How Curiosity Creates Breakthroughs in AI, Data & Biotech | Caleb Appleton (Part 4/4)

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, Caleb shared how he joined Innovation Endeavors during its spin-out, why minimal structure forced rapid growth, and how he left to lead a pandemic turnaround at TuneIn. If you missed it, check out Part Three.

In Part Four, Caleb unpacks joining Bison Ventures as a frontier tech fund investing pre-seed through Series B, why he focuses on "TechBio"—bringing computational toolkits to life sciences—and how biotech's challenges forced him to ensure platforms deliver de-risking datasets that later-stage investors will value. He also breaks down his case for revenue-generating biotech that validates product-market fit like software, his framework for whether data platforms creating 10 times deeper or cheaper data should sell technology or build drugs, and why companies like Vivodyne could become the AWS of biology.

He reflects on why operating made him more empathetic to founders, how easy it is to prescribe boardroom strategy versus executing it, and why teams must identify their superpower rather than becoming something they're not.

Jon Chee - 00:01:49: It sounds like the fundraising was secured. You're ready to get to work. For Bison, what is your mission and focus when it comes to deploying this fresh capital that you guys have just recently raised?

Caleb Appleton - 00:02:01: Yeah. So Bison, first and foremost, is a frontier tech fund. Other people call that "deep tech"—generally synonymous. What that means is that every company we back has true technology innovation at its core. We're not, for the most part, investing in consumer or classical enterprise SaaS, like a finance tool or an HR tool. We're really looking for innovative technologies that are tackling massive problems in large markets.

We invest pre-seed through Series B, with the vast majority of what we're doing being Seed and Series A investments with an average check size of $5 million or so. At the Seed, that means we're leading or co-leading most rounds we do. At the Series A, we've led rounds, co-led them, and followed.

There are three main buckets we communicate to our LPs and externally that we invest in. I spend my time in two of them. The one that I don't spend my time in, but have colleagues with much more depth of experience in, is Climate and Sustainability.

The second bucket is the one relevant to our conversation today, which is TechBio. Really, this thought of: How do you bring technical engineering, computer science, and data science toolkits to the life sciences? Whether that be for the discovery of next-generation therapeutics, enabling tools and services for that industry, or non-human health applications—bio in agriculture, industrial applications, waste remediation, specialty chemicals, or whatever it may be.

The final bucket, which certainly bleeds into the other two, is what we call "AI in the Physical World." It's where I spend quite a bit of my time. That's true atomic manifestations of artificial intelligence—things that blend from the world of bits to the world of atoms. That includes true physical world manifestations of AI, things like robotics, autonomy, and next-generation computer architectures at the silicon level, through to applied AI software that influences decision-making and processes in these physical world industries.

So that might be something that's vertical in nature, selling into biotech or pharma, or it might be something horizontal selling to mechanical engineers, biologists, or data scientists, but really focused on physical world workflows and decision-making.

Jon Chee - 00:04:26: Very cool. As you're thinking about those two buckets where you spend most of your time—your TechBio and your AI in the Physical World—what is the current state of the market for those two buckets? And how do you think Bison is disrupting that status quo and approaching it differently?

Caleb Appleton - 00:04:47: Yeah. Well, I would say that the two markets couldn't be in a more different state today.

Jon Chee - 00:04:53: Yeah. Yeah.

Caleb Appleton - 00:04:54: There is almost unlimited investor exuberance for physical world AI, as manifested by some recent robotics raises. Companies like Figure, Field, Skild, and Physical Intelligence have shown multi-billion dollar valuations very early in their life cycles. Whereas on the biotech side of things, it's no surprise—or it's not a hidden fact—that it's been a more challenging market over the last five years or so.

So we approach them differently. I think you cannot, as a fund of our size with a couple hundred million dollars of AUM, ignore the market forces. You can't afford to be contrarian indefinitely. Some bigger funds can do that, like Founders Fund; they have billions of dollars, so they can make a bet that the rest of the market doesn't have to appreciate until it's in a later state. Ultimately, we're reliant on other capital later down the company's life cycle validating the things that we're doing.

In biotech, that means we need to be very focused on what is driving value for both the end users—hopefully patients—as well as making things less risky for other capital sources.

I do a lot of therapeutics investing. I continue to invest in therapeutics platforms, but I'm much more focused than I was earlier in my career on ensuring that we're not just de-risking platforms or proving that the platform insight is correct, but that there's a focus from the outset on getting to true de-risking datasets that a firm who cares very little about the platform will see as valuable irrespective. That narrows the number of things we can do quite substantially. It's just expensive and takes a long time to build novel therapies, particularly those derived from a novel platform insight.

I've also been thinking a lot about what is more attractive because of this market dynamic. What is true is that there are still plenty of capital sources, both in the public and private markets, that want exposure to biotech but are uncomfortable with regulatory risk and therapeutic risk.

I wrote an op-ed in TechCrunch six or so months ago with a cheeky title around "The Case for the Revenue-Generating Biotech." In every other form of venture, you validate a company's progress by their growth in customers and revenue. The reason "software ate the world"—to use the expression that Andreessen Horowitz coined—was because very early in a product's life cycle, you could ship it, have people use it, and understand product-market fit. That's antithetical to how drug discovery works, right?

You have all these assays along the way, and they become increasingly complex and more expensive. Fundamentally, until you put something in a human, you have no idea whether it's going to work or not. And even then, it might be four years after you put it in a human before you really know.

Jon Chee - 00:08:13: Yep.

Caleb Appleton - 00:08:13: So I had this idea, as I'm sure lots of other people did too, that there should be the capacity to build businesses in the life sciences that look much more like those in the software world—to have more predictable growth curves that have the potential to get to multi-billion dollar valuations by growing rapidly to large revenues, but aren't predicated on massive amounts of technical risk around an underlying therapeutic hypothesis.

Where I've really spent my time there is focused on what I'll broadly classify as data platforms. There tends to be a couple of flavors of company, and I can present a framework for how I think about the right way to utilize the value those companies are creating.

I tend to look for things that are creating data that's either 10 times more deep—for example, spatial omics or single-cell transcriptomics, where you used to have the genomics of a cell and now you can get the whole transcriptome from a 10x device. Okay, now we have data that's 10x as deep in a very specific context. What can we do with that?

Or it might be data that's 10x cheaper. If I can produce the same data that my competitor can but at one-tenth the cost, I can produce 10 times as much data. So I started to look for businesses that are blowing out the data landscape because I believe that's where we are still drastically constrained in applications of artificial intelligence in the life sciences: good datasets. We just don't have the "internet of text" to learn from in the same way.

So then the question is: Okay, I'm a PhD student or I'm spinning out of a pharma company, and I have this widget that produces data in a new way. What most venture investors are going to tell me to do is take that and use it to interrogate novel therapeutic hypotheses and sell a drug. Because, okay, you've got this arbitrage opportunity where you can see things other people can't; hypothetically, you should have a better chance of making this drug successful.

And that can be the right option for businesses. A good example of this was a data business that I invested in called Eikon Therapeutics, which I mentioned earlier. They had this high-throughput, super-resolution microscopy platform that allowed them to see single proteins interacting in live cells for the first time ever. That data is super interesting. It's truly mind-blowing the first time you see two proteins in a live cell interacting with each other. You're like, "Wow. I've been told about how biology works, now I can see how biology works."

Jon Chee - 00:10:52: It's just like those little drawings in your textbook.

Caleb Appleton - 00:10:55: Yeah. The challenge with that was it was a really hard-to-run assay. The data was incredibly high-throughput—terabytes per run. Actually making sense of it was not an inconsequential task. So for that company, it was not something that, in the early days at least, you could imagine shipping to every lab in the world and having them create utility from it. It's actually like, "Hey, really only we know how to use this effectively. We have a team around the table that has developed drugs previously. Let's do that." And that was the best path for that company, and that's how you saw the path to billions of dollars of value.

I have another company in my current portfolio by the name of Vivodyne, who I think you've had the chance of working with. With Vivodyne, what they do is create data at a throughput that no one else could, specifically looking at complex human tissues. So model organ systems—things like kidneys, liver, lymph node, bone marrow, etc. They're able to create these complex human tissues in microfluidic chambers and do so at multiple orders of magnitude higher throughput than any other platform in this space.

With Vivodyne, they could—and very well might at some point—decide to use that to develop drugs. But it was something that, once they figure out how to do this reliably and repeatedly, every pharma you talk to is like, "I know how to use that platform. I know how that would fit into my workflow. Just run the experiment for me."

There, my vision and the company's vision is that actually there's much more value on the table by being this broadly enabling toolkit across the ecosystem. Ultimately, you become the AWS or the Scale AI for creating these datasets for bio. Then you learn from that yourself and you're able to utilize them in the best possible way.

It's very similar to Illumina. It would have been silly if they used their sequencer just to sequence their own samples because, "Hey, we can do this faster, cheaper, better than other people." Instead, they sold them to every lab in the world. And at one point were like a $70 billion company because they were such a fundamental enabler of a ten-year period of scientific discovery.

I think Vivodyne has the opportunity to do that. Therefore, it would be silly of them to throw that away and just myopically focus on building the drug. So that's one thing that I'm very excited about: things that look like that. It's like, okay, this is broadly enabling for the industry. People are willing to buy it pretty early in the company's life cycle, and you can see this path to tens, hundreds, billions of dollars of revenue over time.

Jon Chee - 00:13:40: Absolutely. The cyclical nature is similar to the NFL—a crazy cyclical high and then a low on these troughs. Trying to think about what is a more sustainable business model for life sciences broadly. Not to say that it's an easy feat, because it is definitely a different muscle than just pure-play drug discovery. Now you're selling. And most therapeutic startups are not selling, really.

Caleb Appleton - 00:14:09: Well, I think this is a fundamental question that I always contemplate when I'm looking at companies. Part of it also comes down to team DNA. Teams that are very good at building drugs typically are not good at selling. And teams that are really good at building technology don't typically have experience developing drugs. Yes, sure, anyone can learn to do that on the fly, but you're still going to have the same attrition rate and failure rate that everyone else has—and probably you're going to be worse because it's the first time doing it.

So companies also kind of need to look themselves in the mirror and say, "Hey, what is our superpower? Let's lean into that thing." If that's building technology and selling technology, that's what you should do. If it's drug hunting, that's what you should do. Trying to make yourself something you're not can work, but it's way harder.

Jon Chee - 00:14:59: Way harder. My wife works at CloudFlare, and seeing software sales in motion—it's a well-fucking-oiled machine. They started all the way back from Oracle and Salesforce. Software broadly speaking has continued to iterate that model. Life sciences is like in the stone age.

Caleb Appleton - 00:15:21: Yeah, totally. There's very few companies that have done it effectively. There are some very notable examples of high success there. So I tell those companies, "Hey, it might be bad actually to hire the person who's a salesperson or a BD person from your industry. Maybe go talk to someone at CloudFlare and hire an enterprise seller there." You gotta teach them biology and you gotta teach them a bunch of other stuff, and you probably need to bring in someone from the industry that has the connections, but ultimately, there's a ton we can learn from the enterprise software industry of how to figure out how to sell something and then do that a bunch of times.

Jon Chee - 00:15:59: Exactly. I love that cross-discipline, cross-industry learning that you can bring in-house. We're in equipment, and the equipment sales process... I just see it every day. When Chloe is working side by side with me, I'm like, "What the heck? These are completely two different worlds." But when you're able to marry it together, magic happens.

So we try, at least on our side, to incorporate the software sales playbook where we can, where it makes sense. But I love your thought and thesis on generating this early revenue. It's either you just raise capital or die, which has been the case for a very long time.

Caleb Appleton - 00:16:46: Yeah. I worked for Eric Schmidt for a number of years, and he had this saying: "Revenue solves all known problems." And it's kind of true. Google is able to have these crazy moonshot projects, most of which fail drastically and dramatically, but because they have the search business and the ads business, it doesn't matter.

Waymo, as an example, is one that worked out and required tens of billions of dollars of investment to get it to where it is today. They're able to do that and take those enormous risks because they don't have to go to Bison or Andreessen Horowitz and ask for money to fund that thing. They're just like, "Okay, we're producing a lot of cash. What's the best way to spend that? We should do some things that create massive upside."

I think the same is true here to a smaller degree. Even in just offsetting burn—the difference between having a couple million dollars coming in each year and none is ten people's worth of salary. Or it's six additional months of runway to figure out the thing that has ultimately massive product-market fit. That's very powerful. If you can become much more in control of your own expiration date than letting your ability to access capital sources like myself dictate that.

Jon Chee - 00:18:05: Absolutely. I always think back to that family friend who was at Lawrence Berkeley. I annoyed the shit out of him when I was younger. He had that insight a long time ago. In the very beginning, they were just doing licensing work and generating a shit ton of licensing revenue so they had that bedrock of cash flow. Then they started generating and developing their own technology for the lithium-ion stuff.

I think a lot of the time, people will be like, "You're distracted. You're not focusing enough." It's like, "Wait a second. I'm trying to create this sustainable aspect to the business, which allows me to run your Google-to-Waymo situation." Not every business model is Google AdWords. There are varying degrees of it. But I think in the life sciences, there are tons of opportunities to generate revenue. Not to be glib about it—these are not easy things to do—but you can do fee-for-service stuff, you can do licensing, you can sell consumables. There are all kinds of ways to generate some sort of cash flow or, in your case, selling data. And that liberates you, should you want to develop your own pipeline or whatever it may be to take that moonshot.

Caleb Appleton - 00:19:29: Yeah. I think there's extreme liberation being in a "default alive" state. Very few companies in the space ever reach that.

I think there's also been just a ton of probably bad advice, well-intentioned but bad, given to entrepreneurs in the space from people like myself. And I know I've given this advice to some companies, which is: "The only way you can make money is to become a therapeutics business. So you gotta put it all on black."

I think that's changing. Entrepreneurs hear that and they're like, "Oh, if I'm gonna raise capital again, they're gonna ask me about my pipeline. So I need to have an answer to that." My hope and my hypothesis is that that is changing and people will begin to recognize the power of some of these businesses, particularly if they can generate revenue in a way that's recurring and understandable—not just to a biotech investor, but to a more traditional venture capital firm.

I think a couple of those wins will start to create a path for other people. That's not to say that should be the right journey for everyone. There are plenty of those that I think can generate revenue, but it will never be of venture scale. You have great businesses to start as well. I don't want to discourage anyone from doing that. This is very true as we both live in San Francisco—everyone thinks that raising venture money is the definition of success for your startup. When in reality, for a lot of startups, it just sets the bar incredibly high that you have to clear. The founder might be much better off to just organically build the thing and have control of their own destiny.

Jon Chee - 00:21:04: Yep. Absolutely. It sounds like it's the early innings for Bison, and you guys are starting to flesh this thing out. Can you just talk about the way that you guys are firm-building? Talk about your philosophy on who are good fits to bring into the Bison fold for those rare VC roles? And what do you see your company's culture to be like? Every firm culture is a little bit different. Some people are like a group of lone wolves. Some are much more collaborative.

Caleb Appleton - 00:21:36: Yeah. So maybe just to give you the lay of the land: Bison's a tiny team. There's four of us on the investing team. I'm one of three partners. Ben and Tom were the co-founders of the firm. And then we have a fourth investor named Ari, who's the Principal.

We all have technical degrees. Everyone is an engineer by training, though we're all, I would say definitionally, generalists. We look at companies across a number of spaces. That might sound kind of incompatible with underwriting deeply technical projects, but I think what we actually find often is that the best ideas are kind of at this intersection of multiple technology trends. Therefore, someone that's able to draw from different perspectives, different industry experiences, and different technology experiences does a great job at diligencing and underwriting those businesses.

So it is actually a great question because we are, for the first time ever since I joined, hiring another person for the team. We're hiring a senior associate/mid-career type individual. So if anyone's listening and thinks it might be a fit—depending on when this comes out, hopefully it's still a job we're hiring for.

We are looking for someone with a similar kind of background to the team: technical training, probably spent some time either operating or at a consulting firm or investment bank, and has a real defined passion for startups and entrepreneurship. That might have been manifested by being an investor at a different firm, being an angel investor, helping their friend out on the side, or maybe they have a side project or side hustle they've been working on.

Because the firm is so small and because we're only about 15 investments into our life cycle, we aren't at full capacity each of us. That means basically every deal we work on, multiple investment team members are spending time really doing the diligence and getting to know that company. It's highly collaborative. Our compensation structure is based on fund performance, not on deal performance. So everyone's incentivized to find the best deals. And if they're not the best person to support that company, to do the diligence to get it to the right person.

I think one of the things I find most empowering—and this echoes back to Bain and Innovation Endeavors—is that I get to work on a team where everyone is capable and everyone does their own work. They pick up their own pencil, write the memo, call the experts, and try to understand these businesses. I find that super empowering. I don't want to end up at a place in my career where I'm just managing process and have a bunch of people underneath me doing it.

So someone that's going to be successful in this role is going to be similar to what I described my early role in venture being like, where you're tasked with making the job everything you can make it. There are no constraints on how you spend your time other than, ultimately, it needs to result in good deals being done over your tenure. In some ways that's very intimidating—that there is no blueprint. Obviously, there's a ton of support and people you can learn from. But we think about it as just hiring those high-agency, high-IQ, high-EQ individuals that can really run with ambition at the task at hand, and then ultimately stand shoulder to shoulder with our founders as they do things that are improbable in building their business.

Jon Chee - 00:25:19: That's rad. If I was looking for a venture role, that sounds like the one I would want to get a jump on immediately. Very, very cool. And as you are looking out one year, maybe two years out for you and Bison, what's in store for you guys?

Caleb Appleton - 00:25:36: Yeah. I think you'll continue to see us make announcements around our capacity to support entrepreneurs in larger and more impactful ways. Fundamentally, there are these areas that I specialize in and have more experience than others. But much as we talked about entrepreneurs constantly needing to be thinking about the best incremental investment of their time and dollars—and making sure they're not overly dogmatic about some approach they've been taking—I continue to pull on new threads and try to figure out other areas that both excite me personally and professionally, but also I think will be meaningful and impactful companies and technologies.

You know, it will continue to be businesses in the life sciences. I think the coolest thing about that space is the direct impact you make if successful is hopefully financially very rewarding, but is impactful to society and has real meaning in that way. So I hope to continue to partner with exceptional entrepreneurs taking crazy but reasonable approaches to intractable problems.

I continue to spend a lot of time in this world of applied AI. Most recently, I've done a deep dive and am really enjoying meeting companies in what I'll call the "AI co-pilot" space for technical users that aren't software engineers. Claude, Copilot, and Cursor have transformed what it's like to be a software engineer. I think we'll see similar uplifts in terms of productivity and utility of toolkits that mechanical engineers, architects, data scientists, etc., are using.

We've been spending a lot of time there, inclusive of tools in bio as well. We have an unannounced investment in a company that's selling tools to commercial pharma—so not R&D, but basically everything post-clinic. How do you make a drug successful? How do we buy drugs, acquire a startup, etc.? They've built a really exciting toolkit for that kind of technical user that allows them to understand their landscape significantly better and make better decisions. I think that's a really cool way that we're seeing AI already impact workflows in the life sciences, where you don't have to wait ten years for a drug to make it through a clinical trial. You can say, "Hey, this allowed me to decide to buy this asset, which I wouldn't have done otherwise."

Jon Chee - 00:28:07: Very cool. Very cool. I love how the AI aspect of your focus is also bleeding into the life sciences as well.

Caleb Appleton - 00:28:13: Yeah. The coolest things we see are these intersections of trends, and biology in many ways remains the final frontier. We understand so little about so much of biology still. It's an exponential growth curve in our understanding. I think AI is the thing that allows that to continue to be exponential.

Jon Chee - 00:28:33: Absolutely. And if I were just to insert a goal for us: to climb the V14 in the cave and become as strong as that dude...

Caleb Appleton - 00:28:44: I think they say that goals should be achievable.

Jon Chee - 00:28:49: What about the moonshots, Caleb? We can do it. Like, believe in ourselves.

Caleb Appleton - 00:28:53: I think me climbing a V14 boulder might be beyond my capacity in this life. Maybe once some longevity companies work out, I'll be able to revert to my 14-year-old self.

Jon Chee - 00:29:06: Yeah. Exactly.

Caleb Appleton - 00:29:08: Exactly.

Jon Chee - 00:29:10: You've been so generous with your time, Caleb. Thank you. This has been super fun, learning about your background, your upbringing, and everything that you're doing at Bison. Super rad. Honestly, I feel like I'm a sponge just absorbing this. I'm looking forward to being able to take away some of the things I've learned today and bring it back to Excedr, so thank you for that.

In traditional closing fashion, we have two questions. The first question is: Would you like to give any shout-outs to anyone who has supported you along the way?

Caleb Appleton - 00:29:38: That's a great question. Obviously, my family—my wife and my parents—are incredibly consequential in both who I am today and how I make decisions. I think without my parents being incredibly supportive of me exploring my passions early on, I certainly wouldn't be in this chair. So that's one.

The other is... fundamentally, I have to do this job because entrepreneurs are audacious enough to do things that are improbable at the outset, but feel inevitable in retrospect. That's the greatest privilege of my career: I get to spend my time learning and soaking in things, just as you mentioned, from these people who I genuinely believe are going to change the world. Not all of them will be successful, but I have every belief that a number of the companies we have invested in at Bison and continue to invest in will be that.

Without the people that are daring enough to do something incredibly risky and probably a little bit insane, I wouldn't get to do this. So to all of the entrepreneurs I work with, I'm very thankful for the privilege of being able to partner with them.

Jon Chee - 00:30:52: Hell yeah. I honestly couldn't say it better. It's a rare opportunity, and an exciting one at that. Especially being in the life sciences, I think as an industry we're doing really important work, if not the most important work. I mean, I'm biased, but I'm very grateful for the opportunity to work with people who are this passionate about a hard-as-hell problem.

Caleb Appleton - 00:31:15: For sure.

Jon Chee - 00:31:15: They're running through walls every day, just nonstop. Last question: If you can give any advice to your 21-year-old self, what would it be?

Caleb Appleton - 00:31:24: It's a good question. I think that it would really come back to one thing we've already talked about, which is a reinforcement of the value of exploring your curiosities.

It's very easy, particularly for those of us like myself—more Type A, engineering mindset—to try to architect, "Hey, here are the things I have to do to be successful," and have that checklist that I am going to check off.

I think much more impactful—both in terms of my own personal enjoyment of the things I'm working on, but also retrospectively in terms of the value it's created for me over the long arc of my career—are the things that weren't necessarily on that checklist where I said, "Hey, this is just really interesting to me. Let me spend some time trying to understand that."

That might be something related to work. It might be like learning a technology. It might be like, "Hey, I have this hobby and I want to do that." I ride my bike a ton and I meet really cool people through that, and that sparks something.

Married with that is, because you're doing that, allowing serendipity to take hold and not being scared to embrace opportunities as they present themselves. Because there's never going to be a perfect time or a perfect answer. So to some degree, you just have to throw yourself to the wind and assume you're gonna fly. And if you don't, that the landing's soft enough and you'll figure it out.

Jon Chee - 00:32:50: Yep. Hell yeah. Honestly, that's spot on. Probably I could have used that advice when I was just like, "Here are the things that I think I need to do by this time in order to get to this next thing." And the times where I felt most lost was when that was my game plan, even though it felt more structured and organized. Definitely was just like, "Oh, what the hell am I doing?"

Caleb Appleton - 00:33:15: It makes it way less fun. I quit doing triathlons—I mentioned earlier that I did triathlons at a pretty elite level in college—and I stopped doing that when it became so structured that missing a workout or having a bad day was creating ancillary stress in my life.

Jon Chee - 00:33:33: Yeah.

Caleb Appleton - 00:33:33: I felt like, "I just don't need this anymore." I love each of these sports individually; I'm just going to do those. I think the same is true in your career. If you try to over-architect it, you end up having a lot of stress about, "Did I do this right? Am I behind on this thing?"

That's exactly perfect. When you allow curiosity to lead the way, it might take longer, it might be circuitous, it might not always be clear, but what will be true is you're enjoying the thing that you're doing along the way.

Jon Chee - 00:34:05: Yeah.

Caleb Appleton - 00:34:06: And it's much easier to wake up and do something you enjoy than something you feel obligated to do.

Jon Chee - 00:34:11: Yeah. Absolutely. And it's easy to forget that too. Awesome advice, to be honest. Caleb, thank you again. This has been super fun, and thank you again for being so generous with your time. We're in the same neighborhood, so let's go climb, let's grab some coffee. I'm embarrassed... I was going into the rock climbing gym way more, but now I've kind of fallen off the horse. So I'll have to shake off the rust the next time we get back there. Well, thanks again, Caleb.

Caleb Appleton - 00:34:38: Yeah. I appreciate it.

Outro - 00:34:41: Thanks for listening to our four-part series featuring Caleb Appleton. From College Station to Georgia Tech, Bain, Innovation Endeavors, leading a pandemic turnaround at TuneIn, and now investing at Bison Ventures, Caleb's story shows how embracing serendipity and proving you can do more than advise leads to breakthrough innovation at the intersection of biology and computation.

If you enjoy the show, please subscribe, leave a review, or share it with a friend.

Join us for our next series featuring Roy Maute, CEO and Co-Founder of Pheast Therapeutics, a clinical-stage biotechnology company developing novel innate immune checkpoint inhibitors to revolutionize cancer treatment. Before founding Pheast, Dr. Maute served as Director of Translational Research at Forty Seven, Inc., leading the biomarker strategy for the breakthrough anti-CD47 program.

Following Forty Seven's $4.9 billion acquisition by Gilead Sciences in 2020, he launched Pheast to pursue the next generation of innate immunity targets. At Pheast, Dr. Maute leads the development of PHST001, an anti-CD24 monoclonal antibody targeting macrophage checkpoints in the tumor microenvironment. The FDA has granted Fast Track designation for advanced platinum-resistant ovarian cancer. With a PhD from Columbia, a BA from UC Berkeley, and deep translational science experience, Dr. Maute's journey from pioneering CD47 biology to building Pheast's CD24 platform demonstrates how scientific insight can activate the immune system to eliminate cancer, making this a conversation you won't want to miss.

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