Breaking Boundaries: Garry Nolan’s Path to Scientific Greatness

I've had plenty of people tell me that ideas that I have will not work. I'm not going to sit here and argue with you all day. I'm just going to go back to the laboratory and prove it. Our Bay Area innovator today is Dr. Gary Nola, the Ratchford and Carlota A. Harris Professor in the Department of Pathology at Stanford University School of Medicine. He has published over 350 research articles, is the holder of 50 U.S. patents, and has been honored as one of the top 25 inventors at Stanford University. If you know you're right and you can see the steps to get there clearly, don't let somebody else dissuade you. Just do it. In addition to research, he has founded several biotechnology companies, two of which are currently trading on NASDAQ. He has also been particularly active in the study of unidentified flying objects, also known as UAPs. They said, oh, don't touch it. They said, you're going to ruin your reputation, Gary. I'm not saying I'm right about it being aliens or extraterrestrials. I'm saying it's right to ask the question. This is Bay Area Innovators, and I'm your host, Steve Esposito. Dr. Nola, welcome to our program. Thank you very much. Well, glad to have you here. So I'd like to ask, talk about some of your inventions. And the one that comes to mind is the 293T. This is a cell rapid retroval mass production. Please tell us what the invention is about and how it's applied in everyday life. So the 293T cell retroviral production system is a way to create what's called a vector, a retroviral vector that can carry genes to the target cells. It is simultaneously a way to deactivate the bad aspect of the virus and then reinvent it so that it can be a vehicle to carry the cargo of interest to us. So when I then got a position at Stanford to start my own laboratory, I decided to make what I would think of as a stable cell line. So we reinvented the cells, and they were stable. And we called them the Phoenix Lines. Phoenix means, if you remember the old ancient Egyptian story of rising from the ashes. So the idea was that DNA rises from the ashes, becomes a retrovirus again, lives again, and can be used to deliver genes. So that was the origin why we called it the Phoenix Lines. And the Phoenix Lines ended up being extremely popular because they were stable and everybody wanted them. And we probably gave them out to something like 20 or 30,000 laboratories around the world. Because I did it in a way that I rewrote the material transfer agreement that normally universities use that ends up being cumbersome and gets lawyers involved. And I just wrote a quick, easy one-liner saying, you can use this, just don't use it commercially. And you're responsible and liable for any problems you cause with them. But you can have it under those terms. And that was very agreeable to most scientists. And then it is used everywhere. And then when it was time to start to think about gene delivery for gene therapy in the human realm to fix people who might have genetic defects, then people looked upon the 293 system as, OK, well, here's a baseline. Here's where we can use this. And so then it became the system for developing retroviruses for gene delivery in humans. And that's still the case. Wow. Yeah. And the applications, talk to us about how this is used in everyday life. Is it, you know, for cancer or different? Yeah. Well, I mean, it's used to deliver genes, which can make proteins or other RNA. So you could deliver those, deliver genes and proteins. So that would be sort of the end goal in human therapy. Is this, in effect, altering the DNA? It's changing? Oh, yeah. It's changing. That's what it does. It delivers genes to cells and alters the DNA by inserting the DNA more or less randomly into the genome. It doesn't affect the germline. In other words, you're not putting it in eggs and you're not putting it in sperm. So it's not passed on to the next generation. But it is integrated into the cells that are important. People have used it for delivering genes to brain, delivering genes to the retina, delivering genes all over the place. We have visited your lab. Please talk to us about some of the things we have seen there. Walk us through the lab that you have at Stanford. So I showed you three instruments in the laboratory. One of them is CyTOF, the instrument that was sort of the workhorse of my laboratory in the 2010s and even today it's still being used. I showed you the multiplexed ion beam imager, which is a kind of spatial way of reading biopsies, in this case. We tag antibodies with metals rather than with fluorophores. So that's how we got up the number of simultaneous parameters. Maybe what we're looking at is human biopsies, looking at cancers mostly, to understand all the different cell types that are there relative to how they're positioned around the cancer. We have another instrument called CODEX, or PhenoImager as they renamed it, by the company Akoya that I started. There we're tagging antibodies with fluorophores, but we have a way of getting to 50 or 100 by doing three at a time. And we iterate three at a time. It takes a while, a couple of days, but again the data you get is so valuable. The idea behind MIBI and CODEX is that the immune system is a complex choreography of players, dancers, who are all moving in the right way at the right time to accomplish the goal of either eradicating a pathogen or fixing and removing the cancer before it becomes a problem. In fact, most people every day have mutations in their body that lead to the beginnings of a cancer, but the body's immune system recognizes it as a problem and deletes them before they become a problem. Cancer is where the cancer cell has evolved a way to evade these immune deletions. I've had actually cancer 15 times. I've had multiple melanomas, I've had kidney cancer, I've had this side of my face reconstructed twice. There's people online who say, what's wrong with Gary's face? Well, that's what's wrong. I had total reconstruction. So understanding how those cells are interacting with each other and how cancer is confusing the immune system to actually trick the immune system into supporting its growth is what this data collection is all about. We're now using artificial intelligence to look at the patterns because no human can possibly be an expert in all of the fields of biology and cancer biology required. So there's a Zen Buddhist saying that basically the flip side of the perfect question sits the perfect answer. If I ask the question in just the Zen Buddhist correct way, the answer becomes obvious. And so that's what we've been doing. The next question is more of a philosophical question. What is the most beautiful thing about DNA when you think about it? Well, to me the most interesting and beautiful and fascinating thing is the information compaction that's there. People don't really think about that. People often talk about the DNA code. One way to think about it, if anybody in the audience knows about artificial intelligence and large language models and how they compact information into just a few gigabytes, I mean DNA is only a few gigabytes. It's like three billion base pairs. Three billion individual letters does not explain this in terms of the linear sequence. So the way you have to think about it is that the DNA in the egg serves a different purpose than the DNA in a nerve cell or the DNA in the heart cell. It has all the information there. As the DNA replicates in the different cells that it becomes, it actually assumes a different function or set of functions in each cell. The way I usually talk about it is, where is the gene for nest building in birds? Is there a gene for building a nest in birds? Because people often think of the gene for intelligence or the gene for this or that. It turns out there is no gene for nest building any more than there is a gene for me liking chocolate. But what there is, is as the DNA is replicating, it is assuming a new environment. It's unzipping into a new environment using computer terminology and it's expecting a certain environment. And then it divides again and again and again. And so what's happening is, eventually what is built in the bird's brain are different cells in just the right place at the right time signaling in just the right way that has the instinct for building one kind of nest versus another. If you ever watched a nature documentary, you can see all the different styles of nest building that different birds will have. It's all built, but you have to reverse engineer the final structure of the bird's brain back to the DNA and you can't find any one place. It's distributed across the genome, as it turns out, most likely in what's called an epigenetic state. So it's not just the linear sequence of the DNA, it's the three-dimensional information of the DNA that actually has a code in it that we've yet to decipher. Could there be a deeper layer, like maybe at the top layer you see the 3 billion codes, but this could be a deeper layer? Absolutely. No, no, that's exactly what I'm saying, is that there's codes within codes within codes. The ability to understand that is actually, frankly, starting to become possible given the artificial intelligence programs that people are writing. So people have looked now, using these large language models like OpenAI and GPT and other things, they've looked at the code and they find and see vast codes and programs that at prior levels of analysis we never saw before. And so that's only just starting to become available. That reminds me of the movie or the book Contact, when the first level of information was the prime number, right? And then it was the image and then it was much more complex. And yeah, that great part where the billionaire who's funding Jodie Foster basically says to her, because they couldn't figure it out, because you're only thinking in 2D, but if you make it into a 3D, which is what epigenetics is, it's 3D, now you can basically see how all the pieces fit together. Next question is, do you see a paradigm shift in this lifetime? A scientist will not agree with the divine creation of the universe because it cannot be explained by science. Two, because I'm a top scientist, I feel that could be a god or a creator that created this because the way it's made, it couldn't have happened by itself. It's just too much to happen by itself. Well, I mean, I think that, I mean, first answer is no, I don't think that there's proof one way or the other of a god. Now, there might be. I'm not saying there isn't. I'm just saying that science doesn't say that. If you look at the structure of the universe, if you understand anything about particle physics and all the various waveforms and how the waveforms define how one particle interacts with another, how an up quark interacts with a down quark and comes together to make from a distance and all the rules down there, what you realize, whether somebody made it or not, is you have a very complex computer program that, in and of itself, enables the reality around us to be present. Now, I don't need to believe in a god to be awestruck by that, right? That the vast amount of information that we've already discovered gives us an appreciation of the complexity of the world in which we live. So I'm happy just to wait until some point in time after my time on this earth to see whether or not there's something else out there. Fascinatingly, there's actually a physicist who has experienced a bit of a resurgence. He's dead. He's a German physicist. His theory of how the universe is put together, first of all, explains what are called the constants of the universe to a great degree of precision in ways that others don't. But in putting together of his treatise, he says, look, that there's ways that matter can come together in a way that when it is in a sufficiently complex form, it can create a free living energy that, in and of itself, can live without the supporting structure. So he proposed, it's a fascinating idea, and this is probably the reason why he was kind of kicked out of mainstream physics at the time. He said, this is where the soul comes from. The soul can be explained by physics. Now, I'm not saying it's true. I just find it a really fun thought experiment where he shows that the math supports this thing. And there's, of course, your colleague from Stanford, Dr. Leonard Susskind, who I actually interviewed years ago, and his theory of this multiverse, universe, where basically I think we're saying that there's an infinite number of universes, and this one happens to be the one that all these things click. Yeah, because there might be a universe right next door where the constant, where the rule is just a little different, and so basically all you have is formless energy that never congealed into matter. It seemed like a waste of space and time, but... But you know, I mean, if it's infinite, and you imagine if you can wrap your head around what infinite means... And there's actually an interesting documentary on it I saw about what infinity means. It's called the Anthropic Principle, meaning we live in the universe that allows us to exist, but that doesn't mean that we're the only ones, because there's an infinite number of other universes where we could never be. If we were to go over there, we'd basically just dissipate or form a puddle of goo. Please tell us about your other inventions, the CyTOF and the quantum barcoding, which is, I understand, the more recent invention. Okay, so CyTOF was born out of a limitation of an instrument called a fluorescence-activated cell sorter. So Leonard Herzenberg at Stanford, professor there in the Department of Genetics, and his wife, Leonora Herzenberg, had sort of co-participated in the invention of the fluorescence-activated cell sorter. They'd already developed this instrument, and it, at the time, could not only analyze proteins in cells, on cells, I should say, with antibodies that bound to target proteins, and they had fluorophores on them, these are basically tags that you could use to read whether or not the antibody was there and therefore infer that the protein was there because it was binding specifically to that protein. But they could only do three tags at a time when I was there. And when I left their lab to go to David Baltimore's lab, I think we were up to five, and the instrument that I had used that could do two or three was ready to be delivered to the Smithsonian as part of their display and exhibit on biotechnology in Silicon Valley. So I actually signed up the last day to make sure that I was the last one to use it, and I wrote my name on the inside of the instrument. So 300 years from now, if we don't fall off a cliff, someone will say, who's this narcissist who wrote his name in there? So that limitation basically means you can only measure, let's say, four or five things at a time. And even after 15 years, they'd only pushed the number up to maybe around 10. And meanwhile, I was interested in the immune system, and there's a hundred different kinds of cells. So you need more than 10 markers to look at the majority of the cells in the immune system. And so I had been searching in the early 2000s for other ways to create tags. It turned out, by pure happenstance and luck, that there had been this guy by the name of Scott Tanner, who was a professor at the University of Toronto, who'd been emailing me saying, I have this thing. And I was like, who is this guy? So by luck, I was in Toronto at a conference, and I was interviewing literally this... He saw me and then made a beeline for me, and I'm like, oh God, who's this? And it was this guy, Scott Tanner, who would not let me leave until he explained to me what he had. And so I called Sean over, and we listened to what he had to say, and then I realized, okay, I get it. If what this guy has is right, and it's doing what he says it can do, then this is the game changer I've been looking for. And so we developed a collaboration. We took it to the next level. And then I, because of my connections in Silicon Valley with venture firms, I got funding for Scott to create a company called DVS Sciences. We got $10 million, and then later sold the company for $207 million. But what we'd done was we had created a tool that suddenly could do 50 parameters, which was such a step up. Being more than tenfold, it has to do with the complexity of how the numbers work. It allowed us to look and survey the whole immune system. We published a landmark paper in Science, not only showing what the technology could do, but then also developing algorithms, computer programs for dealing with the data. And that ended up being in, I think, 2012, Nature Invention of the Year. And so one of the limitations there was... There's the CyTOF we're talking about. The CyTOF. Yeah. Was 50 is nice, but it's not, you know, scientists always want more. And so around that time, we came up with this idea of how to use a process called split pool, which is, again, just something that's been in the literature for a while, to put it together with single-cell analysis so that we could measure millions of events, or at the very least, thousands or tens of thousands. The only limitation is not that we can't measure millions of things. It's that at the time, the costs of measuring a million things would be the whole NIH budget, which you can't do. So we set the bar a little lower. We wrote patents. We went and did some of the proof of concept. I raised money outside, proved it the case, sold the company to Roche, spun it out again as another company, because they satisfied themselves that it worked. They said, okay, but our objectives have changed. So some venture firms had approached them and said, hey, this technology that Gary invented is foundational. We have some other inventors who have some tricks that they can add on top of that. Let's put together another company, and that's scale. And scale now has products. They can do some pretty remarkable stuff. They can not only use it for proteins, but they can use it for RNA, they can use it for epigenetic states in cells, et cetera. So it took 12 years to get it to this point. I've had plenty of people tell me that ideas that I have will not work, and my response is usually, okay, well, if you don't see the future I see, I'm not going to sit here and argue with you all day. I'm just going to go back to the laboratory and prove it. So that's, I mean, and that's usually what I tell students is don't feel you, if you know you're right and you can see the steps to get there clearly, don't let somebody else dissuade you. Don't let them demoralize you. Just do it. Yes. That's great advice. What keeps you motivated to do the work you do, to continue to do the research? What is the top element that keeps you going? I hate seeing opportunity wasted. I get a kick out of seeing somebody else do things better and then get lost in the data. I want to give people so much data that they feel like they're swimming in a sea of opportunity themselves. Speaking of that, you formed several companies, two of which are at NASDAQ, maybe there's more going to be there. How do you have time to do a research that you do and at the same time run or create these companies? I think you have to understand how it is that ideas flow from the laboratory to the commercial marketplace. Scientists are great at producing ideas. You create an idea, but if you see value in that idea, the NIH is not going to fund it. They funded your basic research. They're not going to fund putting it into commercial. They need another kind of risk taker. That's where venture capital comes in, where if you can formulate your idea in the right way and show that there's a commercial possibility, they'll put in money so that they can make money for their investors, who end up being actually often the taxpayers, not through their taxes, but through their funds for retirement. That money then goes towards testing if the idea is valid and viable, but then creating a commercial version of it, because a laboratory version is basically tinker toys compared to what the commercial version needs to be. It needs to be foolproof. It needs to have instructions. It needs to do the work that I would normally have to do to teach another laboratory, but all in a single, simple package. When the VCs step in, they bring a level of company maturity and then the funds and the ability to find professional company managers to do it for you. The scientist has two options when they create a company. One, they leave their position and go be in the company. Then that's going to be it. That's it. That's usually it. Sometimes if you're amazing, you get a chance to come back. Or you stay and you basically give over your baby to the venture capitalist. I would say to any startup professors who might be out there is be prepared to step away or be prepared maybe to be pushed out. Once you hand over the idea, they don't necessarily need the founder there nagging them about how they should be doing things. What you do is you're giving it over. You say, call me if you need my advice, but I trust you. Like with children, you invest your mental energy into giving them the ability to go out and be themselves in the world. The same thing with companies. At least I do. Start multiple companies. I've had a couple of failures, but the majority of them have done quite well. That's how you do it. You do it by not doing it. I don't run them. I also wouldn't go to them because I'd be fired probably in a week. I hate people telling me what to do. I mean, I'm probably the worst employee in the universe. Dr. Nolan, thank you so much for your time. We'll be back with you next week to follow up on this discussion. Great. Thank you for watching another episode of the Bay Area Innovators. If you like our show and if there's someone you have in mind who should be on our show, please send us an email at sfbay.epochtimes.com. We would love to hear back from you. Thank you so much, and we'll see you next week. I once went, I was in such a rush to get to the plane one morning, and I went all the way to Stockholm, Sweden in my slippers. And I got there, and the taxi dropped me off at the wrong hotel. It's winter. Oh, okay. And I had to walk through the snow a few blocks in my slippers. There were no shoes or anything in the airport because I had to buy things in the airport. I had to buy clothes in the airport one time. No, it was San Francisco airport, so there are no shoes. And the Stockholm airport doesn't have shoes. So, I mean, relatively speaking, it's a small place. Right. Are you all set? Yeah. Okay. Hold on one second, hold on one second. The 293, it's a little bit... And I did that twice, by the way. One time I did it, I went to New York as well. I had slippers. It's not a good time to laugh. You have to laugh at yourself. If you take yourself too seriously, other people will laugh at you. You might as well beat them to it. Might as well beat them to it. Exactly. Okay. All right, gentlemen. We are rolling. One, two, three.