Resilience After Loss: Leadership Lessons for Biotech Founders | Richard Yu (Part 3/4)

Intro - 00:00:06: Welcome to the Biotech Startups Podcast by Excedr. Join us as we speak with first-time founders, serial entrepreneurs, and experienced investors about the challenges and triumphs of running a biotech startup from pre-seed to IPO with your host, Jon Chee. In our last episode, Richard shared co-founding Green Pacific Biologicals for algae biofuels, learning that science is necessary but insufficient for commercialization, and joining QB3's incubator to help build one of the Bay Area's first shared lab spaces. If you missed it, check out part two. In part three, Richard talks about reconnecting with Gustavo Martinez, who approached him with the idea for functionally active GPCR antibodies, building the yeast-based screening technology that tests for function rather than binding, and why conventional antibody discovery optimizes for the wrong metric. He shares the analogy of grabbing scissors by the blades—tight binding doesn't mean it will cut paper—and the devastating moment in 2021 when Gustavo died in a skiing accident, followed by the team and investors rallying with unwavering support through crisis.

Jon Chee - 00:01:32: And has the Abalone mission, values, like, everything—was that just, like, the same since that YC Demo Day?

Richard Yu - 00:01:41: Yeah, pretty much. We were on a mission to develop multiple best-in-class and first-in-class drugs for GPCRs. For ones where pharmacologically active antibodies make the most sense and have the better characteristics to drug those targets, that's what we're doing now.

Jon Chee - 00:01:54: Very cool. And the founding team was Gus, you—kind of from the next interactions? Like, or were there more people that kind of, like, formed around at during your YC?

Richard Yu - 00:02:05: The real founding team was, uh, me and Gustavo. We were the ones—

Jon Chee - 00:02:09: —who were, like, going to YC every Thursday or whatever the thing was.

Richard Yu - 00:02:13: So, yeah, we were just like—I had known the dude for twenty years at that point. Right? So that gets me to the, you know, one of the touchpoints in the conversation, of course, is in, uh, 2021. I think we had some grant submission due in a week, and I'm sitting in my computer, and I get this message from his wife. She's like, "Oh, um, you know, Gustavo's, like, passed away." But I was like, "What is going on?" And—and ironically, I happened to be on the phone with—I don't know if it's ironically, but I happened to be on the phone with, uh, Leandra, the co-founder from the algae biofuel company, at the same time. Like, I was like, "Dude, I—I gotta go. Like, I just got this message." And he's like, "That's gotta be a joke or someone broke into her phone or something." Right? Like, that—that can't possibly be true. But it was. Yeah. He'd gotten in a ski accident, and he just, like, taken a jump and, like, landed in just, like, the wrong place in the wrong way and, like, uh, ruptured his aorta. Right? And he was skiing with his son. It was, like, a horrible moment.

Jon Chee - 00:03:11: Yeah. So that—that was, like—

Richard Yu - 00:03:13: I think, 2021. Right? Right around this time, 2021. So that was, like, a massive shock. And I—and I—I gotta, like, give the team here and all the investors—

Jon Chee - 00:03:23: I mean, they were just rock solid. Right?

Richard Yu - 00:03:26: No one was like, "Oh, man. What does this mean for the company? I'm out of here." And then like that, it was like, "What can we do to help?" Like, it really just—

Jon Chee - 00:03:33: —sort of renewed my—my faith in a lot of humanity.

Richard Yu - 00:03:36: But yeah. So that was, like, a huge crisis moment for me personally and also the company too. Yeah. I mean, that's one of the—I mean, as I was dwelling upon sort of lessons and—and personal development that's really been meaningful over the last few years, certainly since that moment, but in the intervening years, just using crisis moments like that and sort of transforming them into something productive and beautiful and helpful and—and all that. Right?

Jon Chee - 00:04:03: I just saw the phrase this—this morning.

Richard Yu - 00:04:05: It's like, not stoicism, but "broicism" or something.

Jon Chee - 00:04:08: Right? Yeah. Yeah. Yeah. Yeah. Yeah.

Richard Yu - 00:04:09: There's a lot of that going through the—Yeah. Yeah. But, like, you know, memento mori and, like, you know, being just sort of conscious of death and, uh, and stuff is—like, that was a really visceral lesson in that. Um, and it took—I mean, I'm still processing it, but it—it took a lot of years to really integrate that. But moments like that—and I'm past 50. So now it's like, it's not people getting married.

Jon Chee - 00:04:30: It's like people you know—

Richard Yu - 00:04:30: It's like on the downside of—Yeah, I think it's pretty good news. Right? So, yeah, I've had a—a couple other friends in their fifties, like, pass away. So it's like—it really helps you focus on what's important. And I know it's such a cliché, but it's, like, it's so true. Right? It's—it's very easy to read this and, like, go, "Yeah, that makes sense. Like, you know, pay attention to what's important." But, like, when you feel it and, like, actually experience it, it makes life a lot more integrated, frankly. So, like, all these splits, you know, that sort of immigrant experience, computation, you know, experimental, you know, like introvert, extrovert, you know, whatever. You could think of, you know, the ten, twenty axes of—those are splits. Like, wow, something about the last few years since that happened, like, everything is just, like, really intertwined and integrated in a—in a really great way. I mean, it manifests itself in the—the company and the—the science as well. Right? Like, the wet lab and the—and the ML AI, which we spun up over the past couple years—

Jon Chee - 00:05:26: —uh, integrating again wet lab and computational work—

Richard Yu - 00:05:29: —sort of high-throughput science—

Jon Chee - 00:05:30: —you know, sort of funneling in down on, like, a—

Richard Yu - 00:05:32: —you know, single drug product. Yeah. Just, uh, a lot of this, like, all these multiple, multiple threads of—of integration over the past few years have been such an experience. Right? It's mirrored or parallel there. It's not even just parallel. It has been my company journey as well, like, finding our footing and figuring out a way to, like, make things work, right, and, like, being comfortable with ourselves with who we—

Jon Chee - 00:05:54: —are and, like, doing what we do. And, yeah—

Richard Yu - 00:05:56: I hope that makes sense.

Jon Chee - 00:05:57: I mean, it does. And—and, I mean, absolutely. I can imagine, kinda like what you're describing, is, like, it gives your life and business, like, an immense amount of focus.

Richard Yu - 00:06:08: Yeah. Yeah.

Jon Chee - 00:06:09: It's like we're pulling this thing together. Like—

Richard Yu - 00:06:12: Yeah. Totally. Like, drama falls so far, you know, down on those things that, like, affect me anymore. You know what I mean? Like—Yeah. It's just like, whatever. Right? You know? Yeah.

Jon Chee - 00:06:23: It's not worth caring. Like, it's not even worth my—

Richard Yu - 00:06:25: Like—

Jon Chee - 00:06:26: —any sort of, like, me sweating this right now.

Richard Yu - 00:06:29: Seriously. Yeah. I mean, I—of course, it took a—like, a—a lot of meditation. You know, I had to work at it. Right?

Jon Chee - 00:06:35: Oh, yeah. Yeah. This is not just like a layup. It's like—a layup. No. No. No.

Richard Yu - 00:06:38: It's like—and it's like, it's still in progress. I'm not—I'm no Buddha. Right? You know? But, like, just having that experience and sort of, like, chewing on it over and over again, and it strips away a lot that's unessential in your day-to-day experience—

Jon Chee - 00:06:53: And probably gives you, like, I would imagine, like, a sense of urgency.

Richard Yu - 00:06:57: Yeah. For sure. I'm 53, dude. Like, I'm, uh, I have one of those charts with, like, the, you know, ninety weeks by, you know, 52 squares and, like, man, the—that next line is, like—it's two-thirds of the way through. I'm like, "Oh, man. That's, like, that went really fast, you know." And, like, those rows, there's, like, no guarantee, you know. Like, another friend who passed away this past year was, like, super healthy, ultra-marathoner type person, just, like, just, like, flossing his teeth and just, like, keeled over. I was listening to Sam Harris' podcast about this. Like, what are the lessons of death and what are the lessons of regrets? Right? It's like—it's not wallowing in fear or self-pity or anything like that, but, like, using that to, like, be a better person, to be more aware, to be a better boss or colleague or spouse or dad or whatever. Like—and—and, like, just do it. Like, you know, just make those decisions and and do that. I'm not grateful for the experience, but I'm grateful for what I've been able to—to pull out of that. And for the company too, yeah, it really has given us a lot of focus, right, in terms of what we wanna do, how we're gonna do it. The end goals are very clear, you know, making these drugs for hard-to-drug targets. We think antibodies are the best ways to do that. We think we have the platform that is a very good way, if not the best way, to get those molecules. So we're gonna take our shots, and we have a platform so we can take multiple shots on goal, which is great. So then we can have more opportunities to, like, have an impact ultimately on people. Right? So, yeah, it's like, uh, life is great, man, to have that sort of clarity and—

Jon Chee - 00:08:30: And the opportunity to do it. Opportunity.

Richard Yu - 00:08:32: Yeah. Every moment is like this opportunity to, like, do the right thing and make something better. Right? So that's pretty awesome.

Jon Chee - 00:08:39: It's pretty rad for sure, and that's, like, an understatement. Like, it is super rad. It's super rad. So it's like when people are like, "Oh—"

Richard Yu - 00:08:45: "—my God. You've almost run out of money, like, you know, X number of times. Like, how do you deal with it?" It's like, I don't know, man. Like, you know, we just do what we can. Obviously, it's not—like, I'm not being flippant about it. Like, it's—you have strategies and, like, you know, make sure we have, you know, multiple irons in the fire and stuff.

Jon Chee - 00:08:59: But at the end of—

Richard Yu - 00:09:00: —the day, like, you're just doing what you can and, like, the chips are gonna fall where they are and, like, I don't know. Like, you—you just keep your sort of core values driving all that stuff. And, I mean, I'm not sure if that's, like, the answer, but, like, it's my answer.

Jon Chee - 00:09:14: And I—I think too, there is only so much you can control. Yeah. Absolutely. There is only so much you can control. Right? Like, if you had your way, the '08 timing, the 2020 kind of timing—

Richard Yu - 00:09:26: That is the universe. Like—but—

Jon Chee - 00:09:28: —there's only so much you can control and only concern yourself with those things that you control, or you're gonna drive yourself absolutely insane.

Richard Yu - 00:09:36: Yeah. It's like "circles of control." Right? Like—and just being, like, just, like, really honest and relentless about focusing on those things in that circle. Like, again, you don't wanna be a dick about it for the things in the outside. Right? It's just like, no. I—I wanna radiate compassion, and, like, I—I truly do wish the best for everything outside that, but it's like, I—I can't do anything about it, you know, or had minimal input into that. So I'm not gonna—I'm gonna concentrate my energies and efforts elsewhere.

Jon Chee - 00:10:02: And a lot of energy is spent outside of the, right, the—the circle of con—like, so much—so much energy and so much heartache. It's like that's almost like human suffering.

Richard Yu - 00:10:12: It is. It's like little—we have little, whatever, 32, you know, a 128-gigabyte suffering machines in all of our pockets. We just, like, look through the news or social media streams or whatever. It's like, oh my God. Like, it is challenging because, like, you know—I mean, I don't mean to make this so much about, like, the world, but, like, there are echoes of this and parallels of this in the startup experience. But it's like, what is actionable information and what isn't? Right? And what can you do with the tools and the skills and the tools you have at your disposal? Right? Focus on that.

Jon Chee - 00:10:42: Yeah. So since 2020 and '21, I mean, you—

Richard Yu - 00:10:44: —know, we're very fortunate to have our CSO, Toshi, join. He was one of our first advisors in the antibody space, like a—like an experienced guy. He's done drug development. And, you know, after Gus passed away, he called. He, like, just came over, right, like, and joined. That probably, uh, immense financial impact to him in the negative—well, momentarily in the negative. It's gonna work out great for him in the long term. But, uh, yeah. And then a couple people who'd already joined, Monica and Lauren, they were there when Gus passed away. So, I mean, we have, like, this amazing core team. And I think Samir joined a couple years ago. It was just his work anniversary today, two-year work anniversary, to do the AI stuff. And then we have the, like, just—just such a fantastic team doing work in the—in the labs. I—I just feel—yeah, just immensely grateful for the opportunity to—to do that. And then, like, if I could just, like, focus on that and, like, all the other stuff of, like, I just hit my four hundredth rejection or whatever the number is, you know, from the VCs, it's, like, whatever. You know? It's like—it's the—the random walk of life, you know, we'll—we'll figure this out.

Jon Chee - 00:11:46: Figure it out. Absolutely. And, you know, you were talking about the platform you're building and the pipeline that you're working on. I guess, like, to set the stage, can you talk a little about, like, what is, like, the state of the market for your space, and how are you guys approaching it differently? And as in—in YC parlance—disrupting? But yeah. How are you doing it differently?

Richard Yu - 00:12:08: Yeah. Yeah. Yeah. You know, and as a technical founder, I'm going to answer about the technology first, but there are many other threads now that are, I guess, aspects of this. Right? So there's, like, the whole AI aspect.

Jon Chee - 00:12:21: Oh, and just—I just realized, as you're gonna go into the platform, tell Lauren to say hi. I—I worked with her, went through that Distributed Bio.

Richard Yu - 00:12:27: Okay. Awesome. For sure. Yeah. That's what I love about this. Like, this past JPM, I was like—I just ran into so many people randomly, you know. It was just awesome. Like, I—

Jon Chee - 00:12:36: It's a grand reunion. Because—

Richard Yu - 00:12:37: No, seriously. Because, like, I don't know about you, but for me, there's always, like, the little scared grad student who went to his first ASCB meeting. It's like, you walk into Moscone Center, and there's, like, thousands of people. There's, like, 10 parallel tracks going on. You don't know—Yeah—anyone. You're like, "What am I doing here? Oh my God. Like, you don't know anyone." You know? Yeah. And now it's just, like, just bumping into people constantly. It's like, "Hey. There's, like, this actual community. This is pretty dope."

Jon Chee - 00:13:01: I actually, like, the past JPM just, like, ran into Jeff in the middle of the street, and I was just like, "What up, man?" Like, it's—

Richard Yu - 00:13:08: I know.

Jon Chee - 00:13:08: That's the best. It's just like you're just running around meeting friends, bumping into friends. But, um, sorry to interrupt you.

Richard Yu - 00:13:15: No. No. No. I just love this conversation. It's like such a treat. Such a great way to start off the year. I was doing a retrospective anyway, but this is just like a—a nice way to—I mean, I'll probably look back on this recording and be like, "Oh, I wasn't—I wouldn't say focused, but, you know, like, at least there's some grist for some clips or something."

Jon Chee - 00:13:31: You're good. You're good. You're good.

Richard Yu - 00:13:34: Yeah. So I spoke a little bit earlier about the—it's almost like the mindset. Right? So particularly in the antibody space, previous technology, its—methods were really—and even—and that's bled over into the AI world. Right? It's very focused on binding and binding affinity, which makes sense. Antibodies have to bind their targets to have an effect, but it's like any KPI. Right? If you set up the wrong KPI, like, you're gonna optimize for the wrong thing. Right? So—so in the space of modulators, things that can, like, alter the signaling properties in a quantitatively defined way, our position is that that's not only ineffective, but actually the wrong way to go about that. Right? And I—on my website, there—there'd be pictures of, like, you know, a hand grabbing a pair of scissors on the blades. Right? It's like, "Yeah, that's a super tight interaction, but, like, that's not gonna help you cut paper." Right? So it's—it's really more about how do you bind and where do you bind and the dynamics of that binding. Right? Not just the on-off rates, but the actual ultimate consequences of the dynamics of the protein that you're binding. And that's something that, like—I mean, I think I have a keen appreciation just given my protein structure background and molecular dynamics and all that, but I think it's still, like, unappreciated. Right? Like, I think people still are talking about, you know, they're using—and—and I get it. It's—it's—that's where the data is. There are PDB structures. Right? And those are static structures of proteins, and it's fine if you're looking for a binder of some, you know, SARS, you know, CoV-2 extracellular domain or something, right, or—or some binding domain to neutralize. But if you're talking about, you know, uh, 40,000-atom GPCR, which is, like, jiggling like a—Yeah. Yeah. Yeah.—hula dancer, right, in a—

Jon Chee - 00:15:12: Yeah. Yeah.

Richard Yu - 00:15:13: —in the membrane, and that those movements are what define its signaling properties. Like, our position is that, you know, except for some edge cases, it's gonna be hard to predict what—what type of binding will give you the—the effect that you want. And we have developed this yeast-based technology to just test antibodies for—in a—in a very unbiased, structure-independent way of, like, "What does it do to the signaling? Period." And then we can try to learn from that. And then—so I—I think we actually have the data to do that predictive biology on function, and we have some examples where we've been able to do that in—in sort of local sequence space. But we're gathering the data to be able to do that. And in the meantime, like, try to develop meaningful drugs. It's not just, like, proof-of-concept experiments. So how does that differentiate on the technical side and the sort of experimental data generation? It's really about focus on functional data. That's like the ultimate KPI, right, that you're interested in, right—

Jon Chee - 00:16:08: —or—or metric, target function, right, if you—

Richard Yu - 00:16:11: —wanna use the optimization sense of terminology. And then I think in the sort of broader landscape of other companies, I mean, then there's—we have to bring in the sort of computational versus experimental side. We're mostly experimental in terms of the—we generate that raw data, and then we have an ML pipeline to really make good use of that data to either identify or, in some cases, extend beyond the original sequence space into new sequence space to get good hits. There are other companies who are predicting a couple GPCR antibody agonists last year. I think towards the end of last year, a couple papers came out. Uh, Nabla and Chai, they're doing awesome stuff. I mean, when I graduated, there are three great problems. Right? There's, like, the protein folding problem, you know, more degrees of freedom in—in ligands' design than there are, like, you know, atoms in the universe or whatever. Right? Yeah. And then there's natural language processing, and then I was doing the computer science minor. Right? So that and vision. Right? And, like, "We'll see if we get there, you know, by your grandfather's age or whatever." Right? And then now it's like—I mean, they're all effectively solved. Right? It's like crazy how many advances there have been. So, I mean, certainly, on this sort of, like, exponential slope, are—is there gonna be some, like, push-button day where you just, like, "I wanna just go click and develop an antibody or mini-protein or whatever," some other format to hit whatever target you want? Probably. Right? And the computers and stuff will be powerful enough, or we'll have some sort of model that captures it in some reduced representation, but complex enough that it captures all the degrees of freedom that you need to get the molecule that you want. I still think we're in a window where we can generate some really important drugs and products and be part of building that path towards a more generative or de novo drug discovery platform. You know, I'm very practical about this. My mom is just, like, super practical about things. Like, it doesn't really matter how you get there. Like, there's only way to get there. So, like, whether it's de novo or not, like, I don't necessarily care, which I—like if I could do it with my or our, you know, wet lab platform, like, fine. Let's just do that. Right?

Jon Chee - 00:18:18: But, yeah, if it allows you—

Richard Yu - 00:18:20: —to get to targets that are, like, hard to incorporate in our platform, whatever, sure. That—that'll be awesome.

Jon Chee - 00:18:24: And, uh, I mean—

Richard Yu - 00:18:25: There are hundreds of GPCRs we can, like, think about extending this into other target classes and—and whatnot. So, yeah, there's a lot—a lot of opportunities for growth for ourselves and for other companies. I think that's where it sits in the sort of like data measurement, the experimental side of things, as well as in the AI sort of computational space. It's just very unique data, functional data, that I think allows us to carve out a—a unique region of this AI game. Yeah. And, ultimately, it's about the products we make. Right? So I—I think these are the lessons that I learned from the 2008 era and then also going up and through the first sort of platform bubble, you know, in the QB3 days. It's like, I'm of the mindset that the pipeline or the products validate the platform. So, like, try to focus on that. And there's this infinite tension. There's a persistent tension of, like, "How much you know?" But if I don't put enough in the platform, it's gonna make it harder to find the products. And, you know, there's always that dance, but it's a sort of analogous dance to the—well, "If I focus too much on revenue versus fundraising, then I grow too slowly." Uh, there's, uh, the competition and, uh, you know, the speed is of the essence. So there are all these, like, things that you're always trying to balance out in this line of work.

Jon Chee - 00:19:35: And I guess the question for you on that is, like, what is the optimal balance, or is that an ever-shifting target for you or for everybody?

Richard Yu - 00:19:43: I think the answer is that there is no permanent answer. I think, you know, I think we're at the point now that there is reason to take dilutive capital to drive some of the products further to develop it more rapidly. Right? And at a certain point, unless we can license out one of our earlier products, we just need the funding to—to do that. The clinical development's very expensive. Right? So you—you just need to—to access that capital somehow. But how we got to here, whether through all the revenue-driven work or whether we could've just raised, you know, $20,000,000, you know, 2020 and just be done with it, who knows where we'd be if we had done that. I—yeah. It's so hard to back-cast and think about where we could've been. Sort of like, "Well, what I would've done with that job at Yahoo in 1993."

Jon Chee - 00:20:25: Yeah. Yeah. Yeah. Yeah. Yeah. You'd be on an island somewhere.

Richard Yu - 00:20:29: I mean, you'd be—

Jon Chee - 00:20:30: —on an island somewhere. So talk a little bit about the revenue-generating side of your business and maybe talk a little bit about your philosophy on, like, internal development and perhaps external development. Like, what's your philosophy around all of that? And, like, who do you look to work with?

Richard Yu - 00:20:44: So, you know, I think this is another sort of differentiation contrast, at least to earlier instantiations of the computational or frankly, even other platform companies. You know, if you on the antibody side, these are much more wet lab-focused companies, the Adimabs, the AbCelleras of the world. It's—it's very much, like, cranking through a lot—a lot of programs and, like, clipping the coupons so that you can eventually get a portfolio of potential downstream payoffs. And then if you keep that going for five, ten years, those milestone payments start becoming real money. Right? But then you have to, like, last that long. So—and then, you know, Adimab, of course, went wholly in one direction. Uh, they don't do internal pipeline development, and companies like AbCellera, who we've collaborated with, have pivoted very much towards their own internal pipeline development. I think a lot of that depends on your company status, how much money you've raised, whether you're public or private. Certainly, I can just say for us, uh, we focused on key sort of low-volume but high-value, whether it's upfronts—cash is king for small startups. But we do wanna clip some of those downstream coupons for building up some potential downstream value. But, yeah, fundamentally using that to—to drive internal pipeline development. So by having sort of like a portfolio of internal and partner projects, you can sort of, like, interweave them so that if the timing works out, some of the internal projects can be licensed out earlier and use that money to drive the longer-term but higher-value internal pipeline products. So it's some sort of, like, mixing and matching of all of the above, and you can throw grants and fundraising into—

Jon Chee - 00:22:19: —that.

Richard Yu - 00:22:20: —But from the business side, yeah, it's like portfolio management, right, and the different aspects of each of the programs.

Jon Chee - 00:22:26: And I was gonna say, like, this aspect always, like, is really fascinating to me. When I talk to my parents about it, they're, like, outsiders looking in and he's like, "You just bet on a drug. Right? You raise a boatload of money, you bet on the drug." And I was like, "That's one way to do it."

Richard Yu - 00:22:39: That's one way to do it. Yeah.

Jon Chee - 00:22:40: That's one way to do it, but there's a bunch of creativity when it comes—it's like as you describe, it's—it's like kind of portfolio management.

Richard Yu - 00:22:47: Yeah. Yeah. Yeah. And it's dynamic. Right? Like, I mean, in a year, we'll be in a place, hopefully, where we'll be getting, you know, nearer to the clinic on a—on a really important, you know, metabolic drug. So if that's the case, then things will shift, right, to fund and—and support that aspect of value creation. So, yeah, I mean, it's—it's equal parts, you know, some strategy, you know, portfolio theory diversification, that sort of thing. Equal parts is, like, you know, opportunistic, you know, where the science goes at any given time, where—where it's at. I think we're—this happened to be in a—you know, we've emerged from the, you know, the deep, dark winter, and I think there are only signs of—of, you know, the overall markets being a little bit brighter out there—

Jon Chee - 00:23:29: —in the marketplace. A little bit more cooperative.

Richard Yu - 00:23:31: Exactly. That does, thankfully, intersect very nicely with where we're at with certain pipeline projects. So that's great. If we were in another stage, we'd have to do something else. Right?

Jon Chee - 00:23:42: And I guess a question, just, like, thinking about your revenue kind of activity, who are the folks that you guys want to work with and like to work with? Like, who has the best kind of, like, fit for you guys when it comes to those types of collaborations?

Richard Yu - 00:23:55: So we just kicked off one with—with, um, Pfizer, which has been amazing, but we just signed them last year as well with, uh, Shichuan Pharma in Hong Kong. Again, amazing partners. I think particularly for those programs, the Shichuan partnership, we really do think of that as—it's not just like this clean divide between internal and partner. Right? It's like—it really is like a—a true collaboration, both in terms of the science as well as the economics coming out of that. So that is, I think, like, the ideal. But, again, we have this platform where we can turn the crank. Right? So if there's someone who's like, "Oh, we just wanna give you a boatload of cash, but, like, we want all the downstream," we can, like, figure out how to mix and match that into other things that have less upfront and more downstream.

Jon Chee - 00:24:34: And—and—and a lot of—

Richard Yu - 00:24:35: —it also depends on whether it's competitive or complementary to our current pipeline. And we wanna, like, make sure—

Jon Chee - 00:24:41: —that we overlap and, yeah, synergize. Right? Synergize. Yeah. With the—

Richard Yu - 00:24:46: —all the expertise and the KOL, the sorta experience, right, the knowledge databases. Yeah. It's mostly out of just, like, we have limited bandwidth. So, like, if we know a little bit about metabolic space, it's easier to go into metabolic-adjacent, you know, diseases rather than go into cancer or whatever. Right? Even though there's, of course, an overlap between those two as well. So, yeah, that's how we have managed it, and it's—I mean, we're here.

Outro - 00:25:10: That's all for this episode of the Biotech Startups Podcast featuring Richard Yu. Join us next time for part four where Richard recounts how processing loss shaped his leadership philosophy, building the team, including CSO Toshi and AI lead Samir, developing CB2 agonist antibodies showing efficacy in liver fibrosis and neuropathy models, and navigating hundreds of fundraising rejections while staying focused on what he can control. If you enjoy the show, subscribe, leave a review, or share it with a friend. Thanks for listening, and see you next time. The Biotech Startups Podcast is produced by Excedr. Don't want to miss an episode? Search for the Biotech Startups Podcast wherever you get your podcasts, and click subscribe. Excedr provides research labs with equipment leases on founder-friendly terms to support paths to exceptional outcomes. To learn more, visit our website, www.excedr.com. On behalf of the team here at Excedr, thanks for listening. The Biotech Startups Podcast provides general insights into the life science sector through the experiences of its guests. The use of information on this podcast or materials linked from the podcast is at the user's own risk. The views expressed by the participants are their own and are not the views of Excedr or sponsors. No reference to any product, service, or company in the podcast is an endorsement by Excedr or its guests.