh. I said, holy cow. Why didn't, why haven't I been with this guy before? So

Eric Topol (01:08):

It's, oh my gosh. So you must have been there that year. And I came to the graduation.

Peter Hotez (01:12):

No, I actually was speaking at another graduation. That's why I couldn't be there, . Ah,

Eric Topol (01:18):

Right. As you typically do. Right. Well, you know, it's kind of amazing to track your career besides, you know, your baccalaureate at Yale and PhD at Rockefeller and MD at Cornell. But you started off, I, I think deep into hookworm. Is that where you kind of got your start?

Peter Hotez (01:36):

Yeah, and I'm still, and I'm still there actually, the hookworm vaccine that I started working on as an MD-PhD student at Rockefeller and Cornell is now in phase 2 clinical trials. Wow. So, which is, I tell people, is about the average timeframe --about 40 years-- is about a, not an unusual timeframe. These parasites are obviously very tough targets. oh man. And then we have AOIs vaccine and clinical trials and a Chagas disease vaccine. That's always been my lifelong passion is making vaccines for these neglected parasitic infections. And the story with Covid was I had a collaboration with Dr. Sarah Lustig at the New York Blood Center, who, when we were working on a river blindness vaccine, and she said, Hey, I want you to meet these two scientists, New York Blood Center. They're working on something called coronaviruses vaccines.

(02:27):

They were making vaccines for severe acute respiratory syndrome and SARS and ultimately MERS. And so we, we plugged their, their, some of their discoveries into our vaccine development machine. And they had found that if you were using the receptor binding domain of the, of the spike protein of SARS and ultimately MERS it produced an equivalent protective immune response neutralizing antibodies without the immune enhancement. And that's what we wrote to the NIT to do. And they supported us with a $6 million grant back in 2012 to make SARS and MERS vaccines. And, and then when Covid 19 hit, when the sequence came online and BioXriv in like early 2020, we just pivoted our program to Covid and, and we were able to hit the ground running and it worked. Everything just clicked and worked really well. And stars aligned and we were then transferred that technology.

(03:26):

We did it with no patent minimizing strings attached to India, Indonesia, Bangladesh. any place that we felt had the ability to scale up and produce it, India went the furthest. They developed it into Corbevax, which has reached 75 million kids in India. And another 10 million as their, for their primary immunization. Another 10 million is adult booster. And then Indonesia developed their own version of our, of our technology called IndoVac. And, and that's also reaching millions of, of people. And now they're using it as a, also as a booster for Pfizer, because I think it may be a superior booster. So it was really exciting to s you know, after working in parasitic disease vaccines, which are tough targets and decades to get it through the clinical trials because the pressure was on to move quickly goes to show you when people prioritize it. And also the fact that I think viruses are more straightforward targets than complex parasites. And well, so that in all about a hundred million doses have been administered and

Eric Topol (04:33):

Yeah, no, it's just a spectacular story, Corbevax and these other named of the vaccine that, that you and Maria Bottazzi put together and without a patent at incredibly low cost and not in the us, which is so remarkable because as we exchanged recently, the us the companies, and that's three Moderna, Pfizer, and Novavax are going to charge well over $110 per booster of the, the new booster updated XBB.1.5. And you've got one that could be $2 or $4 that's,

Peter Hotez (05:11):

And it's getting, so we're making, we're making the XBB recombinant protein booster of ours. And part of it's the technology, you can, you know, it's done through microbial fermentation in yeast, and it's been in a big bioreactor. And it's an older technology that's been around a couple of decades, and there's no limit to the amount you could scale. The yields are really high. So we can do this for two to $3 a dose, and it'd even be less, it wasn't for the cost of the adjuvant. The C P G, the nucleotide is probably the most expensive component, but the antigen is, you know, probably pennies to, to, you know, when you're doing it at that scale. And, and so that, that's really meaningful. I'd like to get our XBB booster into the us It's,

Eric Topol (05:55):

Yeah, it's just no respect from,

Peter Hotez (05:58):

We're not a pharma company, so we don't, we didn't get support from Operation Warp Speed, and so we didn't get any US subsidies for that. And it's just very hard to get on the radar screen of BARDA and those agencies and, 'cause that's, they're all set up to work with pharma companies.

Eric Topol (06:16):

Yeah, I know. It's, it's just not right. And who pays for this is the people, the public, because they, you know, the affordability is going to have a big influence on who gets boosters and is driving

Peter Hotez (06:27):

. Yeah. So, so what I say is we, we provide, you know, the anti-vaccine guys, like the call me a Shill for pharma, not knowing what they're talking about. We've done the opposite, right? We've provided a path that shows you don't need to go to big pharma all the time. And, and so they should be embracing what we're doing. So we, we've, you know, have this new model for how you can get low cost vaccines out there. Not, not to demonize the pharma companies either. They, they do what they do and they do a lot of important innovation. But, but there are other pathways, especially for resource coordination. So we'd love to get this vaccine in, in the us I think it's looking a little work just, just as well, it's, you know, but

Eric Topol (07:12):

You, yeah, I mean, it's not, I don't want ot demonize the vaccine companies either, but to raise the price fivefold just because it's not getting governed subsidy and the billions that have been provided by the government through taxpayer monies. Yea…