Dasha: [00:00:00] Welcome to the Biomedical Frontiers podcast, where we explore pivotal research projects and disruptive innovations aimed at translating scientific advancements into tangible healthcare solutions. I'm your host, Dasha Tyshlek.
Tom: Science and art stem from the shared human impulse to create. This is something we all share.
And so an artist does not really fill a blank canvas in one fell swoop from a magical vision. They often make their way towards the craft and develop a vision in small steps and explorations, much like a scientist does. A scientist doesn't just follow some boring analytical process to invent a smartphone, or build a bridge, or send a person to the moon, or cure cancer.
There's often a creative process of zigzagging to a solution, deciding which direction to go in totally unknown territory. Just as an artist does.
Dasha: This startup that was spun out was also able to raise 1 billion as a startup.
Tom: It was historically staggering as an amount. So it may be just worth thinking about why is that?
You know, why did investors have the confidence to do that? And I think it's really because coming out of the breakthrough in AI based protein design, they raised as huge amount of capital because they got an exclusive license to develop small peptides as like the ones I just mentioned for drugs, for a number of human disease states.
Dasha: When I took bioelectricity with Dr. Kim, he emphasized this idea that when studying the human brain, you run into a paradox because the computing power basically required to understand a thing is beyond what the thing itself possesses.
Tom: Even with the largest computers today, we're only doing two dimensional computations while the brain is doing seven layer computations at least.
Plus the number of synapses interconnections in the brain is something like a hundred to a thousand trillion connections. So that greatly exceeds the number of transistors, which is only about, well, on the biggest one, 3 trillion on the, on the largest computer chip.
Dasha: Welcome to the second season of Biomedical Frontiers. We're so excited to have our audience back. And this season has so many exciting new guests sharing their wisdom, their knowledge, and their innovations. Today's guest is Dr. Tom Skalak, who joined the Joe and Clara Tsai Foundation in 2018 as the senior advisor to Clara Wu Tsai.
The foundation makes philanthropic investments in science, social justice, and cultural production with a vision to produce transformative impact on societal well being and sustainability. Tom was previously the founding Executive Director of the Paul G. Allen Frontiers Group and the Vice President of Research Emeritus at the University of Virginia.
In these roles, Tom led creative synthesis of research and innovation programs spanning biosciences, environmental sustainability, Physical sciences, engineering and technology, art, design, entrepreneurship, and the humanities as a professor and chair of the biomedical engineering department at University of Virginia.
Tom's original research included cardiovascular biomechanics, computational modeling, wound repair and regenerative medicine, hot topics on this podcast. He was the founder of the UVA Coulter Translational Research Center at University of Virginia and the early stage investment funds with corporate partners, such as Johnson and Johnson and AstraZeneca. Tom has worked widely on innovation ecosystems with the white house and US Congress and fortune 500 CEOs.
He was also a residential artist at the Djerassi Resident Artist Program. Tom, we are so excited to have you on the show.
Tom: Happy to be here.
Dasha: Well, you have seen biomedical and biotechnological based ventures at nearly every stage of their growth process and have helped numerous partnerships be created that support these ventures.
And so this is where I'd like to start. Can you break down for us the stages of development for biomedical and biotechnological ventures and what is needed at each stage of a new biomedical venture when they're initiated through academic research? I know that's a mouthful.
Tom: Well, Dasha, academic research is usually at the cutting edge of a new technology or seeking to discover new knowledge through original discoveries, finding things that have never been seen or understood before.
So the key ingredient at this early stage is talented and [00:05:00] curious investigators, the faculty, the staff, and the students at research institutions. At this stage, I like to say there's a sort of beautiful inefficiency that's needed. And this isn't really done in most corporate innovation groups or what are called skunk works in industry.
There has to also be patient capital, usually grants, often from the government, sometimes from philanthropy and a structure that allows for this kind of free exploration, which often takes several wrong turns before finding answers or uncovering novel findings. The next stage is usually to explore applications in the commercial world to benefit people.
For a new venture to be viable, this requires an outward facing mentality to follow where the needs really are and to move the new knowledge towards solving that need. So here, moving rapidly to make go no go decisions about what's viable is important. And this is where programs like the University of Virginia's Coulter Program with program managers in place can be really helpful.
I should mention that there's another method of doing, quote, use inspired research in which a pain in the market is identified first and then new research undertaken to solve the identified problem. This method is often used in more applied labs like engineering and in some biotech operations. And then finally, you know, in terms of the steps you asked for, in either case, once a proof of concept is done, often with a working prototype or a first in animal or first in human testing of a drug, raising of private funds and then acquiring an experienced business leader, a CEO, is very helpful in almost every case.
Now there's some exceptions where a tech or science leader has taken companies all the way through to exits or acquisitions. Examples would include our former UVA faculty member, Bill Walker, or Microsoft founders, Paul Allen and Bill Gates, who wrote the code themselves, or Wallace Coulter, who built the blood cell counter himself.
Dasha: So various stages here, value is already being created, but it needs to be nurtured and funneled. How does that process work and what is required at each of these stages to support the evolution in a way that results in research that's been productive for human health?
Tom: Well, new knowledge or a new invention is often at the heart of value creation. Without it, value is often based more on marketing differentiation or pushing feature sets to customers, especially in today's digital world. In biomedical ventures, the first value creation stage is usually asking and testing. Does it work? Yeah. It's a simple phrase, but very important, certainly for medical devices, this is key.
For pharma and drug development, and more recently for AI based patient treatment services, value is sometimes based on prospective or promissory claims about expected efficacy, future sales, or savings to the end users. Another stage is, securing IP rights, intellectual property rights. This can add substantial value by providing barriers to entry into a market.
And then adding an experienced management team often adds value, not least because they bring the network needed to raise capital rapidly in later rounds. And after that, it's really the obvious stages such as first in man results or clinical trial data releases. And then it's sometimes also, customer or government adoption through large contracts for products and services.
Dasha: When you were describing the stages, you mentioned a couple of things that really caught my ear. You said, early stages and discovery, you need like patient capital. Later, you need almost rapid testing and project management and then oftentimes you need venture capital. I'd like to go through each of these to better understand the capital and the resource need that you described specifically.
So what is patient capital?
Tom: Well, patient capital means capital that's not driven by quarterly results or annual revenue projections, [00:10:00] nor by publicly held companies, stock prices on wall street. So, it's typically means, capital that comes in either via government grants, and that's important because governments are committed to the long term health of our society, so, they can afford to use tax dollars to invest in long term research.
That eventually, you know, we'll win the war on cancer or we'll produce a better image, you know, of an injured, knee joint and so forth. They can do those things, and it can sometimes also be augmented, of course, by, private philanthropy. So grants and gifts can support that kind of long term investigation. That's what patient capital means.
Dasha: Excellent. And then in the second stage, you mentioned, you know, the organization like Coulter, but you specifically said program management, something that I'm personally passionate about. But how does program management meet science at the stage to achieve results? What does that really look like?
Tom: Well, that just means when a new finding like identification of a molecule that a drug ought to bind to, you know, cure cancer or to treat diabetes is discovered, you then need to move it in ways that give you go, no go answers like, there's this molecule manufacturable.
Is it toxic? Is it going to hit the target, you know, at the right level to produce the desired, you know, therapy or benefit to the patient. And so this means that laboratory group is often segwaying into a bit more managed process. And the idea is that the results from each step of that experimental process, makes the entity, the concept, or the company, or the product, more attractive and more valuable to an outside investor.
So, the goal is to manage it through steps that then allow the often, university or institutional discovery be attractive enough to go across the street where a private investor, either an angel or venture capital, or other can go ahead and make a confident investment to bring it to a commercial product stage. And it's important to have that management because if you know, for the average person on the street, listening to the scenario, this segue through management to commercialization.
It's important because no drug or device ever helped anyone who was sick or ill or injured and needed the help, unless it was commercialized. So, the knowledge flows out to the world through commercialization and program managers help with that process.
Dasha: And then in the last stage, venture capital, private capital starts getting involved.
How does that capital then help advance the technology into healthcare field? And also, what are the limitations of VC capital at this stage? And I ask this because I think there's always a lot of attention on venture capital as a means for producing, you know, new startups and to getting technologies out, but it's not the only way to go about it.
And so I'd like to understand a little bit better, the pros and the cons at this stage involving VCs.
Tom: Well, Dasha, you are correct. venture capital has acquired almost mythical status in our commercial ecosystem. And that's because they've helped support some early stage companies that are now market leaders.
So it's an earned reputation, but in earlier days, you know, VCs would roll up their sleeves, help founders, company founders achieve growth, and then share the financial rewards with those who created the original value today. Venture capital funds are generally have become so large. They're in the multiple billions of dollars for the, you know, the top decile funds so that.
In many cases, they look only for very large market ventures, usually after proof of concept, customer sales, beginning of scaling up. But there's a diversity of VCs, so if you are looking to do a biomedical startup, finding the right one with the right people and the right fund size for your venture is the key.
And, if you do find the right one, VCs can help most in two ways. I would say first, they know the landscape because they see a lot of deals and technologies, more than most people at any one institution where the discovery has happened or the invention has been made. And so they can do a comparative analysis very quickly.
And, the downside of that is it can sometimes backfire when a herd mentality is in place. So novel, disruptive ideas, which were originally the bread and butter of a VC, might now go unfunded, ironically, [00:15:00] by VCs. And, the second positive is that they can help raise capital and they can put excellent management networks in place, rapidly.
This can be very helpful for ventures in smaller regions like Charlottesville, Virginia and other places where there's a high talent concentration for early stage value creation, like at universities or other research institutions, but there's a low concentration of management talent.
And then you ask for the limitations, the limitations for VCs are they overlook very important, smaller markets, deals that are viewed as below, let's say 500 million, you know, valuation or exit potential. Even though, companies that have that sort of valuation or potential, often are producing extremely valuable goods and services.
In fact, it's a history of, you know, the greatness of this country or others that have had manufacturing economies that you have a diversity of smaller businesses as part of your strength. So in a way it's going against What, you know, made the nation strong originally, you know, to only look at large market, you know, unicorn type plays, it would make sense to have a set of investors looking at smaller deals, actually economically, another limitation.
They have limited patients with deals outside their, let's say, 100 mile radius in their typically larger cities. And that's a well known, which is. Generally true. although they do fly around a lot, and then they have a current obsession. I would say this is a recent one with it and especially AI artificial intelligence.
because of the perception that you can get rapid low capital growth in those areas, like Uber or other such examples, and this is true, despite. Long term valuations being highly suspect, right? Because the eventual value has to come from does it work back to that basic question in the certainly in the biotech world or health health care world.
And the last 1, I would say limitation. They're subject to herd mentality. I mentioned this earlier, but. There can be a herd mentality in their diligence. In other words, they ask their VC friends for opinions and that can then become an echo chamber where everyone's looking at the same kinds of larger scale deals.
They can miss really important and significant new biotechnologies or medical devices, because they're within that chamber, they're only looking for the larger tech deals.
Dasha: Well, one example that I'd like to dive into a specific case study that you have been intimately familiar with, which is when you were VP of Research here at UVA and you helped found the Coulter Translational Research Center.
You have now gotten to see over many, many years, the impact that it's able to produce, not only on the university, but also on the region. Could you describe what you see as a result of that middle stage of nurturing from deep science, fundamental research into commercializable product what effect that produces?
Tom: Yes, I can. That's one of my favorite topics. So, the Coulter program was vital. I would say to the maturation of biomedical engineering and innovation more generally at the University of Virginia, which is 1 of the top 2 public universities in the country. UVA BME, for bioengineering, at the time was ranked among the top programs in the world already.
It was alongside Johns Hopkins, UC San Diego, MIT, Duke University, and so on in terms of quality and citation impact and so forth in areas like cardiovascular disease, cancer, diabetes, orthopedic tissue engineering and systems biology, along with some technologies. We had leading MRI and medical ultrasound expertise, so that was the state of the department.
But what Coulter did was it allowed the talent, and the early stage ideas in this very, you know, energetic research engine to go ahead and make their way towards commercialization. And it led to a flourishing venture system here, actually propelling the Charlottesville region, to be the fastest growing venture capital region in America, amazingly.
So the grand Coulter experiment as we call it, because it worked well in 10 other places in the country. It wasn't that we brilliantly did [00:20:00] something different, it really was a genius of this Coulter experiment. And it was a rousing success, now with over 20 to one return on investment and an endowment that's grown to over 25 million, here at UVA.
And it's really a tribute to the ideas of the Coulter Foundation and they're very experienced corporate leaders, which included Sue Van and Elias Caro, who had worked in industry, with the Coulter corporation. And, you know, The other key ingredient was we were fortunate to attract a young David Chen from his MBA at Darden, which is the top 10 business school in the country here at UVA.
And he had already had prior biomedical industry experience. Having said that, those were his credentials, but he was the youngest Coulter manager in the country. Others were, you know, more kind of seasoned industrial managers, but for the first several years, UVA outperformed Stanford in innovation, according to all of the Coulter metrics, which were independently measured.
And it really was David's enthusiasm and energy, to get everyone involved and attract external partners for our researchers, that was a key to the success. In fact, you know, there's a program called UVA Innovates in quotes, active today at the university, it's now involves all 11 schools of UVA.
But this wider program really owes its backbone DNA to the success story of Coulter at UVA. And then this growth you can see as really representing kind of a smart realization by the current leaders of the university, President Jim Ryan and Provost Ian Baucom, that innovation is consistent with and actually amplifies basic scholarship in all fields of human endeavor.
And, you know, at UVA, this is why it's my favorite topic, bringing useful knowledge is the phrase that was used, by Thomas Jefferson. He said, bringing useful knowledge to the world was his founding aspiration for the University of Virginia when he built the university, right after writing the Declaration of Independence and Coulter, and now UVA innovates the program are making this a reality in the modern world.
And so I think, you know, the reason I'm so happy to talk about this topic is that now, the substantial private wealth in our beautiful region here in central Virginia, by the Blue Ridge, mountains is recognizing that they can make private equity and philanthropic investments, early stage investments, right here with the talent at home and realize the same aspirational impact that they want as if they were investing in more traditional innovation regions, like Boston, San Francisco, San Diego, New York City, et cetera.
So, my call to action out of all of this kind of growth and success story of the Coulter program, would be to people in the region, let's create a 100 million dollar investment fund for Charlottesville area innovation, startup companies. That would be the next step in this story.
Dasha: I love that. And I just want to add personally, you know, working with David has been one of the highlights in my career, over a decade now. And, his enthusiasm for translation of promising technology into health care, was an inspiration to me as a student. And I've seen personally the impact it's had even on undergraduate students taking the risk of trying to innovate, you know, even before they've gotten their own lab. And it has been successful. There have been many people I know who have come through, with startups or who are now VCs because of the experiences they had through David's teaching as well as through the Coulter projects he's funded being in the lab with the professors.
And so, the impact is probably even beyond what can be measured in UVA spun out companies because of the people who got involved in this translation of biotech because of this work.
Tom: It's a great point.
Dasha: This is kind of a big question and I'm sure we will not get to the depth of it, but because of your wide view, both having been here at UVA, but now working with a foundation that funds research everywhere, all kinds of different universities and specifically also involved with Yale, you have the big picture view of [00:25:00] how biomedical engineering has been translated into impact on human health. And that's a big question we're looking to answer on this podcast.
Tom: That is a big question, Dasha, but that's what you do, so, I'm happy you asked it. The benefits of biomedical engineering have been vast. And so there's a lot of ways you can say it or measure it, but they've been vast for really billions of people worldwide, and it's contributed to hundreds of billions and new economic value that is dollars and created millions of jobs.
Most people will appreciate that. BME was behind every drop of blood that's analyzed at their doctor's office by a Coulter Counter or similar device. Every time a high school athlete twists their ankle or knee and needs an MRI, that's coming from BME. Every time a child is born in the U. S., the mother has a very useful ultrasound imaging session, which comes from BME, ultrasound engineers. Every grandfather whose life was saved by an arterial stent in their heart after they had a heart trouble or a new heart valve, perhaps that came from biomedical engineering and most new drugs that have been analyzed for their efficacy and toxicity to clear them through the FDA have been looked at recently with systems bioengineering analytics.
So I like to say BMEs don't do the surgery, but we make the surgeons better. You know, we don't diagnose the illness, but we make better drugs available to patients with illness, etc. So, you know, most families are touched by BME at least once a year, if not more. In maintaining their health and well being and in an even larger sense for our society, it makes our economy grow and it actually keeps our country secure because you need tax revenues from that strong economy to keep your country secure.
So, the impact on society is health and wellness, but actually well, beyond that, towards economic, security as well.
Dasha: I can see you're really passionate about, some of these things that you mentioned as technologies and impact. What drove you personally to become a biomedical engineer?
Tom: I studied at Johns Hopkins, which was the number one BME program in the world way back in the 1970s, which was when the field was just developing. It was when cell biology and biology were joining with the quantitative methods of engineering and mathematics and computing.
So it had the attraction of being young and new and offering great promise to make biology and medicine more precise and more effective. So I essentially studied a dual major in cell biology and physiology and engineering mechanics. And, then I went off to UCSD, San Diego on the West coast, which was at that time pioneering applications of biomechanics to the microcirculation.
So my specialty there was how small blood vessels form the millions of small vessels in the tip of your little finger, for example, how they react to disease and how they're repaired after injuries. And that really became my specialty. And I came back east to UVA because it was a unique opportunity to help build up one of the nation's oldest BME programs.
It had been founded back in 1968, when people came down to Virginia from some of the even older programs at places like Penn, farther North. And, also, the BME program at UVA was right alongside a world class cardiovascular research center, which was then led by a physiologist, Brian Duling, and now by Gary Owens.
And so it was a fantastic marriage, again, of sort of the engineering and the physiology opportunity, which has really been critical since the department even today sits partly in the middle of the medical center, which is key to its success actually. And, we were then fortunate after that, to attract a lot of young talent to UVA BME, and they've made it a top program in the world today.
So, that's the short story.
Dasha: Well, let's turn to your work at Joe and Clara Tsai Foundation. You get to see the outcomes of early stage project funding, and [00:30:00] one area that's really piqued my interest from what you shared earlier is protein design. What is protein design and what is the fundamental challenges of protein design?
Tom: Well, protein design is the process of designing new proteins from scratch on a computer using new combinations of amino acids than the ones that were evolved by nature via evolution. So the essential idea is that the solution space of possible peptide sequences in the protein is very much larger than what nature has produced.
So if we can design proteins for specific tasks, they might be better at specific functions, like a medicine, a drug, a building material of photosynthetic structure to capture clean energy from the sun, or to make more efficient molecular machines. And once they're designed, the new proteins can be produced rapidly and cheaply using microorganisms and tested in the lab for effectiveness.
So you can prove out that the structures are what you thought they were. And the fundamental challenge, historically, in doing this was the difficulty of predicting real protein structure in 3D from the basic peptide amino acid sequences. And that was because it involved very complex solvent field calculations, so called, you know, how the water molecules interact with the different, chemical moieties on the, on the peptides and so forth, which was very expensive on the computers of that time, you know, several, many years ago, basically. And, also taking kind of other local charge effects and chemical effects, you know, where different chemical bonds of different strengths were being made in these proteins as they folded. And so that made the protein folding problem, or 3D shape problem very difficult.
Newer programs for protein design use artificial intelligence to rapidly match peptide shapes for new sequences to known structures, and that accelerates structure prediction dramatically. It's been done now for hundreds of thousands of human proteins. And in fact, the work we supported at the University of Washington was named the Science Breakthrough of the Year Worldwide by Science Magazine in 2021, which just as a measure is much harder to do than winning a Super Bowl.
Dasha: It's mind boggling to first think about the reality of hundreds of thousands of different proteins existing in our bodies. And then also the scientific rigor required, as well as the documentational and management rigor required to even start fathoming that we could understand every one of them and ultimately be able to recreate it.
That's extremely visionary. What is kind of the future of protein design and and the future the future benefits that humanity might see in the next, let's say, 5 to 10 years.
Tom: Well, they're dramatic and they range across the things I just mentioned. So, so-called high value applications for small amounts of new proteins are obviously in new drugs for a variety of disease states.
In fact, that's well underway in a variety of spin outs from the Institute for Protein Design at the The University of Washington, which we could talk about. but, you know, you're talking about medium sized peptides that are bigger than the traditional small molecule drugs, but smaller than very difficult to manufacture monoclonal antibody type drugs.
And so you have these easy to manufacture, you know, medium sized peptides that can hit disease targets in dozens of human diseases, and I think what we'll see over the next decade or so is a lot of these protein designed drugs will come to fruition and they'll make drugs cheaper and more available to hundreds of millions of people worldwide who right now can't get those drugs they need because they're either too expensive or they're not widely manufactured.
And then I think there'll be other applications that involve larger amounts of proteins, you know, some are in, for example, many people have heard of the plastics crisis that we're in where, you know, in the developed world, at least, there's a lot of plastics used in packaging and manufacturing and even devices like computers and microphones that we're working with today.
And, so one needs to take care of these in [00:35:00] terms of a life cycle. And so one way to take care of them is to have enzymes. Proteins that break down plastics back to their basic chemical constituents, and therefore make them more, you know, essentially biodegradable and help the environment that way.
Another application would be clean energy, which we all know we need to reverse global warming. Well, yeah. Plants do that, you know, trees do that in their leaves and green grass does that. But, protein design could develop new molecules that capture energy from the sun, you know, capture electrons basically, and use them to produce electricity, more effectively by designing photosynthetic molecules.
And then another one at scale might be the building industry. So right now, the construction industry is one of the most wasteful ones on the planet. There's about 30 percent waste when you build a skyscraper or a residential house. And you can imagine reducing that by using building materials that are made more biologically, if you will. By, you know, using protein design to make structurally stiff proteins or to make flexible coatings.
For example, you can imagine a flexible coating that even absorbs sunlight for the outside of the house, rather than a paint, a traditional paint, which is more of a moisture barrier than anything else. So there's a lot of applications across multiple industry verticals, but the first one clearly will be drugs and medical applications.
Dasha: Well, one company you highlighted was Xaira, which was spun out of that University of Washington research group that studies these proteins. And, in addition to the technological capability that's staggering, this startup that was spun out was also able to raise 1 billion dollars as a startup, which is not the highest that's ever been raised, but it's right up there with the top companies.
What's the significance of that for the field of biomedicine in general and VC funding, as we talked, what does this mean?
Tom: Yeah, well, it was exceptional. It was historically staggering as an amount. So it may be just worth thinking about why is that, you know, why did investors have the confidence to do that?
And I think it's really because coming out of the breakthrough in AI based protein design, they raised this huge amount of capital because they got an exclusive license to develop small peptides as like the ones I just mentioned, for drugs for a number of human disease states, outside of infectious diseases, which are being worked on by other companies. but using the methods from the University of Washington, and the David Baker lab group, and then the 2nd part of it.
So they got the technology and they got an exclusive license to it for a period of time. They also attracted management talent. So they attracted a former Genentech company leader, in Marc Tessier-Lavigne, the former president of Stanford, and that gave investors confidence that the basic research advances in protein design could be moved forward to drug development.
Rapidly, and I think the valuation is so large because most biotechs raise, let's say, 5 to 20 million dollars in their startup rounds, based on having 2 to 4, that would be a lot actually, promising lead chemical compounds for a single disease, or maybe a couple of diseases. In this case, there were dozens of promising protein design compounds for over 10 different human diseases.
So, the valuation for the startup was correspondingly higher.
Dasha: You also mentioned that David Baker, who is the principal investigator who leads this initiative at the Institute of Protein Design, this is not his only high impact, high raise licensed or spun out venture from his research. Is it the field that he's working on or is it something about his practices that is enabling this level of productivity in new venture development?
Tom: Well, it's funny you should ask that because I've asked David that, many times and his basic answer is that this sort of work can't really happen at more mission focused commercial firms. And so he invests his time and energy into what he calls a sort of magic of collaboration that exists in his university lab, which doesn't scale to commercial entities. And that's the [00:40:00] key to his serial success in protein design and new venture creation that you're alluding to.
I mean, they've had over 10 companies with a total investment of over 2 billion in private equity over just the last six years. It's actually a remarkable record, probably the most remarkable in the history of, you know, early stage research. And, he just says that it's because of the speed of information flow within this highly collaborative group inside his university lab, where they can share information freely and very rapidly that allows them to make progress.
In fact, with their AI discoveries, you can argue that they beat the best commercial AI company, Deep Mind, part of alphabet at their own game. So it was a public university beating the best commercial company in the hottest tech, at their own game. And there's gotta be a reason for it, which is why I like your question.
And, but it's sort of a mysterious answer, right? Is that there's this intangible magic of collaboration when you allow information to flow freely. And I think there's a second part, which is that it's David Baker himself, who's a brilliant, you know, chemical biologist and really understood deeply the physics and chemistry of protein folding.
And he's able to build that into their algorithms and therefore, you know, gain a leading position in that, based on that expertise. I think that's the key, and so, you know, in the larger innovation discussion, I really find his attitude refreshing and it's a great lesson for everyone looking to bolster our US innovation ecosystem because it's a virtuous cycle in action in the sense we need all the parts of it to work.
So the basic science part that David drives that you dub works really well, but then he's open to letting things go across the street and attract, you know, commercial experienced, drug company managers, to join him in the various spin outs, and then that can lead to commercial success. So then the cycle works really well and society sees the benefits of advancing science and engineering because the whole cycle is working.
Dasha: Could there be any sort of counter incentives or distractions from situations like this. So obviously 1 billion valuation is an enormous fortune and fame for a scientist in David Baker's specific example. It sounds like he's spun out many companies, and so, he has a track record of of continuing his research, despite this incredible attraction of leaving academia and going into the commercial world.
But, you know, I could see that something like that could put more emphasis on only doing translational research versus the scientists who are doing basic or foundational type of research, or it could even incentivize overstating the effectiveness of new technologies to investors, or maybe prevent cross university collaboration where so much money could be at stake. Do you see those as risks, or do you think those are somehow balanced out in the grand scheme of things?
Tom: Yes, I think all of those risks are just part of human nature, and they're natural, and they're real. So, you know, some part of that desire fuels the success of American business innovation. There are good parts to this dilemma or conflict or tension, and, you know, to an extent, everyone seeks a degree of financial independence. And for some, it's a path to more discovery and exploration. And for other people, it's an end in itself to enjoy life or other pursuits, and that's just human nature.
And I think, the undesirable and unethical parts that you alluded to can be managed by having the right checks and balances in place, using common sense and using generally accepted guidelines for research integrity. You know, I used to be the research integrity officer of the University of Virginia, a major, you know, public university.
So we take these issues very seriously and when there are violations of research integrity, there should be consequences for those individuals or for those companies. As a positive example of, you know, how this can be managed, we could use the protein design company we just talked about, you know, the co founder David Baker at UW. As I said, it's a public university and he believes deeply in [00:45:00] continuing to pursue basic knowledge at his public university, giving access to all students from all walks of life to join in, to gain an education, and even share in the financial rewards, if those happen for their projects.
So even after spinning out those 10 companies with that total private investment of over 2 billion, he's still committed to do further science at his university, knowing that this sort of work cannot happen at more mission focused commercial firms, that he's been part of starting. And he's even reinvested some of his personal financial wins back in to the university research.
So I think, you know, the cycle works well when it's involving good people who are working for the right reasons and for, you know, the good of discovering the truth, inventing new things and then moving them over to commercial success. It can work really well, but I think the temptations or some of the ethical breaches you mentioned can happen because of the promise of financial rewards and they just have to be managed.
Dasha: It makes sense to me, and I think a big concern could be things like talent drain, but sounds like the people like David Baker, who are serial inventors, they are confident also in their ability to continue delivering great innovations.
Tom: It's an interesting point because, you know, talent train would be if David Baker, in this example we're discussing, had left the public university and taken a billion dollar startup package and set up a lab across the street and taken all of his know how and knowledge and ability to teach and left.
You know, and that's just a personal choice. Many people do that, right? So we should also applaud, you know, say faculty, or as you said, undergraduate or graduate student entrepreneurs who take the initiative to go across the street, start something new with their ideas and their abilities and make a success of it.
But, you know, it takes all of those choices to add up to a successful ecosystem of innovation, right? Because if everyone went across the street and had that kind of investment, they'd all, everyone would be in mission focused commercial farms and it would kill the early stage innovation in general.
You know, the idea that can work completely in their private sector, I think is misguided. And that's why having a very diverse set of university research institutions in the United States has been the key to our growth as a country over, you know, over 200 years now, because you just can't do it.
You know, the private sector is good at some things, and then, you know, the early stage science and research institutions are good at other things, and they're very complimentary. So the talent drain, it's almost an anomaly to talk about it, right? Because if some, it's okay for some people to go where they're called, if you will, where they're calling in life is because there always be other people with ideas.
But if we were to kill one part or the other of this virtuous cycle, the cycle will be broken. That would be the talent train that would be dangerous. But I think when individuals make decisions to be in one point on the compass, if you will, you know, one point in the cycle or another, depending on their individual interests and skillsets, that's fine. So people should vote with their feet and go to what they're attracted to. But I think if as a country, if we were to cut off a part of the cycle, that's when we would have a problem.
Dasha: Yeah, that's a great thought. The balances and how the system is in a virtuous cycle. I love that. Well, another area you're involved in, with the Wu Tsai Institute at Yale lists out three areas of research, and I am only vaguely familiar with the meaning of these words.
So, I thought probably our audience also, might not have heard these new and complex ideas. So if we can dive in to each one of these in turn: neurodevelopment and plasticity, neurocognition and behavior, and neurocomputation and machine intelligence.
Tom: Yeah, we can do that. So the first area, neurodevelopment and plasticity, it refers first to how the brain develops and how specific neural circuits are formed and pruned during childhood and growth of a young person. And then, the second term plasticity refers to the same process, essentially of adapting neural circuits after we're grown up.
So how does an old dog new learn new tricks or how does an executive [00:50:00] learn new decision making skills to, for example, assess how AI affects their existing business or how does a retired accountant learn to play the piano. And luckily, the adult brain has plasticity, so we can do new things. My favorite example of this is the artist Monet, who said, at age 72, I'm just beginning to see.
And right after that, he painted his masterpiece, the water lilies paintings. So I think, you know, that's what neurodevelopment and then adult plasticity refers to. The second area, neurocognition and behavior refers more to questions of the whole mind, if you will. So, how we focus our selective attention, say on one aspect in our view, rather than others in the background.
Just because we're more interested in certain features or threats in our world or opportunities facing us. So as an example, how does a baseball player focus on the flight of a fly ball while ignoring the noise of the beer drinking crowd, just to one side of his view or the field? Or, you know, why does, why does fortune favored the prepared mind? Or, how do we develop empathy for others, which is what allows a civil society to continue without constant conflict. What is altruism? When we help people without the hope of a reward. How do stored memories in our minds play into our creative imagination, for example, a designer planning a new city or a musician composing her new masterpiece?
So all these behaviors historically fell under the field of psychology, mostly, and now they're becoming underpinned by much more mechanistic understanding of neural function at the cell and molecular level. So all of these play into that area of behavior, if you will. And then the third one is neurocomputation and machine intelligence.
So, yeah, it's a complicated way to say this area will work with extensive data that are obtained from the actual functioning of the brain and the mind, you know, obtained using imaging or electrode measurements and so forth and try to see what principles or analytical rules are being deployed in biological intelligence, and it does this using mathematical, mostly computer modeling.
So, as an example, when the brain carries out a prediction about the future, how are we using our memories or other creative tasks to make this prediction, right? Because all you have in life is your memories of your past experience, yet, we all probably feel we're somewhat creative or we make smart decisions about what to do tomorrow and so forth.
So all of those come under neuro computation. So how does the brain carry out cognitive computing? And it's solved really well. You know, the hope is that this kind of new knowledge could actually shape the future of synthetic intelligences too, like AI or future general intelligence systems.
Dasha: Now you said a lot of this used to be studied in psychology and I was also hearing some even philosophy.
Tom: Yes, exactly.
Dasha: Now we're looking at it from a scientific biomedical perspective. What is our current state for understanding this cognition from a scientific perspective?
Tom: Well, I'd say it's in its infancy, certainly relative to more established fields like chemistry or physics. We understand some aspects of how, if we break it down, how sensory systems deliver input to the brain, what happens to those signals inside the brain, and then how certain reactions occur, you know, how we make decisions of what to do and how to act, like, should we fight or should we flee? Should we eat more? Should we socialize less or more? You know, do we feel loneliness, et cetera?
And we really don't fully understand even the working parts or interconnections in the brain yet, much less how complex phenomena of the mind happen, things like literature and how it might affect us or how we feel after watching a movie, kindness or loneliness in today's, social [00:55:00] media world. So I think it's really just in the early stages.
Dasha: And so what are some of the challenges of studying cognition scientifically?
Tom: Well, the unique challenges are that it's obviously difficult to study human infants for the development, part of this, even though there is some progress, there's some fMRI imaging, being done now on young children, safely.
And, we also have some methods of studying adult living brain, but they're still limited. So a lot of our current understanding comes from lower organisms being studied in the lab or even organoids, you know, collections of cells that resemble some aspects of neural function. So, the study of collective cognition is another thing I would say that's still really young and a big challenge, that is the interaction of groups of people.
It's very young, and yet we know that these kinds of environmental effects can play very strong roles in behavior and mental processes. It's essentially the nurture part of our behavior. And we know now, you know, from molecular biology, there's even epigenetic codes being formed on our DNA as we converse on this podcast, our own brains will each be different having completed this conversation.
Dasha: What do you think, and I know you said this is an early state of research, for now, but what can be some of the impact in the future from taking this biomedical approach to cognition?
Tom: Oh, impacts are really extensive, but let's name three. One is how we learn during childhood growth and adolescence. So by understanding how we take in information and inform our views of the world and our creative or analytical abilities, it could really affect how we teach children, and how children learn, from various, you know, modalities of instruction or schooling, if you will. So I think that'll be a huge impact.
For adults, I think, you know, some of the things we talked about adult decision making, you know, executive function as it's called, could be improved and particularly, what's being called brain resiliency could be improved. And that is that you could, improve the last third of life for many people by maintaining, you know, peak, cognitive function, much further through, through the lifespan.
Dasha: Are there any elements of the research that's being done through the Wu Tsai Institute that you would say could now be applied in a kind of general wisdom way?
Tom: Well, there are a lot of these, I mean, some of them have to do with, for example, what's being called a flow state where one can, you know, be aware of a complex environment around whatever you're doing, whether you're engaging in a competition or whether you're at work, whether you're reading a book or, you know, interacting with a group of social friends that you can be in a state where you're more able to integrate different kinds of inputs through your different senses, and then focus on the activity at hand, if you will.
So, you know, there are some results coming out on that. I think how we structure classrooms is another impact that's coming out in terms of presenting material to school children in certain ways, even length of classes, those kind of things. I think can be some of the nearer term impacts, and you've probably heard of some of the things coming out in terms of digital applications in terms of improving memory, you know, in adults.
And so I think those kind of things will be some of the near term gains that we'll see.
Dasha: That's awesome. It's amazing to think there can be knowledge that can be applied now, but that we're also just at the beginning of a whole new area of science. I remember when I took bioelectricity with Dr. Kim, he emphasized this idea that when studying the human brain, you run into a paradox because the computing power basically required, to understand a thing is beyond what the thing itself possesses.
So our brain can't understand itself was the paradox he taught us. Do you see that manifesting in some of this research?
Tom: Yeah, that's a very sophisticated concept and it might turn out to be true. So I think what he was saying is that, you know, the [01:00:00] actual primate and human brain has many layers.
And there's many interconnections among those layers. And in contrast, even the most advanced computer chip from Intel has only two dimensional circuit connections. So even with the largest computers today, we're only doing two dimensional computations, while the brain is doing seven layer computations, at least. Plus, The number of synapses, interconnections in the brain, is something like a hundred to a thousand trillion connections, so that greatly exceeds the number of transistors, which is only about, well, on the biggest one, three trillion on the on the largest computer chip.
So I think he's saying that we might not understand the functions of the brain until we can build a computer to help us analyze it, that has many layers of circuits. And that's a big cooling problem right now for engineers, so we really can't build that. And also has hundreds of trillions of transistors, and it's essentially the proverbial hot fuzzy ball of a supercomputer, and we're not even close to creating that right now. You know, maybe we'll get there eventually with DNA computing, or maybe even protein design for computer engineering.
Dasha: It's going to require a lot of collaboration with electrical engineers. Well, one other area of study, that you're involved in with the Wu Tsai Human Performance Alliance, which aims to transform human health through the science of peak performance, which beautifully stated, is really interesting.
It's a really big, hot topic right now in a lot of medical literature, kind of more a popular medical literature on some of these big podcasts, human performance is an emerging topic of discussion, but I'm wondering what does looking at human performance and studying human performance scientifically enable us to discover that looking at disease does not?
Tom: Well, optimal human flourishing is not simply the absence of disease, so that's at the heart of it. And, you know, we all aspire in life to some passions like, to run faster, jump higher, or create art that really moves people or make music that touches our listeners or beat the stock market, or maybe play with our grandchildren as they grow up.
So looking at performance opens up the possibility to help people realize their maximum potential, both early in life, you know, when you're learning and growing in your formative years in midlife, where you generally, you know, working and creating your place in the world. And then in the last third of life, you know, if you lose movement capability later in life, your life narrows considerably.
And if you want to win an Olympic gold medal, like is happening right now in Paris, you need to move effectively and really well, often with exquisite mental control over the physical action. So all of these are situations why we're excited to learn more about human performance.
Dasha: And what is some of the most important research you see going on in human performance right now?
Tom: Well, we are focusing, in the Wu Tsai Alliance, on digital models of human movement on molecular basis of performance in males and females, on multi scale modeling of the cellular basis of training, you know, building muscle or building endurance and regeneration after injury, and unique features of the female athlete, because we think that's been greatly understudied.
As one way to learn principles of performance, and then rehabilitative repair after injury. We imagine, you know, what if we could repair a torn ACL in the knee and ligament in the knee joint in weeks rather than months? But, what if we could even avoid the injury in the first place by changing running geometries in school children so that injuries were reduced by more than 80%.
So this, you know, kind of catastrophic life injury would never happen in the first place. And that's what the digital models are aimed at achieving. Or, imagine if stem cells could be induced to form useful, load bearing cartilage replacement. So, creaky knees, which many people develop in about midlife could be restored without expensive knee replacements.
So, all of these kind of things are what we're looking at.
Dasha: One of the things that I think [01:05:00] about when I'm thinking about the human performance field is to treat diseases, we have doctors, but unless you're in the Olympics, as you mentioned, you don't typically have a performance focused professional who is responsible for optimizing your health and performance, right, if you're a regular individual.
How does just a normal person who's not getting trained for the Olympics get the benefit of these advancements and techniques, practices, or even treatments that are non disease focused, but performance focused, but still impact, obviously, their health span and longevity, but you know, we don't really have someone who's responsible for that right now. How do we benefit from that as people?
Tom: Right. Well, you know, there are sources now that many people, you know, use more and more like Web MD, or you can go to the CDC for certain, you know, information on infectious disease and so forth, which is reliable. But what we're hoping to do is, you know, similarly provide a reliable place, for performance.
So the Wu Tsai Human Performance Alliance is producing, what we call, a playbook of evidence based tips and guidelines for optimizing performance and longevity, both in sport and in regular everyday life. So you can basically check the website of the Wu Tsai Performance Alliance for free updates on a regular basis, and the playbook will keep expanding as the science produces more evidence.
Dasha: Awesome. That's a great resource. And we're going to make sure that we link that right in the show notes so that it's available to doctors, patients, students, everybody who wants to benefit from the research on human performance personally.
So, in addition to your many efforts and spurring investments into biotechnical innovation, you're also a writer and a proponent of the arts, which I think is so amazing. And, last year you published an article describing an art installation in the National Academy of Sciences called blue dreams. What is the relationship between science and art?
Tom: In my view, science and art stem from the shared human impulse to create. This is something we all share. And, so an artist does not really fill a blank canvas in one fell swoop from a magical vision. They often make their way towards the craft and develop a vision in small steps and explorations, much like a scientist does.
And, a scientist doesn't just follow some boring analytical process to invent a smartphone, or build a bridge, or send a person to the moon, or cure cancer. There's often a creative process of zigzagging to a solution, deciding which direction to go in totally unknown territory, just as an artist does.
In fact, many Nobel Laureates in Science are also great musicians, as just one example of this shared creative process. You know, in fashion, fashion designers who create the clothes we all wear, they're like engineers. They assemble multiple pieces until they fit the creative vision. Everyone wakes up in the morning and has to answer the same question for themselves, which is what should I do today? And that's at the heart of of human creativity.
Dasha: Well, one idea you explore in your article is that art can bring out new knowledge and add to the comprehension of existing knowledge. Can you elaborate on that?
Tom: Yeah, in blue dreams, which is a monumental work, it was a visual display of visual art showing essentially scenes and processes from the deep sea.
The aim was to inspire people to embark on their own path of discovery by making them aware of these elaborate and really ancient processes at play in the deep sea. Processes that produce most of the oxygen we breathe every day, and a lot of the protein that we depend on for our lives. And yet, this whole world is unseen and unknown by most people.
We used art because we didn't want to use a didactic method, we didn't want to do it with a didactic textbook, but with a work of visual art. And so, in that way, you can bring people to new knowledge and new comprehension.
Dasha: And what did you personally learn from this collaboration about the potential of collaborations between artists and scientists?
Tom: I would say the main thing I learned was it's absolutely critical for each co creator, or collaborator, to actually commit to learn the thoughts and the dreams of the other, and then, approach the work of shared art science with multiple perspectives in mind. I think, too often, [01:10:00] collaborations that happen across disciplines fail because one discipline is, quote, in service to the other.
For example, photography, showing a pretty image of a cell in a microscope, or visual graphics depicting a rocket launch, or even a work of art serving as a visual metaphor for a company's main business or a social movement. These are not true co-creations. They're just techniques in service of a set vision or objective.
Co-creation requires and deserves much more extensive learning and then a fresh reflection on all sides.
Dasha: That's wonderful. And, Tom, we're here at the end of the time and I want to thank you for your time. But, is there any call to action, I know you mentioned something about investing in the Charlottesville region, that you want to call out specifically at the end of this episode?
Tom: Well, that would be the main one, you know, because, we spoke with some conviction about the Coulter program and its benefits on this region of Charlottesville, Virginia, where the University of Virginia is located. And I think, you know, historically, as I mentioned, we saw capital and confidence flowing to larger city regions because they had existing businesses.
But, I think the call to action would be, yeah, to have this new recognition that substantial private capital can invest right here at home with the talent that's here and realize the same financial and aspirational impact on the world as if they were investing elsewhere. So the call would be create on the order of 100 million dollar investment fund for Charlottesville area innovation based startups.
Dasha: Awesome. Well, Tom, thank you so much for your time.
Thank you for joining us on this episode. For all of our listeners out there, please reach out to us through biomedicalfrontiers @virginia.edu. We have had a wonderful experience in our first season hearing from a patient in India who had had throat cancer and who called in after episode four with Dr. Griffin and Dr. Daniero.
We've had several scientists and inventors reach out and share with us what they're working on. So we would love to hear from you, what you're finding impactful, if you have any recommendations for speakers or anything else that you would like to share, please reach out. Thank you so much, everybody, for your time.
David: Thank you for listening to Biomedical Frontiers, stories with innovators in healthcare. My name is David Chen and I am the Managing Director of the Wallace H. Coulter Center for Translational Research at the University of Virginia. Our mission is to help bring promising new biomedical research and technology into the hands of the provider and the patient.
If you found this episode valuable, please let us know by subscribing, following, or sharing. You can learn more about our promising translational research projects on our website. See links in the show notes.
