On today’s podcast, Cofactor Genomics COO, Dr. David Messina discusses how his company is working to make personalized medicine a reality by focusing on the potential of RNA as a diagnostic tool.

Unlike DNA, which is set in stone at birth, our RNA changes on a minute-by-minute basis and acts as a barometer of our health.

Led by 3 former researchers from The Human Genome Project, Cofactor Genomics is developing a patent-pending RNA-based technology that will allow medical researchers to detect specific RNA molecular markers in even small, low-quality tissue samples. This will make 100 times more patient specimens available for analysis and will open the door to massive, Big Data-style databases for use in both drug and treatment development.

Carter Williams: So, David, the way we normally do this, is we sort of walk through background.

David Messina: Great.

CW: Sort of just, you know … Cofactor is doing some really exciting things and so we’ll spend some time talking about that, but I also love technology and try and understand what’s happening next, I think. In iSelect, we have this opportunity to see cool emerging technology, and when I tell other people, that’s … No, idea, what’s … And, so it’s normal stuff for us –

DM: Right, but, not everybody knows what’s going on.

CW: Not everyone knows what’s going on and it sort of gives them some excitement, so … But, I’m really intrigued about you’re now at Cofactor, right? Part of the founding team. And, I’m sort of intrigued about how you got here, so, how did you become a computational biologist?

DM: You know, I never expected to be, actually, I … When I went into college, I was thinking I would do international law, or maybe political science, and after trying to do that for a couple of years, I realized it wasn’t for me, and I switched gears completely.

And, I was really looking for something 180 degrees different. And I ended up thinking about biology, and I had the opportunity to work with a very talented guy at Argon National Laboratory, a national laboratory just outside of Chicago, who is a mathematician and a computer scientist, originally, and he had met Carl Woese who, kind of one of the pioneers of computational biology.

In 1977, he, Carl Woese, had discovered, or postulated, that there is an entire third domain of life called the Archaea. And, so, you have to think about eukaryotes being multicellular organisms, prokaryotes being bacteria, and he was saying that there’s actually a whole third domain that’s kind of similar, some parts that are multicellular, some parts that are like single-celled organisms.

He predicted this using … looking at RNA molecules, the very early sequencing, that was available at that time. And he looked at enough of them to be able to figure out that there was, in fact, this whole third branch of life. Nobody believed him for a long time. And, it turned out to be true. And, now we know this. This is accepted many years later.

So, Ross Overbeek met Carl and became enamored of applying computational techniques to biology. So, when I met Ross, this was just after a team had published the first free-living … The genome of the first … The first genome sequence of a free-living organism. So, Methanococcus jannaschii, this was done by Craig Venter’s group.

CW: What year was this?

DM: This would have been 1996.

CW: Okay.

DM: And, so, Ross was a unique individual, in that, even at that time, this is when we have one genome … He started thinking about, and we talked about, “Well, what do you do when you have ten genomes, or a hundred genomes, or a thousand? What can you do, in terms of comparative genomics, to better understand the world? So, in a nutshell, you can think about it, where, once you have the whole parts list, that’s what a genome is, really, is how to make an organism. And, once you know what all the genes are, then you can look at two organisms, or two groups of organisms, and say, “The parts that are the same are likely to be fundamental to life.” You know? If they’re all occurring in lots of different organisms. And, the parts that are different, are maybe unique to an organism, explains what is unique about that, or some characteristic about that organism.

So, being able to think about genomics, before genomics had even really started, that was one of those times in life where, I had clarity that this was going to happen and be incredibly interesting and influential area to be in. And, so I had to get into it, and so, that’s really what got me started in genomics.

CW: And so, working with somebody like that that can see the future. Are they just wicked smart and they just can’t explain how they got there? Or, are they clairvoyant, or what would you … What did you see that being present in that phase, what can you tell us about a person like that?

DM: I think it’s a hard question to answer. I think that assembling the information that you have, and thinking logically about the consequences of, and the implications, of that information, can lead to startling insight. You can see things that other people can’t readily see, and so, my assumption is, for somebody like that it takes a certain personality, for sure. But I think it also takes somebody who is open to thinking in those kinds of expansive ways, and really being open to unexpected or startling conclusions.

CW: Challenge the conventionalism.

DM: Yeah.

CW: But I understand the basis really well, and then challenge the conventional end of it.

DM: Yeah, and coming up with hypotheses, and thinking, “Well, okay. Can I test that? Can I … Is that really going to be true? Or, is that true today? Can I test that assumption based on what I know now?”

CW: And is that what computational biology lets you do more of?

DM: I think that’s, absolutely, one of the things that I find so exciting about it. So, what is computational biology? Really, it’s being able to apply computer science, computational techniques, to understand biology. And, that was something that was not really possible in a high throughput or a large-scale way, until very recently. Like I said, the first genome, 20 years ago, and so it’s a very new field.

CW: Yeah, and when the gene … Nobel Prize … For the first Nobel Prize for the gene was, like, in the ’70’s?

DM: Well, so, the techniques that were for mapping and splicing genes, I think, right? Were in the ’70’s. Certainly DNA discovered in 1953, so certainly genetics stretches back, depending on how you count it, back to the beginning of the 20th Century, but really, being able to read the DNA code and by extension RNA, and how genes are expressed inside a cell has come very recently, and so, one gene at a time was really how genetics was conducted until high throughput sequencing became available. Which, really was done on a massive scale, for the first time, during the Human Genome Project. Actually there was a small worm that was sequenced before that. Right? So, so in those days-

CW: What was that worm called, again? I can’t recall.

DM: C. elegans. So, and that was done here at Washington University, also, so in fact, that was, in a sense, to Bob Waterston, one of the architects of the Human Genome Project here at Washington University … There’s one of two places in the world that really led that project. He was a worm biologist, and so, he, I think, was excited about applying the technology first to a worm, and then really seeing where we could take that. In those days, this was still fairly high technology. You were using lasers to read the DNA, but it was very low throughput still, you know, you got a large bench-top machine, you would have what is a very fine, high-quality jello, essentially, that was pressed in between two glass plates. And you have it set up with an anode on one end and a cathode on the other end, so basically like a battery.

So, DNA is negatively charged. And so, if you inject DNA that has been slightly chemically modified, on one end, you can flow it through this gel, this high-quality gel, and then you can have … It separates that out by size, and then you can have a laser hit it and read off each letter of DNA.

And so this was done, we could do in one single run of one of these old machines, maybe 60 – 70 thousand letters of DNA we could read at a time.

And so the Human Genome Project. The human genome is about 3.3 billion letters of DNA, so you can imagine how many gels … How many of those old fashioned sequencing runs were necessary to do it. That’s kind of the story of the project, that it took many thousands of those, over many hundreds of people, over tens of years. And, all the engineers and computational people to analyze the data to assemble that back into the chromosomes, to the-

CW: And so we’re talking, so, just to keep stepping through, so people understand how you got here, so you go into law … Decided not to go into law, in college. University of Illinois, you … As we’re sort of approaching into the ’98 time frame, front edge of the Human Genome Project, you came down for your masters in Computational Biology.

DM: That’s right, so right, it was here in Washington University in St. Louis, so, and actually there’s a little step in between. I was trying to do human genetics, or was doing human genetics at the University of Chicago before the Human Genome was finished. So, in those days, we were … We had a … We were looking at an inherited form of Muscular Dystrophy, so, we had cutting edge technology, we had three generations of this family, and at that time, we were excited. It was a good result to narrow down the location of the causative gene for that disease to about a million letter chunk of the human genome.

So about dozens of genes were in there, and that was-

CW: A needle in the haystack.

DM: Yeah, and that was state-of-the-art in 1997. So, I was really interested in genomics. I looked around for where would be the best place to study that, and out of the 15 or so people in the world who were computational biologists at that time, nine of them were here at Washington University. And, so, pretty easy choice to come here and study with them, and take part in the Human Genome Project.

CW: So, I think something forgotten about the Human Genome Project, I recall I was here in Aerospace at the time, driving around the car, and constantly hearing about, both what was going on here in Cambridge, in terms of human genome. In terms of the core concept, what was going on with human genome projects? What was sort of the main charter?

DM: Yeah, the idea is that if we could determine the parts list, the whole set of genes, and really, the structure, the genome structure itself, that’s the blueprint of life for what makes a human. And, by being able to have that knowledge, we could then start to understand how humans are different and alike from other species. So, understand the function of each and every gene. So, remember, up until that point you’d study a gene at a time, or a small collections of the gene at once. So, if you don’t have the complete set of genes … if you don’t know what all of them are, it’s very hard to know, well, is this … How do the function of different genes overlap? If you … How they interrelate? Whether the pathways where these … the chemical pathways where these genes interact, and so having that information allows us to not only understand the fundamentals of human biology, but also allows us to think about things like eradicating disease and how the human body interacts with disease. And, we’re just getting to see the fruits of that, today. 20 years later.

CW: Today. So, human genome … So, I always imagined the human genome is … Sequencing the human genome is on scale with landing on the Moon.

DM: Yeah, it’s a massive, massive enterprise, and a huge-

CW: I think with a billion dollar underwriting for-

DM: At least a billion dollars, right. And, when I talked about the old technology that was used actually to accomplish the human genome, they knew at the beginning they would have to create new technology, new higher throughput technology to finish that on schedule, and indeed they did.

CW: And you brought up Craig Venter’s name. I recall there was a little bit of … Big government program funded, good. There was an effort between here and the Broad Institute?

David Messina: That’s right.

CW: To go ahead with it. And then Craig Venter said, “Oh, I can do this faster, quicker, cheaper.” So, what was the insight on that?

DM: So, I think the other piece of that was they saw an opportunity to do two things. So, 1) to use all the data, the public, publicly funded, right? So, public data that the Human Genome Project had generated. And, 2) to generate some of their own data and combine those two using a new computational technique for assembling the jigsaw puzzle into a full genome. And, by being able to do that on a private basis, I believe, although, I’m not sure, that their intention was to do private research there at a non-profit institute that would then also identify areas for a commercial enterprise, to be able to build off of that work, so both parties, and what was portrayed as a race to publication for the … between Craig Venter’s group and the public group, both parties were … actually have contributed to our ability to do this stuff today, through the work that the public. Really, the fundamental work that the public side did, and then … And the computational techniques that were introduced by the Venter team are still in use today for assembling genomes, those concepts.

CW: So, we’re sort of in the ’98, the 2000 timeframe. You continued on in the Human Genome Project for a while?

DM: Right. So, I worked as a staff scientist at the Genome Institute, now the McDonnell Genome Institute, here in St. Louis, and there were other genomes to sequence, so we did lots of other organisms, mammals in particular, I worked on the chimpanzee genome and things like this, and we continued to refine the techniques, and it took a really interesting turn in about the mid-2000’s when a new breed of sequencing machines started to appear. Which were much higher throughput than the ones I described earlier. Which allowed us to do a lot more sequencing in a lot less time. And, so, we talk about Moore’s Law with computers, right? Where this idea that every 18 months or so, the amount of power, or really, transistor density that you have per unit doubles. So, you get about twice as much compute speed every 18 months according to Moore’s Law.

So, with these new types of sequencers, these next-gen or massively parallel sequencing machines, the increase in sequencing output per cost over the last ten years, or so, since then, has been faster than Moore’s Law, so actually accelerating faster than what we’ve seen in computers. And we all know how dramatic the difference is in computational power over the last 10 years.

So, think about how impactful that change in just raw sequencing output and capability, what an impact that has in our ability to generate the raw data that we can then analyze to understand not only human biology but actually biology in general.

CW: And so that … We’re going to get to Cofactor, here, in a moment. How’d you go from there to Cofactor?

DM: Right, so like all scientists-

CW: On two levels, from: You’re a scientist in a lab, and Cofactor’s an entrepreneurial operation.

DM: Sure. So-

CW: And then 2) What was the inspiration or technology that sort of led to the point that you said, “Hey, here’s the time to go create a company.”

DM: Sure. So, as a scientist who started in academia, like most of them do-

CW: Why.

DM: Right. Law, and then academia.

CW: I can understand why you went away from law, but –

DM: So, academic science, basic research, the goal is the creation of new knowledge. It’s a very important thing. However, we have been able, I think, to accumulate new knowledge much faster than we had been able to apply that new knowledge. And, to me, this is something that always bothered me. I would … We’d have all these great discoveries but until we can really see a tangible impact from them, you know, they’re not reaching their full potential. And, so, I was really motivated to apply a lot of the amazing research that was going on, and turn that into something, commercialize that into something that would have a real impact on people.

CW: Why do you think that is? There are lots of researchers that go their entire career never having that angst.

DM: I think it’s in part because I think there are plenty of people, and there is already lots of new knowledge being created, so there’s plenty of that already happening, you know, and working on the applied side to trickle more of that through to the end user, if you will, made sense. I think also, from my personality, seeing the tangible outcome or benefit meant more to me than the abstract creation of knowledge.

CW: So, you saw that opportunity to take the next step.

DM: And then for Cofactor, right, so, working at the Genome Institute. Remember there was an army of 300 people, and that’s just with the team in St. Louis, at it’s peak, around that many people working on the human genome. And, really cranking out that sequence. When this new breed of sequencers came out that were much faster in generating a lot more data, we saw the potential of these, and so did everybody else, and an institute like the one we were at was really built around large Federally-funded grants, projects like those, on a large scale. They weren’t set up to meet the needs of a commercial user.

And so when, not only other academic labs started knocking on the door, wanting to take advantage of this new high throughput sequencing technology, but also companies like Pfizer or other PhRMA companies wanted to use it. The Genome Institute was not set up to service those needs, and so that’s a business opportunity.

And so that’s really how Cofactor started, was, you know, we realized we could offer what the Genome Institute was offering, as a commercial enterprise. And, so that’s how the company was born.

Now, fast-forward to today, and we’re really taking what we’ve learned over the course of having worked with some of the largest pharmaceutical companies in the world, over the last several years, in helping them perform their research, we’ve realized that there’s a great opportunity to take what we’ve learned and turn it into more clinical applications and more clinical focus.

CW: So, before we dive into that, the day you left WashU, was it you? You and Jarret? What, I mean, was there a moment of utter and total fear, or was it clear? Or, what was the entrepreneurial emotion going through your mind at that point?

DM: Sure, I remember talking to Jarret about this, because Jarret was really the driving force there, and he had-

CW: Can you describe who Jerret is?

DM: Sure, so Jerret Glasscock, our CEO and Founder, he was faculty. Backstory is that he and I met in 1998. We both came to WashU to study computational biology for the same reason, because it was the place to do it. And, soon after that, we met at the Institute. Our third co-founder, John Armstrong, who’s a brilliant molecular biologist, and leads our research team.

So, I remember talking to Jerret about that moment when he decided to jump ship and he, I think, had that same kind of moment of clarity, where he saw that this was going to work. That this was a good idea. And, so, the risk of doing it didn’t seem like that much of a risk to him because he knew that it would work.

CW: It was riskier not to do it.

DM: Right. That, and I think also, because genomics at that time, and still today, and computational biology, is such a growing field and there’s so much work to be done that even if it didn’t work out, we’d be okay. We’d be able to continue on and find something else to do.

CW: And so you started initially, in a business, supporting PhRMA for something they needed right then.

DM: Right. Exactly.

CW: They needed the best guys that knew the best technology that could operate on a commercial basis, and so-

DM: Yep. And, there weren’t that many people doing it at that time.

CW: So, did you get a PO right away?

DM: Right, so, I think when the company opened its doors-

CW: Did you even know what to write on the PO? Other than the dollar number at the bottom?

DM: Yeah. I think when the company opened its doors, we were lucky to have several months worth of orders already stacked up, so we were cash-flow positive from the beginning. We really didn’t take on any external investment at the beginning.

CW: And at that point it was a bit more of a services business, but at a high bill rate.

DM: Yes.

CW: Higher than a lawyer would charge?

DM: I don’t know if we made it quite that far. That hourly rate is still pretty high, but yes, exactly. We had the expertise both on the molecular side, so taking the genetic material, turning it into a form that the sequencer could read, generating the data, and then doing the computational analysis to make it meaningful. So, we had all those components.

CW: And so, you did that for several years with Cofactor, and you reached a point where you saw an opportunity to go to the next level.

DM: Right so it happened in a couple of phases. So, at the beginning, it was all about DNA sequencing and then a little about RNA sequencing, so, perhaps it’s worth a sidebar on the differences there?

CW: Yes.

DM: So, DNA, we’ve been talking about this, the instruction book for an organism, for a human being if we’re talking about the human genome. And, DNA doesn’t change, really, over the course of your life. The DNA that you have when you’re born is pretty much the same as the DNA that you have today. And, so when we think about disease, what DNA tells you is really gives you an estimate of the chance, the likelihood, that maybe you’ll develop a particular disease or not. For some diseases it’s much more certain, based on your DNA, that you know what’s going to happen. For most diseases, it’s really just more of an estimate, or a probability, that you’ll develop a disease. So, interesting and useful information, yes. But it’s really just giving you a probability or an estimate.

RNA, on the other hand, is not the same as when you were born. RNA is really all of the genes in each cell in your body turned on or off at a given time. And, so RNA can tell you exactly what’s going on at a particular moment. And it can tell you right now whether your body is developing disease, or is … Or, right now whether it’s responding to a treatment. And, so that power, that ability, to see what’s going on inside a cell today, not just an estimate but actually what’s happening is very powerful. And, as we started to do more and more RNA sequencing at Cofactor and working with … We became experts in that and worked with pharma companies around their programs to understand RNA and their clinical programs, we saw an opportunity to really take RNA out of the discovery side, the research side, and into the clinical side, into something that would be even more applied, that would make even more of an impact on people.

CW: Just put some context in the sequencing process, what 23andME now does. You see a TV show and all of a sudden you see these cool new discoveries like 23andME. If you tried to do that same analysis in ’96 or ’98, how long would that have taken?

DM: Oh, right. So, I think 23andME looks at about a million individual locations in out of the 3 billion letters of your DNA, it looks at about a million of them, and they do it on a very specialized chip. Almost like a computer chip where they can put your sample on it and get a read-out on that. 20 years ago, if you were doing it using the old sequencing technology, it would have taken probably at least a year to do that for one person. Actually, the studies that they did and University of Chicago was doing that kind of what we call genotyping, determining somebody’s genetic code, or DNA, at particular spots in the genome. I did … I ran a gel a day, one of these old sequencing gels, a day for a year to get enough information for the people in that small study.

CW: So, you decided to go into a clinical application? And, so tell us what that is.

DM: Right. So, because RNA gives a real time readout of what’s going on inside your body, we realized that there are several opportunities to apply that to medicine, particularly as a diagnostic. And, so, can we help drug developers understand which patients are likely to respond to their drug? Can we help doctors understand which treatment is going to be effective for their patient? Those kinds of questions would have a tremendous impact on our ability to practice medicine today. And, indeed, that’s exactly what we decided to do, and that’s what our products are built around, is helping both drug developers and doctors understand what’s going on in each individual patient, on a personalized or precision basis, rather than treating every patient as the average patient. Which, is how, really, medicine is practiced today. When somebody is treated with a drug, it’s because that’s what works for most people most of the time. And what we’d like to do is help clinicians move to a situation where based on what’s going on in that particular patient’s body that we can see with RNA, they’ll be able to know what is likely to be effective for that patient with that particular disease.

CW: So, they could pick the right drug or treatment to give them? Decide whether they should give them a little or a lot.

DM: That’s right. Exactly. So, you can imagine that today when you’re treating people with what works most of the time for most people, these treatments are in some cases very expensive, and so you put a patient on the drug, you wait a few weeks or a month to see whether it’s working, you’ve not only spent a lot of money, but if it doesn’t work then you’re switching them to another drug, and maybe even have to go to a third drug. And, so, it’s a very expensive and wasteful process, but more often it takes time. Precious time that some of these patients may not have to give, to find the right treatment.

CW: And do you have any sense … It’s a broad question, but if you think through the conventional means of giving somebody a drug and it not working and then the disappointment or whatever the consequence of that, you know, that … whatever, versus the opportunity of being able to tailor these drugs, do you have a sense of what kind of impact that would have?

DM: We think that, well, if you think about how many people come down with cancer every year, so, current estimates are that between the US, UK, and Canada probably 50% of the population will at one time or another have cancer. And, 25% of those will succumb to that cancer. We’re talking about millions of people every year, and as we develop better medications, and as we develop approaches like Cofactor’s to better choose those medications, I would imagine the impact would be enormous. Certainly billions of dollars and countless lives that could be impacted by being able to be more precise about the treatment process.

CW: And, in terms of the treatment level, can you give us an example of where this type of technology has been explicitly used and changed an outcome?

DM: So, one of these motivating stories for us actually happened right here in St. Louis. So, there’s a leukemia researcher at Washington University named Lukas Wartman, and he tragically came down with the very leukemia that he was studying. Being at a world class center for medicine and genomic research, his physicians were able to apply all of the latest techniques to try to find a treatment for him, including DNA sequencing. They sequenced his genome and that was not able to find anything helpful for his treatment. It was only when they went to his RNA that they were able to see that there was a particular gene, which was being turned on way too high, it was over-expressed, that they found an opportunity. There’s actually an already approved FDA approved drug for correcting the over-expression of that gene. They gave Lukas Wartman this drug, and very quickly he responded to it. And, the course of his disease reversed drastically.

And so that was information that, from his RNA, that was able to change the course of his treatment. He was in, probably, the best possible place for being able to have that outcome, at a place where genomic medicine is at the cutting edge here. We want to make sure that everybody has that same opportunity that Lukas Wartman had, to be able to use RNA as a diagnostic tool.

CW: So, it becomes as easy as 23andME?

DM: That’s right.

CW: And at any … at your corner urgent care clinic.

DM: That’s right, and this is … we’re at the beginning of the path, but this is something that we believe will be possible at the very near future.

CW: And, so, what is the future? You’ve got Cofactor. We’re an investor in Cofactor. We’re intrigued with it for all the reasons you have mentioned. You’ve got products coming down that are both clinical products and then a product that helps in the research phase. As you look at your next generation products down the road, or what you’re going to be doing down the road, what will be standard of care using this type of technology five, ten years from now?

DM: Right, so I think it’s an expansion of the same approaches that we’re taking today. So, today the products we have, we have Pinnacle and Paragon. So, Pinnacle is focused for the clinician, for the cancer doctor who is trying to choose the right treatment for the patient. And, so we’re giving them information about that patient’s RNA to do that. And, then we have Paragon, which is giving insight into how the immune system and the tumor are interacting.

And that’s really interesting. I’d love to talk about that some more. So, both of those are right now focused on cancer, particular types of cancer. But, we’ve really built a technology platform that can be applied to many more types of diseases, and indeed, we like to think of it as all of the diseases, which is most of them, that that estimate-

CW: Meaning cancer, neurological, other systems.

DM: Right, Parkinson’s, yeah, exactly. Even heart disease. There are lots and lots of diseases for which, just the estimate that we get from DNA is not enough. And, so we think that the same approaches that we’re applying to cancer today, we’ll be able to apply to other diseases tomorrow.

CW: So, if a gene test has one unit of benefit, RNA has a ten unit benefit.

DM: Yes.

CW: And, right now a clinician is worried about immunotherapy, can use your products to help assist and guide them in their clinical decisions?

DM: Right, so the products in development today are aimed at the clinician, and then also the drug developer and the immuno oncology space, so there’s this tremendous new class of cancer drugs called immunotherapies, which are actually using the bodies own immune system to fight the cancer. And, it’s had a huge impact, already, in our ability to treat cancer, so-

CW: So, Jimmy Carter, in glioblastoma, is an example of-

DM: Exactly.

CW: That was on 60 Minutes, is a good example.

DM: It’s a great example, and what we have seen is that in … For some cancers, what was previously maybe about a 30% survival rate over three to five years is now more like a 60 to 70% survival rate. So, that is a huge, huge impact. Particularly when we talk about cancers that are very common. So, lung cancer, there are about 150 thousand cases a year.

CW: And standard care is more around using DNA to type the treatment?

DM: That’s right. Exactly. So, DNA is being used to help guide those treatments today. So, with those types of opportunities, with our Paragon assay, being able to get much better insight into what’s going on inside the tumor. Is the tumor trying to evade the immune system’s attack? Does the tumor look like it’s particularly susceptible to the type of-

CW: So, you get a much more tactical view of … It’s not just, “Hey, it’s getting bigger or smaller.” But, what other systems are operating to help it get bigger or smaller and reactions and-

DM: Right, and for people who are developing drugs around this, we can even tell them what types of immune cells are infiltrating the tumor, and what amounts, so that information is really helpful in determining not only is the treatment effective but, also, in what way, and for what patients. So, which are the patients that are going to be most likely to respond to that, so, that type of information is essentially not available with as much detail and as broadly today. So, today you might have to run three completely different types of tests. One of them, talking about trying to identify the immune cells that are present. You would really only be able to see if you were working with a biopsy that was fresh out of the operating room. And, very rarely is that possible. And even if it did so, it requires a very technically challenging and expensive.

CW: This is part of the reason we invested, is that there are people sequence RNA, but you guys are fantastic at dealing with more challenge samples that actually in a production environment you’re going to run into other challenges in terms of getting a good sample.

DM: Absolutely.

CW: I mean it seems like a mundane thing, getting a good sample, but it’s critical.

DM: Most people don’t know that most clinical specimens are stored in a preserved way. So, people think back to your high school biology lab, where something’s preserved in formaldehyde, so, think about something preserved like that, but also encased in wax. And, this is done, really, historically, for pathologists, right? So, they put it in this form, so, not only does it preserve the tissue, but it can be sliced off very thinly, stained, and then looked at under a microscope. So, it’s really great for that purpose, but it’s not great at all if you’re trying to extract RNA and DNA from that, and so we’ve been able to combine, not only techniques, which allow us to get really high quality RNA out of those 95% clinical specimens, which are stored in that way, but also, pairing that with sophisticated software, which allows us to interpret that RNA data in a way that’s clinically meaningful.

So, it’s one thing to be able to generate good data. That’s part of the process, but by pairing that molecular process with sophisticated software systems, we’re able to get much more information and much more interpretation to the end user, to the doctor or to the drug developer.

CW: And, so, you’re business is also building at that software to feed into that analysis.

DM: Absolutely. And we’ve really found that controlling the entire process, both the molecular and the software pieces, are essential to getting a good result. A lot of people have thought about trying to approach this problem on one side or the other only, and there’s so much variability in the different techniques that you can apply that, and particularly we talked about the challenges of working with these poor quality, low quality, clinical specimens. You really have to be very thoughtful about which technique you use in the laboratory to extract RNA, and then pairing it with software that expects a particular output, so, a whole integrative process, we’re finding, gives a much cleaner, more sensitive and accurate result.

CW: And, so, what’s ten years out?

DM: So, we are at the very beginning of an incredible era. We look back to the human genome sequence and this new high throughput sequencing technology being 10, 15, 20 years old. Already we’ve seen an impact in our ability to practice medicine today from that.

The clearest way I can explain it, the best analogy I’ve found, is to think about what a personal computer was like in 1987. So, in 1987, it was very primitive by today’s standard. Maybe just a monochrome screen, not even a color screen. Big, heavy, low powered, no internet. Think about the impact that computers have had on our lives over the last 30 years. It’s hard to imagine the countless ways in which our lives are different because of the development of computers over that 30 year period.

So, today, for genomics in particular, for applying RNA to medicine, we’re kind of like at 1987 today with that. So, think about, in the course of the next 10, 20, 30 years, how much of an impact computers had over a 30 year span. The same kind of impact I expect to see from genomics and medicine over the next 30 years. It’s really going to be truly amazing.

CW: And are you the Apple, the Microsoft, the Amazon?

DM: We certainly think that we are moving this forward faster than anybody else. And the great thing is that as we’re pursuing RNA’s potential in medicine, there are lots of other companies doing equally amazing things in other areas. I think about the impact that genomics is having in agriculture and our food supply. That’s going to have a tremendous impact, and it is already on how our daily lives are led. And, so, there are all these multiple fronts in which this technology is being applied that are going to be absolutely incredible.

CW: And this is … I’ll just say, put a plug for St. Louis on this is that the fascinating thing here, is the human genome was done here. The technology is being commercialized here and up in Boston? And, that it flows easily between agriculture and human? And, it’s great because we can take talented people, and just sort of, they can wander back and forth, and have got 20, 30 years of legacy of what it was like in 1998 to do this. What it’s like today. And it sort of gives you a sense of the momentum of the technology.

DM: Absolutely, and we are fortunate sitting here in a city, which has some of the deepest talent pool in this area, and the world, to be able see all that’s happening around us.

CW: So, every startup needs a customer. Even one that’s doing cutting edge work like this. So, is your … Because customers really help you figure out how to reduce a product to practice. Who are you looking for to be your customers, at this point, to help Cofactor reach the next level?

DM: So, today, we’re partnering with clinical researchers and pharmaceutical companies doing some of the most innovative work. Research hospitals, institutions, who are running clinical trials. Really focus on immuno-oncology, who are looking to use our technology to understand better their patients. So, those are the people that we’d love to connect with, to help them understand, to apply this technology, to move their drug development programs faster, to be able to understand the right treatments for their patients. That’s our user base. Those are the people that are helping us develop our products.

CW: So, if a patient, or somebody around a patient is being treated by immunotherapy, tell your clinician? Tell your pharmaceutical company. And, because you get better by getting the pressure from those people to develop better answers for them.

DM: Like every company, we learn best from the people who use and love our products. And, they help us make them better, make the next generation even more effective for them, and so we’re no different. And we have clinical studies underway right now, which are allowing us to get that information from some of the brightest minds in the country and we’re always looking for more people like that who are interested in engaging with us, to learn from them, to help them with the challenges that they’re facing and understanding their patients.

CW: Great. Thank you for your time. We’re going to do this again, because there’s a lot more to talk about. And, we’re not going to do it over 20 years, but over a shorter period of time. But, thank you very much for your time. Thanks for everything you’re doing at Cofactor. We’ve really enjoyed the journey that you’re on. And, glad to be a part of it.

DM: Thank you, Carter.

Dr. Todd Mockler is one of the world’s leading experts on plant genetics and has dedicated his career to better understanding how the genetic code of different types of plants impacts their behavior and responses. As a member and principal investigator with the Danforth Plant Science Center in St. Louis, his research has focused on the development of plant genomic tools, with the end goal of improving crop performance and yield.

On this episode of Innovation Anarchy, Dr. Mockler will discuss his career in plant biology, his work as an ag-tech entrepreneur and helped Benson Hill Biosystems — the startup company where he’s currently chief technology officer — is working to unlock the genetic code of plants in order to improve yields, boost crop performance, and help feed the world.

Carter Williams: As we’ve talked before on previous podcasts, the agricultural industry is going through a huge sea change in the United States and around the world. The United Nations expects that we need to over the next 35 years produce a lot more food to feed the world as it continues to grow both because of the growing population and because of growing economies. This is putting a big challenge on farmers who have to grow more while there are challenges in the climate, eroding soils, limitations on natural resources. There’s an urgent need to redefine the model of innovation in the ag industry in order to significantly improve crop performance and meet the demands. As it stands today most biology based innovation in agriculture happens in the R&D departments of major corporations like a Monsanto, which has the resources to reach and dedicate years of research and teams and experts to solve these big, world-changing problems, but this limitation is not sustainable and is no longer necessary.

Recent computational and biological advances have opened up a new era of innovation to address these global challenges with sustainable agricultural solutions allowing smart startups to enter the space as never before. Dr. Todd Mockler is one of the ag experts leading this transition. As chief technology officer of Benson Hill, principal investigator with the Danforth Center, and a long time professor of biology, Todd is at the forefront of plant genomics using the tools of genetic analysis to boost crop yield, improve agricultural output, and redefine how ag innovation is done. So, with that as an intro, Todd, welcome.

Todd Mockler:  Thank you, Carter: Thank you for the nice introduction.

CW: That’s a really long list of stuff. What does being a chief technology officer at Benson Hill, principal investigator at Danforth, and long time in professor of biology — what do you do right now?

TM: All right. Well, I have, I think, the best job in the world. I’m fortunate to be a faculty member, also called a principal investigator at the Danforth Plant Science Center here in St. Louis. At the Danforth, I run a large research group — about 20 people. We are working on various problems in plant biology that I’m interested in like how plants deal with environmental challenges like stresses like cold, heat, salt stress, for example. Fortunately, at the Danforth as a faculty member there I can spend 20% of my time doing other things, and those other things are not defined, but they include spending that 20% of my time being an entrepreneur.

So, I’ve taken advantage of that and had the good fortune to meet the right people, to help co-found companies like Benson Hill Biosystems, for example, where I’m CTO, as you mentioned. As a co-founder of Benson Hill, I brought in some technologies that are essentially spent out technologies from my lab at the Danforth Center, and helped shape the science that underlies Benson Hill’s technology platform. Yeah, I think that’s what it involves. It’s have it providing some scientific guidance and leadership, pointing the direction. Say, “Okay, this is an interesting area. Let’s tackle it, and these are the tools we can marshal to achieve those goals.”

CW: So, the Danforth Center was founded like 12, 15 years ago roughly?

TM: About 15 years ago.

CW: You run one of the three principal labs? Is that right, or how many people are they like you at the lab?

TM: There’s about 20.

CW: There are 20 people who have teams of 20?

TM: Yes. Right. You can think of the Danforth as comparable to a pretty large or modestly sized biology department at a university for example.

CW: And it is now a leading or the leading institution in applied biology?

TM: Yeah, by some metrics. Danforth, it’s the world’s largest independent nonprofit plant science Institute.

CW: I would think that in and of itself would consume all of your time, but you have the capability to start other businesses?

TM: Yeah.

CW: Even though they allow you to do it I just can’t imagine that the depth of challenge of both starting businesses and running a lab like that.

TM: Yeah. It can be challenging, but it’s the fun part that’s motivating. Well, the challenge and the fun is motivating. Of course, I love the research we do at the Danforth. The research … my lab is kind of like basic research oriented, but we are never going to put a product to market. Just like most biology professors are never going to make a drug and sell it to people, right? It’s the same with plant science. I like that aspect of the applied aspect, or seeing a technology through from the inception on the R&D side, and maybe in an academic research setting through to it affecting the marketplace. It’s like a release of that kind of desire and energy by being able to take some of my effort, or tackle those problems.

CW: Based on my experience both working in R&D at a place like Boeing, and then working with institutions over time it’s not common that somebody would be a principal investigator and an entrepreneur. They’re almost counterindicated.

TM: In some ways that’s true, and, yeah, so it’s pretty rare. Often people on the academic side just aren’t interested for whatever reason. Maybe just total focus — absolute focus — on their research and their research group, their lab. The questions they’re interested in, that’s one thing. I mean, some people just aren’t interested in business, right? There’s a lot of reasons, and somehow I just have this personality where I want to be able to do the basic science, but then have a hand on the applied side, and having the good fortune to be able to play on that side because of my position at the Danforth is … you know, it’s the perfect fit for me.

CW: I’ve been excited about doing this interview for some time because it’s that unique quality of your ability to both be a respected and successful principal investigator in an academic setting, and also father or father to several key startups that are leading the way in the commercialization of these technologies. Often, we have an iPhone, and it breaks, and we just go buy a new one, but somebody needs to know how to fix it. There’s a certain point there’s a certain amount of people when three or four people sat down and said, “We know how to go to the moon,” and figured it out, and led a whole team to reeled that success. In many successful things in life, there are a few key people that really were the intersection of incredibly good in their field, and also effective as entrepreneurs. So, I’m really intrigued to understand how you got … what led you to this point in time? Let’s roll the clock back like when you were twelve or six … I mean, like six, did you wake up and say, “I want to-

TM:  We can roll it back.

CW: “… be a plant biologist?”

TM: No.

CW: Help everybody understand what the sort of sequence was.

TM: Sure. It’s long and I could go on and on, but I’ll try to keep it brief. It really starts like 40 years ago. I remember when I was a kid — I’m guessing I was like about six — and my father brought home this book he gave me. It was a book. Something about science. Like, child level science, and I just fell in love with it. Read it, and I started thinking, “I’m going to be a scientist.” Pretty much my entire life. Even though I’ve dabbled in all kinds of different areas, I was always on the trajectory to be a scientist. I didn’t know what that meant. I went through phases interested in like astronomy and other aspects of science, the biomedical side, but ultimately, I landed in plant science. Along the way … Let’s see, what it looks like is going to college, so I went to Wesleyan University in Connecticut, and I dabbled in a bunch of majors. Finally settled in biology, so I have degrees in biology and molecular biology and biochemistry.

That led to my first job in biotechnology. I worked for a startup called Target Tech which was in Connecticut. That company was working on the biomedical side, so I was working on gene therapy for human medicine. At that time, I really was on a trajectory to do something on the biomedical side. That with a company. So, Target Tech was acquired by a company in San Diego called Immune Response Corporation. That company offered to move me. I was like a 25-year-old kid or whatever, maybe 24, and they offered to move me to San Diego. I was like, “You’re going to pay me to move to San Diego? Yeah. I’ll be there tomorrow.” I worked there for a few years. Again, I’m working in the biomedical space on gene therapy, and it became clear to me at that time that if I really wanted to achieve my goals I had to get an advanced degree.

I started thinking about that, thinking about getting a Ph.D., something in the biomedical space. I knew I was very interested in … This was before genomes were being sequenced, but I was very interested in, like, genomic medicine. I remember writing an entrance essay for grad school, and then I had one of my colleagues that work … edit it. He said something like, “You keep saying this genomic medicine. What is that? Like, it’s meaningless.” It wasn’t to me. I mean, I was like, “This is the direction we are going.” Eventually, and when I got to grad school, I threw just kind of happenstance met a new faculty member in the plant science side. He invited me to work in his lab, and it was interesting to me … I was aware of some of the advances coming up on the plant side. For example, this was like when the first GM crops were starting to be commercialized, and I was aware of that.

CW: Timeframe?

TM: This is late ‘90s.

CW: Okay.

TM: Like, ’97, ’98.

CW: So, human genome was not fully unraveled?

TM: Not fully sequenced. The first plant genome wasn’t even sequenced yet, but the GM crops were just being commercialized. Yeah, I’ll give you an example at that time. I remember my first year of grad school outside of one of the labs there’s like a public bulletin board, and I had cut an article out of Investor’s Business Daily that was about — oh, now I can’t remember the name of the company — Delta Pine and Land. I think it was a GM cotton seed company that Monsanto had acquired, and I put it up on the board, and some professor, like, tore it down, and said to me, “Around here this is not going to be favored or received well.”

CW: Did any of your colleagues read Investor Business Daily?

TM: I was probably the only one. There was a couple of others. Anyhow, that’s how I got on this path of plant science. A lot of it’s being at the right time and the right place. I happened to be finishing my Ph.D. right when genome sequencing just was exploding, and I knew that I wanted to go in that direction, and that shaped most of my research career ever since. On the entrepreneurial side, all along what I just described … those were my day jobs. Like, working at the biotech companies, working in grad school for example, but all along I was dabbling on the entrepreneurial side. For example, well, in high school and in college my brother and I basically ran a auto detailing stop for the owners.

CW: Does that help you keep the beakers clean?

TM: No. It makes me fanatical about keeping my car clean. Then I contemplated taking on that business, but fortunately, I didn’t. Then into grad school, my friends and I started a series of basically web-based companies. Again, this was at the time where … this was like the Internet boom time.

CW: Yep, so it started in ‘95ish? ‘94, ‘95?

TM: Yeah. Well, ’96 to 2002.

CW: 

TM: Grad was around 2000. There was a sports focused website that a company … that we built that was actually profitable, and it was great. We ended up winding it down just because all the principals were moving on with their careers. You know, we’re all in grad school. My first genomics company called Cyber Genomics at that time, I became really passionate about gene synthesis and started a ill-fated company called [Combugenics 00:14:56]. Those were all-

CW: Gene synthesis and auto detailing are not normally-

TM: Yeah. I know.

CW: … in the same resume.

TM: Exactly, but I have varied interests, so these things were interesting at the time and/or potentially profitable, or cool technologically. Then I had a bit of a lull, so after getting my Ph.D. I did a postdoc at the Salk Institute. I tried really hard to focus on my science then because I really wanted to set up my career in a faculty position.

CW: So, there’s a certain point where you really have to pay the dues-

TM: Buckle down.

CW: … and dig in-

TM: Yeah. Exactly.

CW: … or really know the science.

TM: Know the science. Publish. In this business, it’s really about you have to publish to achieve scientific credibility, and make discoveries, or publicize, communicate your discoveries. The other part of it is you have to fund that work, right? Money doesn’t grow on trees, and somebody’s got to pay for the science, so fundraising is a big part of that.

CW: Is that like fundraising for a startup but different?

TM: It’s different. You know, it’s different. Yeah, as you know the fundraising for a startup you don’t usually write like a 20 or a 50-page written proposal, right? It’s more of the roadshow, and other supporting documentation. Pitches. On the science side, it’s more about usually written proposals where you really lay out all the science, and the hypothesis, and the experimental plans. It’s kind of like a scientific execution plan. It’s different. The fundraising, you have to raise the money to do what you want scientifically, but it’s done in a very different process. Anyhow, I buckled down, did well enough as a postdoc to end up getting my first faculty position at Oregon State University, and there I was … because when you’re running your own lab you’re basically running your own little kingdom, and you pursue your own scientific interests. Whether right or wrong, or for good or for bad that’s the idea.

CW: Where do you get the inspiration? What’s the pressure that gives you the inspiration for your scientific interests? Is it you have some blinding flash of the obvious where God, like, inserts it in your brain, or are you seeing something in the market, or what is-

TM: That hasn’t happened yet. For me, I can only speak for myself, there’s a combination of things. Part of what you have to do as a scientist is kind of constant surveillance of the literature, and the new findings, discoveries in your field, the hot topics, hot areas. In that way, you know where the science is going, what technologies are available to tackle your problems, things like that. It’s like putting your finger in the wind and sensing the direction.

CW: You’re in a multi-disciplined … yeah, you’ve done immunotherapy, human based I assume?

TM: Yeah. Right. Yeah.

CW: But on Salk side, it was ag.

TM: Yes. That’s right.

CW: You saw the sort of rapidly changing application of genomics really coming from the pure science phase to applied? Is that fair, or you probably still-

TM: Well, I would say it was not really pure science to applied, but the widespread application. Like, genomics going from being a very esoteric thing where the only places doing genomics were gigantic, mega sequencing centers like up here in St. Louis at Washington University where it was like an industrialized thing to nowadays, and even like now it must be about 10 years ago when you could start buying a sequencer for your lab. That kind of thing. It was democratized.

CW: When did you buy your first sequencer? Was that like … did you have a party that day, or was that sort of a … or did it just arrive and it’s like, “Oh, it’s a sequencer”?

TM: No. Well, I didn’t buy it myself. This is at Oregon State University, and with the leadership of Jim Carrington who is now the president of the Danforth Plant Science Center, we were one of the first groups to buy an Illumina sequencing machine. Illumina was the company that-

CW: How much did it cost at the time?

TM: I think it was like $800,000. Something like that.

CW: When was that?

TM: This was 2006 maybe. No, it was a little bit later than that. Probably 2008.

CW: What is it cost today?

TM: Well, let me just … And like six of us chipped in. We pooled our resources to buy it.

CW: Your labs? Yeah.

TM: Nowadays, you could get a machine that has equivalent sequencing capacity probably for $100,000. It’s dramatic.

CW: What does that cost?

TM: The ones nowadays are dramatically smaller, easier to use, and everything.

CW: And what did that cost like in ’97?

TM: The technology didn’t even exist in the sense that the sequencing technologies were radically different.

CW: It was 200 people in a lab pulling films and-

TM: Yeah. Gel images, and manually scoring the bases. Many, many orders of magnitude less throughput, and the costs were many, many orders of magnitude higher. Give you an idea, so the first plant genome project that my lab kind of like co-led, it cost probably about $6 million to sequence a genome, and right now I could sequence that genome for maybe $200.

CW: Really?

TM: It’s just unbelievable how in less than a decade the technology has changed everything.

CW: As you compare yourself to your peers, because they are not really being entrepreneurs … some of them are. I mean, the amount of Ph.D.’s that walk in our door leading entrepreneurial activities is small. What in your background do you credit with making you more entrepreneurial?

TM: It’s a great question. I don’t know. It’s just a personality thing. It’s like definitely part of me is like ADHD, and I have lots of interests, and want to pursue them, and have trouble just shelving something and not pursuing it. I’m willing to take risks.

CW: So, ADHD’s a feature, not a bug?

TM: Correct. Yeah.

CW: Were you ever on Ritalin?

TM: So, traits are all … just like in plants traits in people are relative to the environment, so being able to task switch or multitask, and/or jump from radically different things like giving an academic talk one day, and then jumping on a plane, and then giving an ag biotech pitch for a startup. To me, that’s fun. This is some of those-

CW: It doesn’t create stress? You just naturally shift gears?

TM: Well, it’s always a little bit stressful, but I somehow figured out how to just switch gears. You have to think a little bit differently. A lot of times I find kind of on the entrepreneurial side there has to be — for something to be legitimate scientifically — good scientific grounding, but the people you’re talking to – investors — they’re not going to want to go get down into the incredibly deep weeds, so you have to talk about science at a different level, for example, then if I was giving a presentation at a university. It’s a different audience. Different language. Different approach. I’m not claiming any kind of expertise at it, but I’ve been doing it.

CW: Has there ever been a time where you’ve sort of said, “You know, to do this sequencing or to think about this plant differently, what I learned detailing cars gives me this insight”? Is there any of that kind of multimodal kind of fusion that’s going on in your brain that is … have all those experiences contributed in some way?

TM: I think so. I mean, not like that. That was a good, fun example, but not like that. There’s just a huge amount of crossover. There are things, for example, that my lab has been pursuing — so, I’m talking at the Danforth — in what’s called field phenotyping or remote-sensing of characterizing plants using remote sensing technologies that we are doing on the academic side, and working with people that are like leading the charge in those areas, which are kind of new research areas in the plant field where I see … immediately can see the crossover and benefit to Benson Hill, or to NewLeaf Symbiotic’s, for example.

CW: Just to step this through this, so by gathering information in the field as the plants are growing and that environment, you can bring that back in to the breeding and gene editing process-

TM: Exactly.

CW: … to steer the optimization of a crop?

TM: Yeah. Exactly.

CW: Is that new thinking, or is that … If you get up and stand up and tell people this is it, “Oh yeah, obviously,” or do they sit there and they say-

TM: It’s one of these things it’s like hindsight is 20/20. For many decades, we’ve recognized that in any organism not just plants like I worked on, but traits are the manifestation of the information encoded in the genome – so, genes, the DNA — and how they interact with the environment. This has been well known. That concept is not rocket science by itself, but it’s only recently do we have the capability, for example, characterize the entire genome and the differences between varieties or individuals at a single base resolution. So, you can understand like we can sequence my genome and your genome, and understand every single base difference, and how they might theoretically affect the genes.

At the same time, because of developments in imaging, and optics, and sensor technologies, and then all the computational processes needed to make sense of those data, we can characterize plants in exquisite detail. You could like scan a plant with varied sensors every single day, and have temporal resolution, and spatial resolution, and information that breeders never even dreamed of in the past because it was just effectively impossible. Then we can have what’s called envirotyping information, super precise high resolution data about the environment that the organism is growing in. This is still an emerging field, but when you start bringing all those pieces together, my belief is that’s how are going to engineer the next generation of crops, and engineer and/or optimize breed by a combination of genomics and traditional breeding and genome editing or GMO technologies. It’s going to be because of that convergence of understanding the genome, understanding the plant development physiology, and understanding the environment.

CW: Is that something like … I’m going to make this up that for 30 days it’s okay if it has light water, but in like 10 days if it has more water at this particular phase it’s going to increase its yield by 10%, or is it-

TM: Yeah. That could be an example, and if we-

CW: But we don’t know that per se.

TM: If nobody’s looked for that for a particular crop we might not understand that. There are really basic things that we are just figuring out now where people are just doing the studies to understand. For example, like in the field the growth rate of … the differences in growth rates between different varieties of sorghum with one-day resolution, or hour level type resolution.

CW: Is that the type of resolution it’s like day, hour and not minute, second?

TM: Yeah. Day, hour. Just because the logistics of doing all the sensing over the … it takes time to scan a field, but this is information that it was impractical to ever gather in some cases just because either the technology didn’t exist, or it was too expensive, or too cumbersome, or whatever. So, these kinds of things are now becoming routine. It’s almost like the example I used earlier. 15 years ago it cost millions of dollars to sequence a genome. No regular scientist had access to the technology. Well, now the world’s changed, and you could go by an Illumina machine and put it on your desk if you just felt like it.

CW: We’ll have to look up the price on that.

TM: Yeah, and these other fields-

CW: I do have an oscilloscope at home, but not a genome sequencing machine.

TM: I think it’s akin to that in that there’s all these technology developments around sensing and characterizing plants with resolutions that are unprecedented that now are becoming available and routine.

CW: Then what will happen next? If you’re doing that field data, is there another thing beyond that, or do you think the field data’s another 30 years of effort to understand its impact on a crop?

TM: Did you just say 30 years?

CW: 30 years.

TM: No. I think in a matter of five years or something like that.

CW: If we just look at genomes. The effort around genome probably started warming up in the late ‘80s. Became a main stay in the late ‘90s, and it’s now practical enough to be part of an engineering suite.

TM: Yeah.

CW: So, you’ve got like 25, 30 years of life cycle on that.

TM: Yeah. I think that because a lot of these technologies that I’m talking about that are being applied in plant science, they’re pre-existing technologies. I mean, like hyperspectral imaging’s been around for a long time. It’s, of course, being miniaturized, and made cheaper, and better, and all that. So, it’s really technologies that exist, in most cases, are being applied to crop plants in new ways. Some of that development cycle … you don’t need somebody to come up with a radical new way to sequence. The bigger bottleneck … I mean, there are some bottlenecks, and some of the bottlenecks we are seeing are on the computational side. Extracting the nuggets of information, or think of it like the needles in the haystack, out of these large sensory data sets, to try to find … called features in the data that are correlated with traits you’re interested in like yield, for example — probably the most important trait — and all the components of the yield are other important aspects or traits of plants.

CW: Well, so, in the execution of that will that give us 5% better yield? 10% better yield? Is there sort of a peaking out that you think a natural limit to what the yield can be on corn other than a hundred … You know what I mean?

TM: I’m going to get the exact number wrong here I think, but if you look at crop plants like soybean, or sorghum, or corn that’s grown under absolutely optimal, ideal conditions like no stress and perfect … no nutrient limitations, perfect environment, all that, the yields are dramatically higher — like double — of the average corn yield is, for example. So, that yield potential is … it’s not like 5% more, 10%. There is enormous yield potential to be captured. Then, I guess, the other aspect of your question is small increments of improvement are meaningful. If you look at like the steady rate of genetic improvement, the rate of genetic gain in big crops, it averages out to like less than 2% per year, and that’s meaningful, right? If you compare corn yields from 40 years ago and today, that slow progression is-

CW: 1 or 2% per year is a good … means a lot.

TM: Yeah. It’s great. In other contexts … like, companies may not be interested in trying to commercialize something that’s only going to give you a small bump, right? They’re looking for step function type bumps like 8 or 10% or something like that. I think it’s all context dependent, and I can’t predict what the outcome’s going to be, but I and a lot of other people … the market kind of shows this with what’s going on in ag biotech and the new startups that are popping up, people believe that, yeah, there’s more potential to be extracted.

CW: What do you think comes next after that? We’ve done the genome. We know how to do gene editing, or maybe we don’t. Maybe we are getting there. Or monitor the fields? What’s next?

TM: Well, that’s a good question. Some of what’s next is the integration. The solution for a particular crop isn’t going to just be genome editing our traditional breeding. It’s going to be bringing these things all together. For example, if you could use genome editing to add a handful of desirable missing traits from your elite breeding materials, and then bring some traits in by GM, so it’s really like a product like an iPhone or whatever that’s an assemblage of a bunch of great features and traits. There’s that. I think bringing these technologies … this is I think part of the democratization of the process is bringing all these technologies to other crops. At least in the US in the last 30+ years, corn and soy have probably gotten the lion’s share of the effort in terms of…

CW: By that, what do you mean? Like, 80%? 90%?

TM: I can’t even hazard a guess, but it’d probably be 90%.

CW: Something on that order.

TM: Yeah. Something like that. I mean, where-

CW: So, we put all of our attention on the two big kids in town-

TM: Yeah. On a couple big-

CW: … but we haven’t focused on anybody else?

TM:… massive acreage crops that are really valuable. It totally makes sense. That’s where the economics are, but these technologies can be applied to other crop systems, and now that they’re cheaper or better and all that it’s going to be a faster process. I’m kind of jumping here, but here’s an example: you and I talked earlier about corn. Let’s just say it’s been domesticated for roughly 10,000 years or whatever, or that was how long it’s been-

CW: Long time.

TM: Long time. And other crops, people have been improving them through traditional breeding in one form or another for thousands of years. Well, if somebody wants to try to create a new crop today from some wild species it doesn’t have to take 10,000 years because we can apply all these technologies, and leapfrog it really fast. Maybe you could, essentially, domesticate a new species in a decade or two now, so there’s many opportunities there.

CW: It’s sort of like when the iPhone first came out it had email, but now it’s got 40,000 apps, so once we sort of unlock the capability, the entrepreneurs will unleash everything else.

TM: Exactly, so I think that’s an area where these technologies will just be applied to more and more crops and for different purposes. Some of the examples you and I talked about earlier where it’s a specialty products for example, or chemicals made in plants-

CW:  Like we were talking about, cultivate, making rubber from dandelions.

TM: Right. Exactly. That’s an example where, essentially, the crop is an engine for an industrial application. It’s driven by the accessibility of new technologies.

CW: Could you ever make a winter corn? Will you ever be able to engineer it that far that the-

TM: You mean that would grow through the winter?

CW: It would grow through the winter.

TM: No, well, maybe that would be a stretch, but I won’t say anything’s impossible with science.

CW: Well, that’s very interesting. All right, and so what’s next on your ADD list?

TM: I have a few things I’m interested in. I mentioned earlier this concept of … It’s called envirotyping, which is acquiring and analyzing, understanding very high resolution, essentially, environmental data. I’m working with a colleague at the Danforth and thinking about a startup company in that area. So, imagine sensors that would be in like every breeding plot in a crop improvement platform providing that key piece of information how the genetics of a variety interacts with the environment to give you the phenotype which is the, for example, yield. That’s one area that I’m very interested in.

I am also working with some other colleagues on a concept for another ag biotech type of a company, a seed company idea in the sorghum space. Sorghum is a very interesting crop that’s been very dear to me the last several years. In the US it’s an important crop, but relatively low acreage, and mainly used for feed, but in other parts the world, like the areas of the developing world it’s a staple food crop. It’s really a fascinating plant, and that has tremendous native stress tolerance, drought tolerance, heat tolerance, that’s just amazing. I mean, makes corn look kind of pathetic under those kind of conditions. Those are a couple of the things I’ve been thinking about.

I’m very interested in — and we talked about this — this idea of applying remote-sensing to plants. This is a place where there’s a lot of crossover from my academic work. We have some really big projects where we are using these remote-sensing technologies to characterize plants in the field, and also in controlled environments like growth chambers and greenhouses. Getting that kind of information fully integrated along with the genomics in the crop improvement process, that’s just a general goal of mine. That’s going to probably push forward both on the entrepreneurial side and on the academic research side.

CW: Great. Well, thank you for your time. I want to be sure that you’re going to come back again because I want to keep seeing this evolution. We are certainly interested in all these different angles, and give some more thought to how you end up being both an entrepreneur, and a scientist because I think in the future conversations I want to sort of … people are fascinated by that type of thing, and it’s an intriguing challenge about how we get more entrepreneurs to help grow things. Really appreciate the work you’re doing, and thank you for being on the show with us.

TM: Thank you for having me, and thanks for the great questions and, yeah, the fun time. Thank you.

On today’s podcast we discuss how startup company Better Weekdays is reducing friction in the talent acquisition process. With their interactive platform that provides tools and services, improving the hiring process for students, colleges, and employers.

Carter Williams: This is Carter Williams, CEO of iSelect with Chris Motley.

Chris Motley: Hello. How are you?

CW: Welcome Chris. Chris is one of iSelect’s portfolio companies and the CEO of Better Weekdays. Better Weekdays is a software application that helps corporations with entry-level hires. A very, very novel approach. Their story is very, very interesting. Chris, could you just give the audience a picture of what Better Weekdays does, you know, 30 seconds, a minute, fundamentally what you’re doing.

CM: Sure, our flagship application is called The Whether, and we really take an approach of inbound recruiting to this process. So the traditional methods of recruiting college students is an outbound approach like going to career fair, or having a career website that you’re trying to draw people to. And we’ve created an application that allows companies to engage and nurture talent to convince them to apply. By doing that you really open up discovery of the most relevant opportunities to college students, especially given the fact that they’ve never done a traditional job search.

CW: So you’ve really taught me something in this process as we’ve invested in your company, that I think I already knew this, Millenials are a bit different. I mean I remember college recruiting, this is 1989. I sort of knew the companies, and I was into engineering and trying to figure out what I needed to do, and pretty much knew the companies were targeting at. But you’ve told me that quantum Millenials, who might be graduating in a degree, don’t really know what the opportunities are in their market, which just is mind-boggling to me.

CM: Yeah.

CW: Help me and the audience understand what today’s student graduating, our listeners’ children perhaps, what’s sort of different about that recruiting process than in the past?

CM: Yeah. I think there’s a number of things that are different, but there are also things that are exactly the same. So the exact sameness in the experience is, you want to work for a company that will develop your career, your professional life so that you can kind of build a good life. Right? That’s the exact same thing that people want today as in the past. However, you just think about the S&P 500, I mean the companies that compose the S&P are very different than even 15-20 years ago.

And if you think about the previous generation where folks worked at companies for 20-30 years, you can easily lose touch in what the opportunities are to give the advice to your kids. And so you have the confluence of technology, a different way of discovering all products and services, so that would extend naturally to jobs, as well as sort of the democratization of information. And technology has developed in such a way where a lot of companies exist now that provide great opportunities for students, but they all have this marketing problem of raising that awareness.

CW: Now you’ve also taught me that that marketing problem is, you know, I’m Emerson. I’m a world-wide leader. I’m an extraordinarily well-run company. But the chance that a Millennial has any idea what Emerson does, is a number approaching zero.

And the other thing you’ve taught me, which I’d love you to help expand on, is that Emerson doesn’t know how to … I don’t mean to pick on Emerson, because I love Emerson, but I’ll use them as an example. That Emerson doesn’t exactly know how to speak Millennial. The HR person at Emerson, sort of is trying to tell people why they should come work for Emerson, but you’ve found that there’s a better way to help that student really comprehend in their context, they, the student’s context, what Emerson does. Can you help us understand that?

CM: Yeah so I think it’s two points there. I think one point is that a company as large as Emerson, may have a brand association in engineering, but they have a tremendous number of jobs that there’s no association for college students for those types of jobs. Another example can be BJC, here in St. Louis, where two-thirds of their jobs have nothing to do with being a healthcare practitioner.

CW: This is the largest hospital system in St. Louis.

CM: And largest employer in St. Louis. And again, most of their open jobs have nothing to do with being a healthcare practitioner. So you think BJC, you think hospitals, nurses, doctors, etc. But you don’t think about all those opportunities. So part of it is, companies may not have the consumer-facing brand, so the awareness is approaching zero with Millenials. Or companies have such a strong brand in an area, where they have other positions that are hard to fill, simply because you don’t think about it. An easy example is Apple. It may be obvious now, but three, four, five years ago, their biggest, most hardest to fill position was retail, because most people thought design, engineering, software development, not people to man the Apple Store. So that’s the first point, strong brands create an association or the lack of brand awareness creates a situation where there’s just no awareness whatsoever.

The second point is language. I mean, you taught me, especially as an entrepreneur, you have to kind of talk about your business in the most basic language. Right? So we help employers recruit college students easier. How we do it, it gets more complicated and that sort of thing. But it’s the same as true in recruiting, we live in our companies and our lives, and we’re so ingrained that we don’t use simple language to describe what we do. An example is a company in town called Worldwide Technology, and Worldwide Technology is a systems integrator. Now I’m almost 36 years old, it took me a long time to understand what a systems integrator was, which basically means that that situation is magnified for someone in a college campus. If instead Worldwide said, “Help us help our customers find and implement the best technology.” Well that’s something that anybody can understand. And that is the core of the issue, that we are speaking a certain language as business people, or as recruiters, that just doesn’t register to someone in college who is pursuing the job search or the internship search for the very first time, and they use completely different language.

CW: So the other thing I’ve learned, is this is a big problem. High unemployment in the young graduates, they want a job, that the numbers are sort of shocking. The hiring process, I guess for graduates, college graduates, corporations spend as much as $8 billion a year in that process.

CM: Yeah, it’s actually super interesting and this is the … I mean I laugh every time I think about it, because the Major Industry Association does a survey amongst employers who recruit college students, and one of the questions they asked was, “How do you recruit college students?” And most of the companies, their number one activity is a career fair. Then they asked, “How effective do you find the career fairs?” And 72% of all employers found the career fairs ineffective, and you juxtapose that to that number you just said, which is $8 billion spent trying to hire college students. So almost everybody agrees that what they do now doesn’t work, yet they spend an incredible amount of money on it each year. And so that’s where we see the wide spaces being to dominate it and to sort of redefine how students discover opportunities, and how those organizations discover talent.

CW: And I’m getting that it’s that discovery process. So the corporations spend $8 billion a year running career fairs or whatever the routine is. They’ve sort of done this year over year, and it’s like let’s run another career fair. So they’re spending $8 billion a year doing that, and only 74% of the applicants disappear somewhere along the line of I guess when they first start getting engaged with a corporation-

CM: Oh it’s the application process. Yeah. I mean 74% of people who start an application process drop off somewhere along the way.

CW: Because they’re not qualified, or they lose attention or what?

CM: Part of it is the … I don’t know the last time you applied for a job, but it’s a pretty arduous process. And if you barely…

CW: That’s the great thing about doing venture and being entrepreneurs. You never have to apply for a job. You just keep making the jobs up.

CM: But I tell you one thing, we all hate doing more work, and if a company makes it very cumbersome to apply to their job, the most talented people will choose to do something easier. So what’s interesting about that stat, you know 74% of people dropping out in the application process, is that that doesn’t even include the people who may be considering your company, but choose not to apply. And it also doesn’t include the people who don’t even know your company exists. So it’s a lot of waste that’s in the system, and I think that what we have built is reducing a lot of that waste, and that friction in the current process.

CW: So, I’m a corporation and we certainly know this as entrepreneurs, we know that people are absolutely the most important asset. At the end of the day-

CM: Without a doubt.

CW: … they walk, your most important asset walks out the door, and hopefully walks back the next day. If I’m a corporation, and I’m spending $8 billion and what you’re basically telling me is, the people who I want to employ either or don’t even know to apply to my job, or apply to the job and somehow get pushed away because I’m not communicating with them in an effective and compelling manner. And so my $8 billion investment is-

CM: In aggregate obviously, all companies pay this.

CW: In aggregate, is misplaced and so for a company like an Emerson, or somebody like that or BJC, how much do they spend on this?

CM: Well, I tell you the cost per hire from an entry-level perspective is about $4000. That’s reported by-

CW: So this is somebody that you’re paying 15-20 bucks an hour.

CM: Or the equivalent of $45,000 a year roughly.

CW: Okay. So roughly 10% of their first year of salary cost to find that person.

CM: You’re exactly right. That’s a good way to think about it. And if you think about, well what is the upcharge for someone who has the experience, and the staffing firms have pretty much set this pricing model or structure. It’s 20-30% of the starting salary for an experienced-level hire, based on their model. And that’s a huge opportunity for us you see, because at the entry level, it’s roughly 10% of the starting salary, but our pricing model is such where it’s much less than that.

CW: So how much do you reduce that by? If I’m sitting here and I’m the head of HR or somebody … I’m the person who makes this buy decision, and I’m saying I’m going to spend money on career fairs and my current existing system is $4000 per, 10% per hire. But Chris has now come in and said he’s going to offer his solution, what is-

CM: Yeah, so our pricing model is, first of all, it’s all within the context of inbound recruiting. So it’s something you do all the time. You’re always recruiting. And if you want to engage Millenials, it’s about creating and distributing content that speaks the language of the Millenials and meets them where they are. So that’s an ongoing process, and so as such, we charge a subscription that starts off at $500 a month and it kind of goes up from there depending on the company size. So for an average company, it’s paying us let’s say $12,000 annually, well this is for unlimited job postings, both for internships and full-time jobs, which basically translates to unlimited hires off of our platform. So you can easily see a case where your cost per hire of entry-level talent is less than a thousand bucks. A lot of people say-

CW: So I’m paying $4000 and you give me the option to start to bring that price down to something like a thousand.

CM: Or less than that.

CW: And I’m also getting a more engaged, more interested employee.

CM: Yeah, and I think that the engaged part is important, whether someone becomes an employee or not. Because let’s say you’re Enterprise Rent-a-Car, and you have been nurturing someone to help them understand how they could be successful in your organization. And for whatever reason, you don’t hire them. Well you just gave them a great candidate experience. So A, they’re more likely to rent a car from you the next time they go out of town. And B, they’re more likely to recommend your company to others. Starbucks was a pioneer in this space. I mean they’re selling $5 cups of water, no offense to Starbucks. The point is that Starbucks had one of the best interviewing processes of the many companies, because at the end of the day they still wanted you to buy that very expensive cup of coffee. And so this whole notion of candidate experience is a very big trend these days, and I think it’s really put our business in the sweet spot because you improve the candidate experience by communicating with them in a relevant and engaging way.

CW: And relevant and engaging, you speak Millennial. It shows up on their iPhone. They can sort of check it. You’ve got a new version of your application, they can sort of call The Whether.

CM: Check The Whether. Yeah.

CW: You can check on a regular basis, so hey my girlfriend is moving to St. Louis. I want to find a job sort of doing what I like to do and I can-

CM: Yeah, so check The Whether in St. Louis, exactly. And what’s interesting about it is it’s all about personalizing career pathways. And it’s a very subtle but important point because sometimes you just don’t have the skill for a job. But what about the school or certificate program you can enroll in to upscale yourself? Well that’s sitting right next to the job you may aspire to have. And so that holistic experience that we’ve created that can personalize not only the job or the internship, but relevant events in the future, mentors, or ways that you can upscale yourself, I think is part of the winning combination that really helps to generate increasingly more and more engagement.

CW: So then as you continue to expand on this, you’ll be able to give them some insights to show them, hey here are other people that worked at BJC, or in the field to get some perspective-

CM: Well we take it even deeper than that. We will basically say, “Here’s a day in the life at BJC.” “Here’s an example of an executive profile of someone who went to your Alma Mater.” “Here’s a person who’s already opted in to be your mentor who works at BJC, and they’re like a second year associate, so they’re very much like you.” Versus matching you with some 20 year executive who really doesn’t … His day in the life is very different than yours would be. Let’s just say that.

CW: So if I’m the person running this decision at some place like BJC, you’re telling me one, you can get my cost to acquisition down. Two, I’m going to engage with those folks in a more meaningful way, in a way you can understand what BJC’s looking at, but you also understand the language of the young people, and you can sort of help them make sure that it’s a job match both ways.

CM: Exactly right. BJC is increasing their brand exposure. They’re doing so in a way that is talking about their company culture and what’s valued there. That attracts the most relevant people who care about that sort of thing. It improves the candidate experience, so that each candidate and hopefully new employee will be very engaged at your company, which is a whole other kind of part to this. And ultimately they become a net promoter of your company, right? Everybody knows that the best source of hire, is referrals. It works better at larger companies than smaller companies, but it’s the biggest driver of how talent shifts from one organization to another. The problem is in universities, you don’t have a network, not professionally. And so that’s broken down. So you have to have … It’s an opportunity, I guess a different way of saying it, for a company again to create and distribute content to meet people where they are, because they don’t have that referral to help understand what that company’s about. So companies can play an active role in that process.

CW: So we invested in you in part, well certainly because the core business model makes sense. As we look at what we call the gig economy, an explanation we have for why there’s an employment displacement is what I call an impedance mismatch. I’m an engineer, so everything’s an engineering thing, but an impedance mismatch in which companies don’t know how to find the right people. Students don’t know how to connect with the right company. And that if we can help those folks understand better how to match we get better performance. Now you were that we invest in startups, is because the person leading it is an awesome entrepreneur.

CM: Thank you.

CW: And has incredible resilience, and you, to get more personal, how did you … You’ve got a very interesting story about how you landed here and I love the kind of resilience that you’ve pursued. Can you tell the audience a little bit more about how you got here?

CM: Sure. And on the resilience point, I don’t know if I can take total credit for that. I think it comes down to how I was raised. I mean I’m a son of a teenage mom on the South Side of Chicago. You talk about resilience, that’s where it comes from. But I grew up in a household that while we weren’t rich in terms of money, it was very rich in love. And my mom recognized very early on that she provided me with opportunities that gave me access to people, or information, or the resources that I can probably increase my chances of being successful. So one of the most formative things I think that I experienced was, I was a part of this program when I was in 7th or 8th grade, called A Better Chance. And this organization basically helps to match inner-city youth with college preparatory boarding schools more often than not, that are sort of feeder schools into the top universities of the country.

CW: I gotta say, do you know a guy named Frankie Cruise?

CM: I do know that name.

CW: He was a classmate of mine.

CM: Get out.

CW: Yeah.

CM: Small world.

CW: I didn’t realize you were a part of A Better Chance, because he was … Is he still with A Better Chance?

CM: Well, I mean I look at it as a lifetime thing. I mean it starts off-

CW: He was part of it, and went to a boarding school with me, and ended up leading part of ABC I thought. I never knew that. Okay, keep going.

CM: Yeah, it’s a phenomenal program and the alumni list of you know the Deval Patricks or Marty Nesbitt, you know one of Obama’s best friends.

CW: Really, I didn’t know that.

CM: Yeah, they’re all A Better Chance alums, so very high expectations. But the point is, I think it also proves how that model works. The point is that you can see matching to opportunity and access to opportunity has been a theme, and there’s 10 stories after that which has sort of the same dynamic. I think what’s interesting about it is programs like A Better Chance, there’s many others, served a very important purpose in the community. Because this is the era of pre-Facebook, and pre-social media. Even when I came from high school to college, post-college, this is all prior to social media.

CW: So this is-

CM: 2003 is when I graduated from Columbia in New York. So this is three years or so before Facebook was launched. The point I’m making is that when you had organizations like this that did in a very manual way, what my product does today, right, it’s very, very effective. The difference between then and now, is that you have social media. So you have the apparent access to anything you want. And that’s not necessarily the case. It still goes down to relevance, and personalization, and access to opportunities that sort of meet your strengths and values. So I think many of these organizations, while they still serve a very important role, I think they find themselves trying to figure out how they stay relevant this day and age. Right? But anyway, I’m off subject. The point is that-

CW: But it sounds like you were the beta for your application.

CM: Of course, everything comes-

CW: Or the alpha.

CM: Everything comes out of personal experience. Either directly or what you’ve seen frustrates other people. And so for me, you know I went to this college-prep boarding school. I met different people, access to opportunities. I then was in another program over the summer called the LEAD program in business, and it was at Columbia University, so no doubt why I ended up going to Columbia. And one of the speakers was this gentleman who was a trader at Goldman Sachs. And I said, “What’s your job?” He says, “Well I buy low, and I sell high, and I make a lot of money.” And I said, “Legally?” And he said, “Yeah.” So I said I could do that. And the point is, I didn’t grow up in a place where you even knew what legal trading is. There was a lot of trading on the South Side, but not of oil and other commodities that are legal commodities.

And the point is, you can’t be what you haven’t seen. So when you think about the folks in this country in colleges and universities, they don’t see the opportunities. I mean, who goes to the universities to recruit? Large companies. But who creates the most jobs in this country? Middle-market companies. And they’re at a competitive disadvantage. So it opens up a huge opportunity, which I think leads to that stat you mentioned earlier about the 8% unemployment with Millenials. It’s a structural unemployment. They’re not seeing the opportunities and vice versa. And so there has to be some facilitator in the middle, which The Whether is a mediator.

CW: It’s almost separate. I mean if each corporation tries to do this, it’s something different than saying, look I’ve got a trusted partner. We’re going to use The Whether. They’re the people that understand how to get this point across, and we’re going to team to go get the best people.

CM: Exactly right. I think you have certain markets where you have to have a platform. Dating, right? There has to be a platform that can facilitate that. They’re not many, even if there’s 10 or 15 or 20 apps that do this, that’s not a lot when you think about the amount of people. Facebook plays a very important purpose, even when they first came out, it was really cool to know who else was in your community. I think the same is true in the job space. When you have so much information out there, these days, you have to kind of pare that down to the most salient points to understand how to manage your career. And today, nothing does that. Nothing does it in the market for college students. I’m always waiting for someone to challenge me on that point, because it may be the source of a new innovation, or it may mean I need to pack my bags up and go home.

CW: Well so you went from Columbia. You end up at Goldman. You’re hanging around people that, you know, if you get into that track, gazillions of dollars. And you left?

CM: Well, the goal was to … Well yes, I left. But the goal was to understand how to make money, and the goal was to prove to myself that I can compete at the highest levels. But when you see how much money you make for an organization, and you see the drivers of wealth creation, you almost owe it to yourself to figure out how to do it on your own. And that’s what I did. They taught me everything I know from a data and analytics perspective. I mean it’s a pretty intense environment, and building a company culture and that sort of thing.

But one of the reasons I went to work for Goldman, people used to ask me this question. And I said, “Well, I want to work at a place where I can make the most money in the shortest amount of time, and if I don’t like it I can still have any other job in the world.” And I think that’s the logic students should take these days quite frankly. The point is that I didn’t forget how to trade. I didn’t forget how to value companies and do the traditional banker things. So at 25 years old, I had a business idea that I thought had some legs to it in the manufacturing space, and then I pursued it. And because it was learning, and it was building important tools in the toolkit that I thought would be important to build a significant business. So yeah, that’s kind of how I try to stay focused on the craft of building things that are ultimately useful versus just sort of facilitating transactions, which you know is not that fun in the grand scheme of things.

CW: And so we just have a moment more. If we were to interview you again, let’s say a year from now, or two years from now. What do you want to be able to say? What is it you want to be able to say to the market or yourself?

CM: Yeah, that The Whether is the best place for students to discover the most relevant opportunities, and the best place for university recruiters to discover the most relevant talent. I mean if we achieve that, we’ll create a significant, significant business and that’s exactly what we focus on, and that’s what, you know as Warren Buffett says, “I tap dance to work everyday,” because it’s a noble vision.

CW: So you help create jobs. You help reduce the cost for BJC to find the best people. You’re a hard-working entrepreneur. For the people out there listening, this is the kind of thing that transforms industries. And Chris is the kind of guy that does it. So we want you back. Thanks again for your time.

CM: Thank you very much. Very kind of you.

CW: It was great having this conversation.

CM: Likewise, thanks.

There is massive consolidation occurring in the healthcare space right now, and as a result hospital systems are acting almost like private equity groups. They’re sucking up all of these once-independent primary care providers and are distributing all of the administrative functions that these providers manager to shared, centralized care teams in an effort to cut costs, just like any good private equity investor would.

In the case of healthcare, most of this is happening in outpatient care management. As of today, 99% of all health care delivery in this country happens outside of the office, not when people are face to face with their doctor. Healthcare systems are starting to realize this, and they are now staffing rooms full of nurses who are monitoring the highest risk patients to address this need.

This is a trend that, with support from the right technology, has the potential to dramatically improve patient satisfaction, patient health and business health all at the same time. At the same time, the health system can save money by pooling all of its resources in these back-offices, and patients are getting more access to their providers and better out-of-office care as a result. The missing piece of the puzzle is simple enough: how can care managers identify the patients that need their support and thereby connect with the right patient at the right time?

That is why iSelect has invested in a company called Epharmix, which is taking the digital transition of healthcare a step further by developing new tools to enable effortless, seamless patient monitoring. Epharmix creates technology that sends disease-specific questions to patients automatically, enabling the existing care managers to serve many more patients and bend the cost curve. The unobtrusive system uses mobile technology to collect patient data while they go about their daily lives, improving patients results while simultaneously reducing workloads for providers.

I recently had Blake Marggraff, the CEO and co-founder of Epharmix, on iSelect’s “Innovation Anarchy” podcast to talk about the technology the company is working on, the challenges it faces in the digital medical space, and the opportunities he sees to vastly improve healthcare delivery in this country.

Click above to listen to the podcast.

The global population is booming, diets are shifting and urbanization is rising. Never has so much been asked of agriculture to meet the needs of our society. Never have the external risks to agriculture advancement been greater, whether from changing climate, limited natural resources, concerns over chemical inputs, protests over GMO, industry consolidation or reduced choice in the marketplace.

In the face of all these challenges, new innovations are needed to advance agriculture for people and our planet. Cloud biology — the combination of plant biology, Big Data analytics and cloud computing — is one such innovation, driving new developments in agriculture throughout the value chain.

It isn’t a new field. It is something that has existed in the broader life sciences community for several years, and is centered around the convergence of cloud computing with biology. Think about the cloud services offered by Amazon Web Services and what that really represents, both from an analytics perspective and a computational scale perspective. Combine that with tools like machine learning, artificial intelligence, and more, and you suddenly are able to take very, very large data sets and extract value from them that humans might not be able to see. Then you can take that information, those insights, and develop biological solutions or recommendations from them.

Obviously, this transcends many, many industries, not just the life sciences, but agriculture is quickly becoming fertile ground for cloud biology.

The resulting products from all this, of what the computational engine is telling you to do, is in the crop. Sometimes that means higher productivity. Sometimes that means better nutritional profiles. Sometimes that means a different leaf architectures so that you can plant at a higher density in a field and get effectively more outputs for no additional inputs. Whatever it is, it is a result of cloud biology and analytics informing those decisions.

On this week’s podcast we are featuring Matt Crisp, founder and CEO of Benson Hill Biosystems, an iSelect portfolio company that is pioneering the use of cloud biology for agriculture, leveraging technology to solve some of the world’s greatest agricultural challenges.

Click above to listen to the full episode.