Redefining the Undruggable Through Proximity with Armand Cognetta

Welcome to the Bitson Bio Podcast, where software meets science to shape the future of human and planetary health. We're a global community connecting computational experts and life scientists accelerating breakthroughs in drug discoveries, synthetic biology, precision medicine, and MDOT. Join us as we explore the people, ideas, and innovations driving the bio-economy forward. Today we're joined by Armond Cogneta, Founder and CEO of General Proximity, a cutting edge biotech company developing next-generation proximity medicines to tackle targets the world has written off as impossible. Armond is a Scripps Research-trained chemical biology PhD, with over 15 years experience in drug discovery and proteomics. His really fascinating research is contributed to a foundational IP for multi-billion dollar acquisitions, including a bi-therapyutics, which is acquired by Lundbeck for a thing about a quarter billion, and the Vidion, therapeutics, which is acquired by Bayer for over a billion. He's also created drugs that reverse aging and mice and let international investigations and clinical trial safety. After going through Y Combinator as a solo founder, Armond has been building General Proximity for over four years, recently coming out of stealth with $16 million in funding and breakthrough proximity medicine technology. Armond, great to have you on the show and welcome. Thanks guys, it's really awesome to be here. Armond, if you can just start off by going into your background a bit more, you have very interesting array of experiences being the first intern at Al-Maila. Maybe you can talk about that story a bit. Sure, yeah, so that started, I don't know, I was in college and I was kind of lost really actually with what I was a chemistry major to start off and I wasn't, didn't feel super connected to what I was doing. And sort of serendipitously got really through no marijuana got opportunity to intern at Al Nylon and I was put really there very first intern they've since started internship program and is still going on today. But it's just a really special experience to go to a company that's like that was building a super cutting edge platform really outside of the norm at the time, especially. And see what it was like to just work there to do science that felt directly impactful to patients as opposed to when I was, you know, chemistry major, I kind of was memorizing reactions that felt like they were from 1800s and you know, it didn't really feel super creative. And so I got I got opportunity to do it. I felt like was for the first time in my life like really cutting edge translational high impact science and it really changed my life and I got obsessed with building platforms and I really think the kind of platform company that Al Nylon is where it always bugs me that there's no. Kind of differentiation between a pure platform company and a platform company developing the own assets, but I know this is very much the latter. And it just was the best place to work. It was so cool to see how like if you can actually, you know, mature a new technology things that weren't possible become possible. And I think that's really how drug is covered was forward and the most exciting place to be and where all the real value creation is. So I've seen it really impacted me and that I've spent the rest of my career not in RNAI but at least in like platform companies building platforms and a lab that has built a bunch of platforms. And so that's really my kind of obsession is building platforms and then using the platform to make drugs, which I think like if you're actually building. If you're actually building a real cutting edge cool platform, you should be making drugs with it or else you're you're almost like fooling yourself as to the value. If you're just, oh, you know, let's get big farmer to pay us to use it and we won't we won't do our own development. So tell us a little bit about the exciting work you've got going on now at proximity medicine. You guys have been building for over half a decade and very stealthy about what do you guys do and how is it better than the stuff that your contemporaries might be there. Yeah, so we're solving what is, you know, potentially the biggest problem in drug discovery, which is that there are many well known drug targets. Where we know they're, you know, causative and some disease and we just like the technology to functionally modulate them in a human. So many well known targets like this am newly discovered once. It's a really major challenge. And the way that changes is, you know, kind of new platforms, new technologies mature and then suddenly things that were possible become possible. So that's what we're doing. We're building basically fundamentally new class of medicine so that, you know, what works through this principle called induced proximity. And it's a lot of what we're doing is built off the back of a field called target protein degradation, which is the first sort of instance of this. Which is a really interesting field that enables you to use small molecules to degrade a drug target, which is really revolutionary. The only clinical technology that lets you systemically control the abundance of a protein in human nothing else lets you do that systemically. And the way it works is through proximity basically a normal small molecules binds to a drug target and usually is an inhibitor except for maybe GPCRs. It's just the general principle is easier to break things and just to fix things. So a lot of drugs inhibit and sometimes that's just not enough. In the case of pro tax what you're doing is you're making a small molecule and binds to the target maybe inhibits by binding. But really the major effects is coming from recruiting this other cellular protein or type of protein called E3 ligase. Which is basically a cellular trash can and by essentially forcing those two things in proximity the target and E3 ligase you can rewire the E3 ligase to degrade your drug target. And it's a super great example of how much of have proximity is a master regulator of biology like most biology in some ways is controlled by just like things being near each other. Put to buy molecules near each other and something will probably happen. You can think of cells as like a container to hold things near each other. There's like many types of proteins that do this adapter proteins trafficking proteins organelles or an example of this right natural products that do this. So so protects are this really interesting field and that they really break the rules of what's possible small molecules are amazing technology in many ways in terms of distribution delivery price. And the reason they mostly been you start to be supplanted by larger therapies is because they're just limited in what they can do. And so pro tax are starting to you know enable you to do things that maybe we're in the regime of genetic therapies or or other sort of large molecule therapies that have many challenges in terms of distribution delivery. But you know what we think so we're doing the next step beyond pro tax I always have to be really clear it's a really nice jumping off point but we're not a pro tech company. Our very first swag actually with a shirt that said general proximity it's not a blank and protect and we'll say the full thing but we had we've had a lot of people who kind of just conflate pro tax with next gen to proximity and they're actually very different. But to contact just a little more you know pro tax. So they they work through proximity there. They're small molecule that is inducing a proximity event between either ligasing or target. Super powerful and at the same time we think of the things that you can achieve with proximity. Degradation is like the least interesting one it's like I said earlier there's there's just many. You know it's not that hard for us to break things in biology. Protax it in some ways it's like a bigger hammer you can just you know wax things harder. So some cases that's good but it's still limited to this very specific knock down target regime. So there's just there's a lot of things that you want to do beyond that in biology for tons of drug targets like maybe refold a protein activated. Modulated function give it a gain of function relocalize it etc. Right. Yeah so so there's this whole class of things like biological transformations that you can imagine happening that have just totally been left by the wayside. And the targets associated with them as well because the technology to do that is impossible. So at the really high level that's what we're doing is we're saying look if you look at your genome 10% of it codes for proteins that modify the proteins. So every cell in your body has this huge constellation of molecular machines essentially proteins and enzymes that do biology. And if you could repurpose those you could you know gain the ability to modulate biology in ways beyond anything else that's that's really possible. And again and you're still doing this with small molecules which has massive advantages. It's absolutely an emerging modality and used it at the cutting edge of this. I'm also interested as to the layer of complexity that's added on with bringing another player another protein into the folds. Traditionally you have your small molecule or biologic. You have your targeted protein but now you're sort of bringing another layer into that. It's almost like a two body problem is becoming a three body problem. Does that add complexity in terms of modeling or in terms of experimentation or parameters that you need to consider? Yeah I think it certainly adds some complexity. There's no doubt about that. I think that's counteracted by sort of two things. One is which and one is that like biology just does this already. So it's like kind of in some ways it's more of a natural process. Maybe you're just like strengthening existing interaction which is less complex than a brand new like three body system. And secondly yeah so yeah it adds complexity but just the amount of extra firepower you get from this if you do it right. You know can make your drug discovery process easier actually just just if you find the right mechanism the proximity drug can be extremely potent and that can actually shorten the you know other parts of the development pipeline. Yeah no prior to this you were working with a flagship company building out a proteomics platform. Is that how you got into proximity based medicines or was this sort of an emerging area that you saw a lot of impact or possibility and. Yeah now the flagship company was it was a blast it was not really related to this. The proteomics we were doing was we were trying to broadly characterize the biomolecules that come at a dying cells which is another fascinating area that never been comprehensively done and. And cell death signaling is like really important for a lot of things. But I you know I had a proteomics and phenotypic drug discovery background from Ben Kovatslab right in my PhD. And so really I think where the idea came from was you know combining that with pro tax where it was saying what protects for cool but they're very limited in the mechanism of like what they can achieve. How can you go beyond that and and what I really realized is like proteomics phenotypic drug discovery and sort of an unbiased method to screen across many different effect or proteins. If you put all this together you could you could kind of basically create a new field that let you achieve this. So let's kind of shift the beans because you've got you've really been in the game here in the world. now for almost six years. And there's not a lot of drug discovery companies that came through Y Combinator in 2020. I was a little bit about what that journey was like. - Yeah, it's been a journey, definitely. So I always wanted to start a company. Since I'm an island, I wanted to start a company. I was like, this is the, I always wanted to be at startups. And that's why I joined Benzlalab. He on top of being kind of just a phenomenal chemical biologist. He's spun out a bunch of companies and thought it'd be a great sort of learning experience. But I always thought, you know, I had to spend like 10 years in industry before I had enough experience. So, you know, after my PhD, I got recruited to the flagship company. And honestly, I had a blast. I won't say too many bad things. It was really cool science, but it was not run like as well as you might expect from like, from a company from flagship, right? And the scientific team was amazing, but there was just a lot of kind of short distance between the actual scientific team and flagship. And so it's kind of a combination of two things where I was like, look, this is how flagship runs a company. I could start a company. I don't need, I don't need another 10 years of experience, which is definitely naive in some ways, directionally correct, but naive in that. They do a lot of things really well, including like raising a ton of money, which is really valuable. And so it's a combination of that and like having been obsessed with startups and like I started practicing having startup ideas in grad school. I have good friends, we'd text ideas too. And I was just like obsessed with like, what makes a good idea? You know, what, what, what, if you actually were going to start a company, like what would it be on? And so that's always kind of going on on the background. And then I just, honestly, it was a shower thought. I had the idea for this company of combining projects and freeing to get just every, and the specific way that we're doing it. And just got obsessed with it to the point where I was like, I know this will happen. Like someone is going to do this. It would be so crazy if this didn't happen. As far as I can tell, no one's done this. And then the sort of very obvious next step was, I should just, I might as well try, right? Like who knows if I'll be able to do it, but I don't want to like regret for the rest of my life being this obsessed with something and not trying to go for it. So around that time, I got invited to a Y-combinator conference called YC120, where they put together like 20 existing founders like Sam Altman and Reed Hoffman and stuff, and then 100 people who were learning to be founders. And they brought us all to Boulder, Colorado, and put us in a hotel and had an unconference. And so this is about two months after I had this idea. And I could stop thinking about it. And to me, that's one of the markets of good ideas that you wake up the next day, and it's still a good idea. And next week, in the next month, you don't lose that kind of epiphany shine. So yeah, while I was there, I was in the last night, we were at a bar and I was talking to the president of YC at the time, and he was like, how was the conference? And I was like, amazing. He's like, what would you go to YC? And I was like, I absolutely, and he was like, so what's your idea? And so I pitched this idea and did a terrible job. I had the worst elevator pitch. It's very hard to explain proximity to someone who's not in science. He wasn't a scientist, and it's Jeff Ralston. It's very hard to explain proximity without using the word protein, like 67 times. [LAUGHTER] And luckily, there is another scientist who's a YC partner with URNs who is in the conversation, and she got really excited, and high five made. She's like, you got to do this. And so I was like, amazing. And I quit my job the next day. And then I stayed at the flagship company to transition my role, because I was running the whole proteomics platform. And I had to hire someone else and all this stuff. And so I was supposed to go through the summer or 19 batch. And I've waited, and I went through the winter 20 batch instead. And so it was just me. So I incorporated the company like December 2019. I opened the lab in January 2020. YC started January 2020. Started an experiment in February, and then COVID started. And so it's just me at the time, got to demo day. The batch got shortened. They made it virtual with the last minute. And the market crash was like a week before the actual demo day. And so it's just me. I'm sitting there pitching. It was terrible fundraising. I had no IP, no data, no team. And I was trying to raise $2 million to build a platform, which is why I went through YC to get some money to fund the platform. And I mean, I raised like 50K out of YC. It was a complete disaster. And I was like, what am I doing now? And really just at the end of the day, it was so obsessed with both the platform or building, and specifically how we're applying it. The main target, and there's one or two others that we really love, is a lot of things you could work on in the form, but we've really just picked-- since we're pioneering the field, we get our pick of the best targets. And I think that's a really special thing. So the first year and a half, it's mostly just me at the company and trying to squeeze the little money and do a experiment and eventually brought on enough of a team to get some science. The first, like, the usual company in our average runway was like three months. We were at zero in the bank account multiple times. At one point, I liquidated my public stock portfolio to cover payroll. I missed my big inflection point, which was like, I went through YC, I'm going to build a school platform. That guy kind of squashed by, a, me not being good at fundraising and b, market just being so bad. And then I just didn't have data for like two years, because we built a whole platform from scratch. And I kind of burned a bunch of VCs where I talked to them and hadn't had anything. And then you just lose that FOMO if you're just constantly pinching. So yeah, it was a really long period of having a lot of money, having a really small team, really believing what we were doing. And at the end of the day, it was run out of money and I'd be like, so, so stressful. Not stressful for the team too. You know, it's like hard when people are, you know, really relying on you. And at the end of the day, I always was like, okay, what would I do if the company failed? And it was always, I'm just going to start another company doing the exact same thing. So I might just keep it alive, because it's like last paperwork. And so made it through that, race or seed around about a year ago. And it's been great since then. So low first time founder is a bold choice for sure. There's a lot of mixed mythology out there around how that can go, how that could go, how that should go. I'd love to learn a little bit more about your perspective there. Yeah. So, you know, one point actually after I see, after I'd raised a little money, I did bring on a co-founder from from grad school and I didn't work out. And we parted ways amicably. So I kind of had both actually sides of the things. But yeah, you know, for me was always, you know, for a startup, there's always this, or just in science in general, there's always a kind of like explore versus exploit dynamic. And you can always get stuck in either or, and for me it was like, I got this great idea. I could think about it and try to find people to bring on and do all the stuff before I could just jump off the cliff and figure out how to build it on the way down. And so I kind of took that route. And, you know, I think, you know, being a sole founder is definitely, I think, it's harder in some ways than being, you know, having a co-founder. I think it's easier in some ways too. I think one of the ways in which it's harder is that VCs have this myth that it's hard to be a sole founder. So they don't fund sole founders, which makes it hard to be a sole founder, which is frustrating when you're, you know, and at the beginning, they were telling me that I'm like, there's something wrong with me. And now it's like, no, you know, there's just pros and cons. And there's a lot of advantages to being a sole founder in terms of I've basically enforced to become, you know, a technical, super technical person to start off with. And I've, and I had to learn how to fundraise really well and tell stories. And I think if you combine those two things and the decision-making aspect of a CEO in one person, it is different than having a group of people. There's just a way in which being a super technical CEO can go, I can talk about any molecule we're making, any, you know, any mechanism piece of data that we have, I'm at the very front of like where our company is. And I can talk about it with like complete, you know, scientific rigor. And I can also tell a whole story that's like way zoomed out. And combining those two things, I think, is a superpower, same with decision-making, right? It's like, I just like understand the science, I think to an extent that I've had to. If you could give advice to you in 2019, would you advise you in 2019 to really go find a more operational business counterpart or just say like, this is gonna be rough buckle up, but it's for the best. - Hmm, that's tough. I mean, my life would have been easier, I think. I think it would have been easier if I would have brought an operational person, but I wouldn't have learned as much. And like, I really do feel like the amount of growth I've gone through because of being a solo founder is phenomenal. And I feel really lucky to have gone to that. So yeah, maybe I would maybe say look a little harder, but also be more confident that you can be a solo founder if you need to be. - Going through a solo founder in Y combinators one thing, but also Y combinator for biotech is another thing. What was that like? Because obviously their model is traditionally tech-oriented. There have been biotechs that have gone through that. But what was the thinking process there behind going into YC with a biotech company? - Yeah, so it really started at 10 years before, when I was at on nylon, at the same time I sort of ran away started reading Paul Graham's blog and just got up to that. That's how I got really obsessed with startups too. And so it was like, oh, YC sounds so cool. Like maybe one day I could do that. And then I got to this YC conference and then they were like come to YC. And it was like this crazy dream come true, like of 10 years. So yeah, in some ways it was phenomenal. If I was giving myself advice again, I would say go through it again, definitely. I would say maybe be a little more cautious on timelines because YC is great at saying, okay, we got three months like build something and then go to investors and that works great in the tech company with the software iterations. I go it's a little harder in biotech, especially if COVID has started in your batch. So yeah, I had an amazing time at YC. I probably would have pushed my demo day back actually, which I could have done, but no one knew how the market was gonna be. And then YC had so much good advice on how to run a good company. That's just apical to any company. It really doesn't matter. I think I really took a lot of that to heart and still think about things I learned at YC every day. So you've been quoted as saying, quote, startups are so effing hard. What kept you going through the brutal years? What is this burning passion that you have? What's its nucleus? Yeah, they're not always hard. They're super fun too, but yeah, they can absolutely be hard. If you hit a market like this, they can be extremely hard. Computing with some of the smartest people in the world. And I think it just helps to embrace the discomfort rather than run from it. But yeah, what kept me going was the way we're applying our platform. platform, the main target we're applying our platform to, it's never been drugged if we drug it. The world is like a very different place for many millions and millions of people. And yeah, that's like enough. It's just like, I wake up every day. When you're building a platform company, you can work on a lot of things. And we thought about going down just the Rare Disease Route, which has advantages, but we really went the exact opposite way where we're like, we're in a new field, we've got the first platform in this space. We're going to go after the most ambitious target possible in terms of not necessarily, that's not to be the hardest, but it's like in that quadrant of relatively easier and massively impactful. So if you're in a new space, you get your choice of which targets to work on and those are the ones that work on. So target we don't end up working on it is just super impactful. I wake up every day knowing that if a new one works, many people's lives will be much better. It's a really special feeling. Before we get into more of the therapeutic applications of your platform, you also then she started the company just when the world shut down. How was it during that period when maybe you're trying to get experiments run, you're trying to get data. How did you manage that situation? Maybe you're trying to bring on hires who are all remote. What was that like? I didn't have it with my to hire. I mean, like, yeah, the night before my demo day, I was in lab two, like three, I'm doing experiments, trying to get some screening data done, which didn't work out, but I also was lucky to live in a co-living house in San Francisco. It was a bunch of founders of people who had not a hacker house was more it was like a house for people who wanted to have community while still building a startup and some really amazing people who had been through some stuff. It just been through a lot of the startup journey. I was very, I think that was a really key thing in us surviving too is just having people I could talk to just like next door, you know, like a walk out my bedroom and talk to someone who built a bunch of companies, sold companies. So that kind of founder community really helped. I had a very different COVID experience than most people are. I was in a house with 20 people and I was like, I need COVID to end so I can go back to being an introvert. And I was the only scientist in the house when COVID started, so I was in charge of our COVID safety protocol, which is tough to do in a house of founders because one thing that you know, it's all founders is none of them think rules apply to them. So I had a fun COVID experience, you know, our lab was still open, I was still going in, but it was the combination of yeah, trying to fundraise and trying to think about stuff high level and trying to do science just by myself just kept building and put my nose to the grindstone and eventually got enough money to start hiring people. And I mean, I still remember like the first day, you know, I wasn't in lab and I was not in lab for a while and then experiments like, data still came in. It's like the best feeling in the world, you know. And you stayed in stealth mode for the past four years. Why now? Why are you getting your message out to the world now? What was the decision behind that? Yeah, I think it was partially we were just still really deep in building mode and it just felt like a distraction to have anything more. I made our website and our logo and PowerPoint basically. I guess I just didn't feel, feel ready. It was like two or three years just building the platform before we had any data out of it. So that felt, you know, not ready to share it. And now when we came out of stealth, it was because actually for our lead program, we got some incredible data. So really the de-stealth thing, which we just only talked about our platform, was to kind of set the tone for a much bigger PR maybe like later next year. So what was it like applying and actually winning one of these hyper prestigious ARPAH grants? It was like three million? Yeah, it was three million. Yeah, you know, there was a sprint grant. So they've announced it and you have two weeks to submit like a proposal and then get that and then like, you know, monthly, okay, we like it. Got three weeks to submit slides and a bunch of other stuff. It's for in-person pitch, which I flew to. And you know, it's for a women's health grant. And one of the reasons we working on college is when I was in my PhD, my mother got breast cancer for the second time. And I just remember feeling like so helpless because I was in most one of the best labs in the world and in capable of doing anything to help her. And she's totally fine now. She is doing great. But I just remember I really dove into oncology and was like, there's some really big problems here that we're just not working on that need to be solved. So yeah, that was my pitch to the ARPAH committee. So it's for a big women's cancer push that we're doing. And yeah, I told that in story. They said something like, why wouldn't you do this with an NIH or NCI or something? And I was like, ARPAH is for moonshots. This is a moonshot. This is too big for anyone else. And I think they really liked that. So they've been amazing. They're really kind of productive collaboration. They're super helpful. And yeah, very lucky to have one that. I mean, not to be a political. So that money still exists. It hasn't been affected by Trump. It's been slightly affected. But not in that we're not going to get it. We've had to kind of switch up some kind of studies and stuff that like we had some some of our experiments. We got approved to do in China, some of our Evo experiments and then those since been deapproved. So you've really gone through a period where you know, you really kind of you admitted a couple of years were really rough. How do you maintain startup speed now knowing which, you know, the lessons that you've learned and industry known for these hyper long timelines? That's a great question. I mean, I think part of it is just constantly sending that message to your team. One of the things I've learned as a CEO is that it's better much better to over communicate than under communicate. And so just the way we build our processes, you know, I'm always saying, like, can we move as fast as possible? Right? So we're hiring someone. If someone's good, it comes in our pipeline, you know, we should be moving extremely fast. We should be having an interview with them and then immediately doing rough checks and then we have a bunch of other things we do. We've interviewed someone and given an offer in like a week or less. So just building processes that feel really fast and just rewarding people and just sending that message over and over by what you spend your time on. How you build things? You know, startups are, they are, it's a marathon. It's a marathon you're sprinting maybe it's one way to put it. So it's definitely a little different than tech, I think, in some ways. But you know, internally we'll do sprints for really big projects and just try to maintain a really high cadence of updates and talking to people and I think it's much easier to build your culture than rather than shape your culture, meaning the people you hire are your culture. And it's much easier to hire people who think speed matters compared to hiring people and then being okay, work faster. So just prioritizing that. So maybe so I think a lot of it comes down to recruiting, which is one of the big lessons I took from my C is recruiting is the most important thing you're going to do. And I believe that when I started my company and then even though I believe that I still, I was actually off by like 10 X. It's 10 times more important than I thought because just the people you bring on are really everything and it's much easier to build a good culture by bringing out an awesome person than trying to shape someone's behaviors. And I know we're going to move on to some therapeutics more specific questions, but I am really curious. Do you have any hacks for building great teams and tech bio, bio, tech early stage formal? Yeah, I think I've won that I'm obsessed with, which is for whatever you're building work on the hardest and most impactful possible problem. And it's a hack in that I mean, it's polarizing. You say like I'm going to do this thing that no one's ever done before and like it's just so ridiculously ambitious. Some people are going to be like you're an idiot, you're crazy, no one can do that. But the other half of the polarization will be people who are like super energized by that. Both people you're recruiting and you know, partners, investors, etc. So again, yeah, we went through that process when our initial indication selection and really landed on, you know, start up so hard going to be pouring out your life into them. You might as well do it for something that really, really matters. I think maybe the way to still let us just think about how you can make whatever you're doing 10 or 100 times more ambitious. Absolutely. And mention some indications. Do you want to discuss your indication selection and decision making process around that? How your platform is being applied? Yeah. So it was pretty simple. A is this target amount of proximity, which most targets are, but not not everyone. And there are some that are classes of proteins that are just overall more regulated by proximity events. They have more interacting partners. Their function is orchestrated by PTMs, PBI's, etc. So that was part of it. Secondly, we wanted to go after, you know, our target is our platform is a tool to say across all the different effector proteins that exist, which one works best. So we wanted to go after targets where, and this is most targets, I think actually, but where the biology was of what effector protein you should use is not like 100% obvious. So if it's a happy insufficiency, maybe you use a deep equitonase and it's like pretty obvious. Although I think actually the dub tech companies are all struggling a little bit and I think partially it's because they've tried to be too rational, or they said, E3s work for decorations or dub's work for a stabilization. And it just turns out it's very hard to predict biology. But there is some way in which percent, go after a target, do something, some target, we have to do something more complex in degradation. So like activation, refolding where you can think proximity is going to work, but you don't know exactly the best mechanism should our platform solves. So those are the main criteria. Maybe one or two others, you know, are there good phenotypic models for our very first targets? We didn't want to layer too much biological risk on top of platform risk. For some of our newer targets in the longevity space, we can get away from that because we have such good proof of concept data now. And then lastly, the thing I just mentioned is, okay, of all the targets that fit these criteria, which ones affect the most patients? So you mentioned oncology earlier on and there you've touched on longevity. So what areas are you focused on? It sounds like this platform can be broadly applied. There's a few things in longevity that we're working on, the neurogynergis generation target we're working on. But overall, you know, one of the areas that I think proximity, and I think there will be many, but one of the areas that I think proximity will really change the world is in the modulation of transcription factors, which are canonically hard to drug class of proteins or undrugable in many cases and are all controlled by proximity. They're all, they all have hundreds or thousands of interacting partners, PTMs, etc. So we've got a few targets that we haven't disclosed in longevity yet, but that kind of control like really important cellular processes. And what we're doing is, you know, maybe similar to some of the reprogramming companies that are gene therapy longevity companies, where they're saying like, okay, we're going to find a gene, a Yamannaka factor, whatever that we can deliver to a cell and it turns on autophagy or some sort of youthful reprogramming, something like that. And what we're able to do is I think A, we can do the same thing with small molecules, which is massively valuable, right? Suddenly, you can hit every organ instead of just a few. It's potentially safer, too, because you're dosing it every day, as opposed to, like, a one and done. And lastly, what we're capable of doing with proximity technologies does not phenocopy just overexpressing it to some transcription factor that you'd delivered via a gene. It's more akin to tuning the transcription factor. And I think that has a huge amount of value, because, you know, no transcription factors, they're all complex. They all have multiple programs. They have a lot of ways that they get tuned. So I think there's just a huge massive amount of value in terms of, you know, can you give a human more mitochondria, can you give them more stress-resilience stuff like that, you know, these pathways that are all controlled by transcription factors that are not possible really to drug systemically with any other technology. And it sounds like you've used this platform to screen, whereas it's best applied. Is there a computational approach there? I imagine you're using some sort of machine learning AI in your platform, too. Can you maybe talk about your tech stack? Oh, yeah, I think my fundraising would have been a lot easier if that was true. And I have constantly kind of wrestled with that, but especially coming out of IC and the SAP people were like, you're screening platform is computational. No, it's not computational. It's not really a problem that's soluble to computation. We take almost more of a brute force approach where we just induce every proximity event possible. And that lets you kind of understand the space. I think the data we're generating in the long run will be the first kind of data that lets you build, you know, foundational models of sort of proximity induction. And we've learned a lot about what kind of proteins work, what do all. E3s are very special class and that people got lucky that E3s, there was, you know, that the project based start with E3s. They're overall pre-promiscuous, they're catalytic. The effect is very durable. So there's many other kind of effectors that people have played around with that don't work as well. Like, kindness is our one where you from kind of first blush, you'd be, this is a great class, but you know, regulatory, phospho event, have a five minute and a half life, which is not great for making a drug. The protein acts in the opposite. They have, you have to recentize the protein. So yeah, we've learned a huge amount just by kind of taking this approach and I think in the long run, there's one or two kind of computational things that we're building just from our really high throughput data. Now what AI tools do you actually use day to day as a founder or have been just superpowers for your team? Yeah, I mean, I definitely spend the chat GPT in cloud and definitely gotten better. Deep research is actually pretty helpful for, it's helpful for a lot of things for indication selection. It's never perfect, but it's great to get first blush of what's out there. Yeah, we've played around with some of the full stuff and stuff like that. Pretty pure play biotech though, right? Yeah, I mean, once we've started to discover a pair of effector proteins or a drug for that, there's AI tools that kind of makes sense. We're just starting to kick some of that off. Okay. Now, only a couple more questions here and you've been incredibly gracious with your time. For our listeners, what's the biggest error you've made as a founder that's taught you the most? Or maybe the better way to think about it is, what is the most valuable lesson if you could, let's say, go back in time six years and teach yourself, young or mom, one thing that was going to make us like so much easier or so much more successful or what happy, what would it be? Yeah, I think for me in particular, I think this is very different for everyone, but I had a huge amount of imposter syndrome when I started the company. And the way I fundraised was very much of like a rigorous scientist saying, you know, here's a research and we hadn't done any research. So here's all the cat viats and the way things could fail. And that's not really what you're doing when you're fundraising. You're sort of selling the vision of what's possible with money. And yeah, I think the thing that I got way better at that I wish I would have done earlier was I just, I did a lot of inner work around fundraising around like how I can look and invest in the eye and authentically be like the thing that we're building will change the world. And obviously, there's no certainty in anything, but we're by far the best bet you're going to get for your money. If what we're doing works millions of people's lives will be changed and we'll make you a ton of money. And being able to look someone in the eye and say that with authenticity was not something I was capable of doing when I first started. I had so much imposter syndrome. I had so many ways in which I was like, oh, you know, most startups fail. You know, like most drugs fail. There's always ways in which I was sort of sabotaging myself actually. And so I had this part of me that really believe what we're doing. I wouldn't be able to stop the company. But I had this other part that just, you know, was left over from the reason I went to aown island is because I was a terrible student under a grad. I had just had all this kind of leftover baggage. So I did a bunch of inner work on what are the parts of me that are coming up when I'm speaking to investors that are meeting it when you have two conflicting parts. One that's because it's a great thing and that's who are you to drug this target or something or build a company as a sole founder. And when those things conflict, the way that comes out is bad vibes or inauthenticity. And that's a huge part of fundraising. Yeah. The way I fixed it was a few ways, a bunch of friends who who had entered the same thing. A lot of I got a coach who's phenomenal who I should have gotten white earlier. I was always like, no, no, I'm like, wait, you really have a coach, such a waste of money. And a lot of parts work or IFS, you know, that is. So I would have done that much earlier and just had this other part of me that was, yeah, what you're doing is hard, but it's super important problem. The expected value is massive. Just believe in yourself. It would have made my life much easier if I had done that earlier. I think that's some great advice, Harman. Might just finish up with one last question. Sounds like you've selected your targets. You have your indications, your platforms well on its way. Do you have any exciting news that you maybe want to share or hint at for listeners? Yeah. So we're just getting ready to start our series A and that's the fund our lead program through Phase One clinical trials. So it's super excited. So we're really like hearing up to, you know, eventually become a clinical stage company and it's been really fun transition to split between just the purely platform building that we are doing and to be making a drug and getting ready to put it into human. So really excited for that and we'll have some more PR maybe in a year or so around what our target is and how impactful it is. And so yeah, I'm really excited to just open up the company more and speak more broadly about our vision and how much I think it is important for the world. Super exciting. Harman, that's been a pleasure having you on. I think that's all we have time for today, but we'd love to catch up in the future. Maybe once you have more things released, it's been great talking to you today. Yeah, it's been super great. Thanks for the great questions and the great conversation. Thanks for tuning in to the Bits and Viya podcast. Here Gateway to the intersection of code and biology. Stay connected with our vibrant community through our online events, meetups, our newsletter and Slack channels. And don't forget to subscribe for more conversations at the cutting edge of software and life sciences. Till next time, keep building the future of Viya on bed at a time.