22. Funding Founder-Led Biotech w/ Tony Kulesa

In this episode, we interview Dr. Tony Kulesa, a Principal at the VC firm Pillar. We talk to Tony about his work to open source the biotech company creation process, overrated and underrated investment theses, reading and writing to all the different scales of biology and more!

To learn more about founder-led biotech, check out some of Tony's writing on the topic here.

For more information about EBRC, visit our website at ebrc.org. If you are interested in getting involved with the EBRC Student and Postdoc Association, fill out a membership application for graduate students and postdocs or for undergraduates and join today!

Episode transcripts are the unedited output from Whisper and likely contain errors.

Transcript

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Hello, and welcome back to EBRC in Translation. We are a group of graduate students and postdocs working to bring you conversations with members of the engineering biology community. My name is Andrew Hunt, a recent PhD graduate from the Jute Lab at Northwestern University. And I'm Fatima Inam, a postdoc in the Sonnenberg Lab at Stanford University. Today we are joined by Tony Kulesa, a principal at the venture capital firm Pillar. Tony previously co-founded Petri, a startup accelerator working at the frontier of biology and engineering, which merged with Pillar to become the basis of their biotech practice. Prior to his current position, Tony served as the founding director of the MIT Biomaker space and as an instructor at the MIT Department of Biological Engineering, where he taught courses focused on biotech and entrepreneurship. Thanks so much for joining us today, Tony. Hey, thanks for having me. Glad to be here. So to get us started, can you tell us a little bit about yourself and talk about your path from PhD into venture capital? Sure. I guess where do you want me to start on that? I could go, you know, how many generations back? Maybe tell us what you got your undergrad in and then how you got into grad school, what shaped your decision there onward. Sure. Well, you know, I come from a very engineering heavy family. My dad is an electrical engineer. Went to college kind of expecting that's what I would study, but I got quite frustrated with being on like the 30th edition of the textbooks and things like that and just wanted to go to a place where they like couldn't write the textbooks fast enough to keep up with the state of the field. So, you know, biology, I could see that happening and it just felt like whatever the impact of computing had had in 20th century, you know, perhaps bioengineering would have similar kind of scale of impact in the 21st century. And of course, like I did my, I started my undergrad in 2008. So, you know, I graduated in 2012. The deep learning revolution was like 2012 ish. So like, I think had I foreseen, you know, some of the coming advancements in machine learning might have stuck around, but I think, you know, I still feel like that was the right choice to move into biology. So I ended up doing my undergrad degree in biomedical engineering, math and Chinese and the Chinese, my girlfriend at the time who's now my wife is Chinese. And so like, it was just fun to be able to, well, she's Chinese American, but it was like to like, it was fun to like learn a language she spoke to with her parents and so, which don't ask me to speak Chinese today because it's about 10 years out of practice now. It was a good breath of fresh air. I ended up coming to MIT in undergrad for a summer to work with Linda Griffith and Doug Lauffenberger. And there were two key figures who had built the bioengineering department at MIT. So I just fell in love with what they were doing there. I think one of the key things was that it was biological engineering as opposed to biomedical engineering. And that was a very purposeful name because they had this vision of instead of, you know, applying other fields of engineering, like, you know, mechanical, electrical, chemical engineering to biology, you know, and often thinking about that in a medical context is instead was an effort to create a new discipline, actually, like of treating biology kind of as like a first class object. And I was really attracted to this idea of like engineering biological systems, which then could go not just impact medicine, but everything. Like, you know, if you look at all the things that are in front of you on your desk, like how many of them are biological in origin, like I'm sitting at a wooden desk, for example. My clothes are made of, you know, cotton, probably, and it extends far beyond just the human body. So I just loved that and I loved doing research. I came back to grad school immediately after finishing undergrad. I came back to MIT to do my PhD and also kind of ended up at the Brode Institute working with the newest faculty member at the time, who was Paul Blaney. And I really wanted to be part of the creation of a new lab. And so, you know, Paul was a super nice and smart guy. And so I was excited to join him as one of the first kind of students in the lab, which was cool because we like we didn't have glassware, like we had nothing. And it was an interesting time at the Brode, which was kind of founded around this idea of bringing genomics to all these other areas of science and medicine. But I think they could kind of see peak genomics on the horizon. And we're starting to invest a lot more in inventing the next kind of generation of technologies that would be as impactful. And the two, they start, so they start hiring a lot of more engineering minded people. Paul and Fung Zhang were the kind of two new faculty hires at the time. And so Fung had brought a lot of the genome engineering and kind of microbiology. And Paul was like all of the optics, genomics, microfluidics, lab automation. And it was interesting because I just went around to like every other lab at the Brode Institute and just sat in the front of every talk was the guy would just ask like all the annoying questions, follow people around like, what are you doing, you know, why do you do it that way? What if you did it this way instead? And I tried to build a bunch of new tools for drug discovery, infectious disease research, functional genomics, like you name it. And so our lab, that was kind of the mission. There was no like kind of central organizing principle other than just build a bunch of tools based on the needs of the people that we had around us. And I, from that experience, I learned that, you know, I didn't really want to, I feel like academia, I love, I loved, you know, being an academic scientist, but really it's this game about like citations and grants and things like that. And I didn't feel that motivated by like publishing papers, getting citations there. I just want to talk to you. Like, I don't care about publishing paper, but I can just hand you something and see how you use it and whether it's useful to you like that kind of direct feedback rather than arguing with an anonymous referee seems so much more fulfilling. So I started going around to being kind of like the pitch guy for a lab. Like I just asked a bunch of other professors, like, hey, can I come present your group meeting? Like present like all the stuff our labs are working on and I would try to start collaborations, try and get them to use technology and give us new ideas for what to do with it. And then I realized that why stop there? Like why not go talk to all the local biotech companies and see if they'll start like sponsored research agreements. And I realized at some point that what I was doing was like not what an academic does is doing like something more like an entrepreneur does. And so I started thinking a lot about starting companies. And it was really surprising at that period, which is not that long ago at MIT, which trumpets itself as this like very entrepreneurial institution. And I started telling people like, oh, I want to start a company. And almost universally, the feedback I got was, what are you talking about? Like you're a grad student, you know, you don't know anything. Why are you trying to start a company? You can't do it. You can't start a company. It's not how biotech works. You go work for some of the fancy biotech VCs and you could join an associate and you can like help out with ideas and like maybe you'll move horizontally in one of the companies. Or you could be an academic and you could be like a scientific founder of the company, but you like kind of stay on your academic track and kind of consult for the company. And I think there's merit to the purchase, but I don't think it excludes that you can't do it a different way. And so I end up joining up with like other friends who had similar ambitions and we started a bunch of student organizations, classes, we even built a lab space in a basement that could be like an incubator of sorts. And just trying to learn and try and resource ourselves as we had these ambitions in certain companies. And I wish I had invested in some of my friends there because like they built some incredible companies that have come out of that circle. And I just realized that this kind of transition that was happening wasn't isolated to MIT. It was just knowing that what I mean by this transition is that like it was very uncommon for grad students to be like, I'm going to go start a company. And then all of a sudden it just started happening. And now there's a bunch of like success stories of people doing that, which inspires many more people in their footsteps. And I realized like that was happening everywhere. And I looked at the scale of the opportunity there, I guess, and there's like 150,000 academic life scientists. There are more than 10,000 PhDs graduating per year in life sciences. There's 86,000 active NIH grants. And if you compare that to the number of total biotech companies that are formed successfully, like successfully raised seed rounds or series A or something every year, in 2022 there's only 200. Wow. So I'm like, what? There's like this giant gap of there's these all these people. For the first time, academic culture is changing where these people don't want to be academics. They want to go start companies. And by the way, that's not an endorsement to say every single person that wants to start a company should start a company or like, but I just think if you believe that of all this opportunity, there's only 200 companies that could really be formed every year, I think you're wrong. And so how I kind of entered the world of venture capital is how do we enable this kind of growth of this ecosystem by open sourcing all the knowledge of the biotech industry, hooking people up with the right network? Like, what is the experience that you get when you go inside of one of these firms and like see how they build a company? Could we just open source all of that and give that to people from the start? And then would that lead to many new companies coming out? And so that's what I've basically been doing for the past four years as an investor with the concept of trying to build all of those tools, knowledge based networks to resource people. And, you know, if we can invest in a few of the companies that come out of those efforts every year, we'll do very well for ourselves and for our own investors and we can recycle those kind of winnings back into continuing to fuel the growth of the ecosystem. And so I feel like that aligns very well with like the job as an investor. So that's, that's how I kind of made, you know, decided that that's what I should do. Very cool. Super interesting. Thanks for sharing that. We do see this academic culture changing, especially in life sciences. And one thing I was curious about, especially with your work being focused on the founder-led biotech, maybe for our listeners, could you explain what that means and really what drew you to this type of model? Sure. I would say as a disclaimer, I'm not very good at naming things. I tend to just name them quite literally, right? And so we just call this the founder-led biotech movement to kind of name this grassroots kind of cultural change that we're seeing sweep academia and biotech, where you have all these scientific founders who want to take the reins of the work that they've done and help spin it out. And I think that that at the scale, like, of course, you can always point to examples in history where this has happened. But I think the scale at which we're seeing this shift is new. And that's what we've tried to label this. And I'm sure that it doesn't completely describe it. And I don't mean to say put a fence around who's a part of that and who's not. But I just think that there's this general kind of cultural change. And there's a lot of different sources for that as well. So yeah, what I mean to distinguish that from is most of the headline grabbing kind of companies that you see in biotech are created by VCs in partnership with academics. And going back to the origin of the biotech industry, that's how Genentech was formed. Bob Swanson was a VC, Herb Boyer was an academic, Herb Boyer remained an academic, a bunch of post-docs from his lab joined the company in kind of scientist roles. Bob Swanson ran the company. If you fast forward to how a lot of the companies that are biotech today that you see the headlines about, same model, it's like VCs call up an academic, figure out what to do with technology, either run the company themselves or go hire outside executives. And I think there's built lots of great companies and there's lots of room to keep doing that. And I don't at all mean to say that that's not a good model, but I think that it's undeniable that there's this huge kind of sweeping change happening among younger people in this industry who want to strike out and do it themselves and are sharing all of the knowledge that they're accumulating. So it's not living in these kind of institutionalized walls, but it's open sourced. And that enables more and more people to follow in their footsteps. That's what we've labeled this kind of movement, this founder-led movement. Cool. One of the things I've been wondering about this, and as I sort of move on to next steps in my career, is if you think that something like this creates better alignment between company creation and maybe societal value, I'm wondering if having founders lead the company, you end up with outcomes of the company that are more closely aligned with targeting the really challenging problems in society. So things like pandemic preparedness and antibiotic resistance, these types of problems that have been maybe a little bit more difficult to commercialize in the past. Do you think that maybe founder-led will get us there or at least get us a little closer to tackling some of those problems with companies? It's hard to say. And I think that we'll have to see how that plays out in the data 20 years from now or something like that. And I think certainly great companies that serve great problems in the world can be built in any way. And I'm sure if you look at any successful company that's made a big impact in the world, its own idiosyncratic story, right? I think overall, we just ought to have more shots on goal. In my view, considering the power that biotechnology has and the scale of the problems that we want to attack, healthcare for an aging population, we really don't have great shots on goal on lots of the kind of diseases that people are afflicted by. And beyond that, not just the aging population, the overall population, rising fertility issues, our climates, pandemic preparedness, as you said. I don't think anyone could look at those problems and say they feel great about where we are. We all just have more shots on goal, more voices, more ideas. They can come from anywhere. So anyone that can figure out how to resource more people, no matter who they are, to have ideas and try and execute on those ideas, I think it's a great thing. And so I don't think this is like a zero-sum thing of what's better about one approach or another approach. I just think we just need more total approaches and more total successful approaches. So yeah, that would be kind of the way that I think about it. Yeah, I like that. More shots on goal. That makes a lot of sense. So I want to transition a little bit towards your work at Pillar as a principal now. So beyond this founder-led paradigm, what are some of the other core principles of your investment thesis and Pillar's investment thesis? Sure. Well, look, I think that we look at the history of biotechnology and or engineering biology. The fundamental shift that kind of created the biotech industry was that you could read DNA at least in small pieces. That was kind of what led to Genentech, it was recombinant DNA. And what preceded that was being able to like sequence small bits of DNA using the kind of Sanger sequencing methods and the peptide sequencing as well. That's kind of how they figured out insulin and things like that. So you have to look at biological systems as these kind of hierarchy of kind of components of increasing scale or power. That's the thing that's kind of unique. Like physics, usually the small things don't interact with the very big things, the big things don't really interact with the very small things, or else you wouldn't be able to do physics. Like most of physics is about like separating scales and trying to analyze the problem in its own kind of domain. Biological systems are the opposite. Like the very small things interact with the very big things and vice versa. And so if you look at like biological systems, they're the biomolecules at the bottom. It's like the small molecule, like the biomolecules, the metabolites, DNA, RNA, proteins. Then there's and of course all the other biomolecules, there's organized into cells, which are organized into tissues, which are organized into organisms, which are organized into ecosystems. And so the shift that came into like thinking about this as an engineering field was being able to kind of interface or like read and write with one of those components, which is like DNA. But the broader trend has been our increasing ability to read and write to like each one of those layers. So you have the ability to also measure RNA and we have the ability to write RNA. And like you've seen that with mRNA therapeutics, but also likes all the small RNA kind of approaches as well. And we're discovering even new classes of RNA. You see this with proteins, like you can measure proteins with like mass spec or new kind of approaches are coming online. We can predict their structures with alpha fold like approaches. We can cryo-M is going through this whole revolution. We can also learn how to kind of program them in a sense with like these induced proximity systems like degraders. But people are coming out with all kinds of new second and third generation approaches there to induce like phosphorylation or acetylation or like, you know, do this inside the cells, outside the cells, et cetera. You know, you can see this at the cellular level, right? Like we all the kind of spatial omics technologies to kind of read cells in tissues and how they interact. But then also engineering cell therapies, like we kind of have the ability now of programming simple genetic circuits, programming simple cell behaviors and that's allowing us to reprogram our immune system and other, you know, other kinds of cell types. And then even that whole organism scale, like, I mean, microbial, it starts with like microbial therapeutics, like you're literally using like whole organisms as reprogram whole organisms and then similarly in the kind of work that you guys do, like engineering biology, like about the implications of that, like by manufacturing and food and agriculture and that. And then, yeah, and then I think these impacts even have across whole ecosystems. And so I think like what we see is this kind of broader change as thinking about every single layer of these biological systems as engineers, how do we read them, how do we write them? And that leads to, you know, if you thought that reading and writing DNA led to like the entire kind of biotech revolution in the 1970s and 80s and so on, that change is accelerating dramatically and it's leading to all kinds of, you know, new therapeutic modalities. It's leading to all ways of reading and writing, like the kinds of things that we interact with the nature, our food, our materials, our own climate. And so that's that's what we're excited about at Pillar. Reading and writing at all levels of biology. I like it. Super cool. Maybe on that note, what do you think are some of the underrated and overrated investment pieces? So that's a really good question. So let me start with the overrated and give myself some time to think about what I would say is underrated. I mean, so overrated, I think if you ask anyone in the industry, we really don't have good solutions for delivering a lot of the things that we're excited about. I mean, this started all the way back, like I remember, you know, when I was at the Broad, that was like when the first kind of CRISPR technologies were like, you know, there's a lot of fanfare of that and Editas and I remember there being a lot of criticism of Editas of, well, how are you going to deliver? And it was kind of like, well, we're going to figure that out and when we figure it out, just think about how much value we're going to unlock. And like, they still really haven't figured out delivery, right? And it's like 10 years later now. And so, you know, you see that same pattern now in a lot of companies that are still like, well, if only we could figure out how to deliver this and someone's going to figure it out. And when that person figures out, like we're going to have the greatest thing, you know, since life spread to deliver. And so I think we should kind of think carefully about that overall. And we are starting to see a lot more development in the space, a lot of new academic technologies, a lot of new companies. So we'll see how that plays out. I think delivery is still like one of the real big fundamental challenges in biotech. That's so I don't I don't want to say overrated, but I want to say, like, until we can figure out delivery, I think there's a lot of biotech, which is going to be dependent on figuring out new delivery modalities. Yes, like what's underrated. And I think I think something that's really underrated is international talent, actually. You know, if you look at where venture capital dollars are allocated, it's mostly, you know, Boston, San Francisco. Of course, there's a whole thesis there. You're just looking at the United States. You know, if you look at where all the NIH dollars are relative to where all the venture dollars are, you'll see a massive disparity, right? Like, there's obviously a lot of NIH funding that's going into many other places and creating like a lot of great sciences result by the great scientists that work there that aren't in Boston, San Francisco. But the broader thing I'm actually really interested and excited about is is like there are a lot more people in the world than just people in the US. And I think that the fields that are purely kind of computational or purely kind of theoretical or something have discovered this because you don't need a lot of resources or you can like learn programming online, for example. And so, like, I think the fields like machine learning have discovered, like, there's a lot of people in all around the world who are amazing, who you can find like via the Internet just based on like GitHub or something like that. And in biology, it's so resource intensive today that like you haven't seen that. But I am actually really curious to see as we see more kind of computational approaches having more and more reach in a biological system. And like more of the people who are trained in those fields, like working on biological problems, will we start to see some of the best talent in those fields be in places where nobody's looking and where do you find these people and how do you resource them? So I think that's a really interesting thing that I haven't seen a lot of people talking about, and therefore I'd say is underrated. All very interesting. I'm curious now about a little bit about what your day to day is like as a venture capitalist. I think probably most of our audiences is maybe more towards the graduate student end. And so we'd be curious to hear about what your day to day is like and what what you like about your job and maybe what you don't like about your job. What is my day to day like? I mean, I think you could even kind of try and think about venture capital as maybe five kinds of collections of things or something. The first one is trying to find investment opportunities, broadly called sourcing. The second one is trying to pick the right investment opportunities. The third one is the difference in venture capital between like, you know, picking stocks on Wall Street or something like that. It's like the stock has to choose you. You can't just like, like people have to let you invest in their company. It's not, you know, doesn't necessarily it goes both ways. So I think there's a third thing, which is kind of like, you know, actually finding, agreeing on a deal or something with the fourth one is supporting the companies. It's like most VC firms have some level of support, you know, to varying degrees in how they work with their portfolio companies. And the last part would be internal operation and, you know, fundraise like a VC that are not investing their own money. So you have to fundraising, you know, you have to recruit for your own firm and, you know, all the kind of work that goes into running your own business. Like, so, um, I mean, where are your small firms? So I feel like I've at different points in my time, like done all of those different things and on any given day, I'm kind of doing different levels of those things. But I mean, I would say I, the thing I love most is, I mean, I, I really, I'm a hyper curious person and I'm quite extroverted and I love talking to scientists about what they're working on and trying to pitch them, you know, some of my own half-baked ideas and, you know, like, I mean, I love kind of high temperature bouncing around, like, you know, like a particle and like a hot, it's bad to call myself hot air, which yeah, I'm like some hot air, right? Like, I love just like bouncing around all over the place and like hearing how people are thinking about introducing them to each other, talking about ideas. I mean, that's the most fun part of, of this. I mean, I mean, the least fun part, email, I don't know. It's like a lot of email. I don't know. It's very object level. Uh, no, I mean, the least fun part is like, I would say one of, one of the challenges of venture capital is that, and you know, there's a reason why there's a lot of criticism of the industry and there's, and there are good reasons for why it is, sorry, they're not good reasons, but I mean, there are reasons why it is, is what I mean. And I think one of the challenges of, of biotech and of venture capital in biotech is, and they see this in tech as well, is that very few groups have enough capital to kind of bring a company all the way to fruition where it never, never ever needs to raise money again by themselves. Even the biotech firms that have billions of dollars under management, they're still co-investing still in companies go public. That's still kind of like a financing event more than it's like a liquidity event and the company will continue to raise money, even in public markets. And because of that reason, you can't be too kind of contrarian. Like you can't, you kind of have to be funding things that, you know, other people will fund as well, because you're going to have to go convince them to fund it and it may be 18 months from now, maybe five years from now, you know, depending on how much, you know, what, what dynamics are, but, but like, you're still reliant on what other people want to buy. And I think that that, that's one reason why there's not as much risk taking as there could be, because there is this kind of social element of this, like panopticon element of everyone looking around thinking, what else are you going to, you know, what are you going to do? And that creates this kind of herd mentality. And so I wish we could live in a world, and maybe we will someday where, you know, like, like you've seen with internet companies where you may only need to, you know, you don't really need any resources to launch something and start seeing, start seeing it grow. And then I think we'll live in this kind of Cambrian explosion of new ideas. And I'm really excited to see that happen hopefully in our lifetime in some way. But I think that would be like the hardest part is thinking like, wow, this is amazing, but it goes against the grain too much on what I think other people would be willing to fund and therefore not knowing how to, how to make that work. For sure. And then staying on that funding note, we did see the venture funding in biotech peak in 2021. A lot of companies went public, but now we're seeing layoffs or like cutting down the pipelines or even shuttering of companies. What can we expect to see in the, in the coming months? I'm not sure anything is going to happen in the coming months, other than, you know, there is currently a banking crisis, which is kind of like playing out real time, like those kinds of things. I mean, the level of venture capital that's been raised in 2022 is still quite a bit more than in 2020 and double the amount in 2019. So like, there's a lot, there's still a lot of money out there. Right. So I wouldn't say that I expect anything to change in the coming months. You know, what is the broader trend in by 2025? Are we back down to like 2019 levels? Are we down to 2013 levels? I mean, like that, that would obviously be a dramatic change. I don't really see something changing in the coming months though. And by the way, I don't expect it to be, you know, I expect it, you know, to probably to continue to go down a little bit, but not, you know, fall off a cliff. But, you know, that, who, that, who knows? Like who can predict more than, you know, six months into the future and think it's very hard. Well, speaking of looking into the future, when I was prepping for this, I'd listened to some of your previous interviews and you'd mentioned liking to ask people about sort of what's the most important question in the world. And so I wanted to ask you a little bit, like looking 10 to 20 years in the future, what do you think like the most important questions we should be solving with, with companies are and what should the engineering biology company landscape look like? Well, you know, what is the most important problem or something like that? I mean, I, I do think that this question of how do we unleash a lot more talent and ideas and technology and problems and things like that in biotech. Cause I, I do think like the most, many of the most important problems in the world are biological in some sense. And I don't think we have enough kind of brain power or like working on different ways that we might solve those problems with biology, like even for example, if you go in into most academic labs, like most people are still working on therapeutics, I mean, I think biotech can be hugely impactful in agriculture and feeding our planet and helping elevate living standards, everyone on the world in the same way in combating our climate. And, uh, and I know a lot of people in academia that are really passionate about these areas. And it's just like still the problem is most of the funding comes from NIH, so you're kind of stuck, like, how do you work on that when there's no funding for it? You know? And so I think like, I still think like trying to unleash more talent in those directions is really an important problem to working on, you know, and I still believe this and I still think about this for, uh, this is still the primary mode, but you know, because you're asking me in March, 2023, like how do we envision like the landscape is going to change? I mean, it's very obvious, or it seems very plausible, I'll say that AI is developing at an extremely rapid rate and is going to impact a lot of things in the world. And so I think we can't ignore that in both positive and potentially dangerous ways. And so like, you know, if you ask me like, what's one of the most important areas of working on, like what's the most important area? I mean, I'm usually not one to run with the herd, but I mean, I have, I have been playing with a lot of these tools. I do think a lot of the leaps are real. And, uh, I think it is plausible that like, that is the biggest lever that we have on a lot of problems, but also to be able to do, to apply those tools safely, I think is a big challenge. And so I would definitely really encourage people. We also need a lot more brain power working on AI safety. So I think like that's, that's something in this particular moment, in March, 2023, that's something I'm definitely thinking a lot about as well. If you ask, if you, if you just ask my opinion, what's the biggest problems in the world right now, I'd say, yeah, that plausibly, one of the biggest problems of the world is that we don't have enough people working on AI safety, myself included. Yeah. Yeah. Definitely feeling both of those things, expanding the impact of biology beyond therapeutics and AI for sure. Which by the way, they have lots to do with each other. I mean, I think in some ways this is going to be like a very impoverished analogy, right? But like, if you were a physicist in like what you're is calculus, let's see. In 16, in this, in the mid 1600s or whatever, and you're talking about like physics, like pre-calculus or just post-calculus or something, like there's obviously a huge shift in our abilities to do physics and analyze physical problems in the world with the invention of calculus. And, and I feel like biology is actually kind of in that moment where for whatever reason, in reasons which are completely mysterious to me, to, I think everybody, the world is physical, like, you know, the kinds of like non living matter systems are like pretty well described by close form, you know, equations that are quite simple in nature. And it's amazing. This is just like this, you know, unreasonable effectiveness of mathematics that I forget who coined that term. I think it was Wigner, uh, Eugene Wigner or something like that. You know, mathematics has not been unreasonably effective in biology. Like I, at least as like a first class kind of like, of course, like there's physics and biology and there's chemistry and biology as well described by, you know, mathematical techniques, but, but biological systems have not really lended themselves to close form kind of equations. And, and so it does seem like you need some new paradigm for understanding biological systems and there's no reason to believe that like a human brain could look at these biologic systems and be able to compute their, what they do or predict what they do or engineer them, how to engineer them. And we've tried to come up with kind of our own algebras for like, you know, especially in your guys' world, like, you know, the engineering biology, uh, groups, right? Like we've tried to come up with ways of like describing gene circuit stuff, but everybody knows that like they're impoverished and like there are all kinds of like weird things that happen that they aren't completely described by like our representations of these systems. And like, I mean, there's lots to be excited about the fact that like machine learning is like basically couldn't be, there could be a better fit for these kinds of systems in a way that, uh, they're constructed. So assuming we can like measure enough of the right things. And so I feel like we are in that kind of like pre-calculus post-calculus kind of decade or something for our ability to engineer biological systems. So I know there's like a lot of hand waving and hype there, but like, I mean, I'm seeing, I'm seeing the capabilities develop in real time. It's like among like, you know, lots of our companies are like, you know, lots of the, you guys do. And, and it's, it's very obvious that like there are problems that are just like falling like dominoes that people have been like longstanding. And I think that's the trend that will continue as much as, as much as we can like generate the data to keep up with it. Yeah, cool. And finally, Tony, do you have any career advice for students interested in pursuing a career in venture capital? Yeah. So Sam Altman has actually a really good essay on this, which is, and I know it, yeah, he's a tech guy, whatever, like biotech VC is different than tech. I actually, everything still applies from this essay and it's, I think it's called like how to invest or something. You should go read it. You know, the basic, the basic key way from that essay is just like, just, just start, just find ways to start doing the job like, and, uh, I previously in our conversation, we kind of talked about what is my day to day and it's like all these steps of like finding investment opportunities, like picking them, like trying to like actually win, you know, a deal that, that works both for like an entrepreneur and for us, then also supporting the companies, all those things in different ways are things that you don't need anyone's permission to do. And I, and again, like not everyone has the flexibility to do. So like that being said, I totally understand that, but for the people that have the flexibility and I expect there are many people with, you know, with the interest and flexibility to do it is like what Sam Altman's advice is just like, just like asking, like who, you know, which, which company, like if you have an expertise in a certain area, like which company could you try and help what, or go find investment opportunities and just like try and send them to investors and be like, what do you think of this? And I guarantee like 99 of a hundred, they're going to be like, they're going to tell you they don't like it and then ask them why, and you'll get that experience, like, you know, you'll start to get a lot of experience of like, why do investors stick this way and you'll start to learn and improve, start trying to figure out, oh, like, you know, who, who, who needs to be hired, you know, in these roles at these companies, can you go find those people and send them, like if you start kind of doing the job, like, and you've, you've become good at it because you're like constantly asking for feedback, you know, people will start to take notice and I think one of the really under recognized things is the power of like social media as well. Like there, there's a bunch of people who are just putting out like really great essays or analysis or like market maps or things on Twitter and everyone in the investment community knows them and is paying attention and getting a lot of their ideas from them. And so I think like, you know, you don't, you don't need any less permission to do it, right? Just like start putting yourself out there more and, and just find ways to keep improving your ideas by getting feedback. And I think like, uh, yeah, that'd be my best advice. By the way, there are lots of VCs that have like paid fellowships and things like that, like we do that. I think there are probably 20 other firms that have like paid fellowship programs to try and find ways to do that. There's always like ways you can consult for companies. Like none of this has to be like unpaid in any way as well. So, well we're running out of time here, Tony. So thank you so much for coming on the podcast. It's been a pleasure talking with you as, as we wrap up here. Is there anything you'd like to promote before we finish up? No, I, yeah, I mean, check out our website. We have lots of resources and stuff for people that are interested, uh, in, in Sarah Epsom BC, but I'm just glad to be here and great to have a nice conversation with you guys. Thank you. This has been another episode of EBRC in translation, a production of the engineering biology research consortia's student and postdoc association. For more information about EBRC, visit our website at ebrc.org. If you're a student or postdoc and are interested in getting involved with EBRC student and postdoc association, you can find our membership application linked in the episode description. A big thank you to the entire EBRC SPA podcast team, Fatima Anam, Andrew Hunt, Ross Jones, David Mai, Heidi Klumpa, and Reena Saeed. And thanks to EBRC for their support. And of course to you, our listeners for tuning in, we look forward to sharing our next episode with you soon.