The Hidden Skills Scientists Need to Build Real Companies | Caitlyn Krebs (Part 2/4)

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, Caitlyn shared growing up in Hawaii, a turtle tagging project that sparked a lifelong love of science, navigating Brown University's humbling academic environment, and landing at BayBio at age 27 to manage a 26-person board of biotech CEOs. If you missed it, check out part one. In part two, Caitlyn talks about building BayBioNEST, a scrappy pre-accelerator program she launched alongside the co-founder of Amgen, and then joining Entelos doing biological modeling and virtual patients twenty years before AI was a buzzword, where she posed 40 deals with the world's largest pharma companies using a bake-off strategy that lets the models speak for themselves. She shares the pivotal moment she realized she needed to be inside a product company and what it felt like to land Tethys Bioscience, a diagnostic startup racing to prove that prediabetes was a real, diagnosable, treatable disease before anyone else in medicine was willing to believe it.

Jon Chee - 00:01:45: And so at BayBio, it sounds like you're managing, you know, obviously, large board, many stakeholders. What were some other responsibilities that you had while running BayBio?

Caitlyn Krebs - 00:01:55: So number one was fundraising, actually. So it was a membership-based organization. And so going to the Genentechs, the Gileads, the Coolies, and asking for dollars. So, actually, that was really a second time that I was fundraising—different than the startup, but in more of a ecosystem-based community. The other piece that I really loved was I started a group. It was called BayBioNEST, network for entrepreneurial strategies and tactics. But the idea was you had all these really smart scientists who didn't know how to build companies. There were no accelerators at that time. And so this was, like, pre-accelerator. It was like, alright. We have expertise, and we can tap into the community. And so we started that. And one of the first talks networking events, we actually did at Stanford with George Rathman, who's basically the co-founder of Amgen, so on the science side. And so you had these incredible people who would come and talk to these folks from Berkeley and UCSF and Stanford and UC Santa Cruz. And I just love that. I was like, "Okay. Can we put, you know, startup in a box and really support these young scientists who needed more of the business acumen on how to build a business?" And so I love that. That was something that I really enjoyed.

Jon Chee - 00:03:18: I was gonna say, like, it's also one of the things that I hope this podcast can help people with is, like, learning about the business aspects. There's a lot of folks who are coming from the bench. Where I don't blame you for not having time to learn about business because you're busy enough. I think too, there's, like, a lot of educating that needs to be done even to this day, like, even to this day. Like, kind of reminds me of your previous experience at your first startup. Those kinds of lessons are critical, like, super critical even in a biotech company. And the thing that breaks my heart is when you see a company that's, like, super promising but just, like, missed these kind of, like, foundational business principles and practices, the outcome could have been very different if we just missed those, like, common pitfalls. For example, financial discipline.

Caitlyn Krebs - 00:04:12: Yes.

Jon Chee - 00:04:12: Financial discipline is not specific to any industry. Like, no. No. Right?

Caitlyn Krebs - 00:04:18: Or IP. Right? IP in this space. And then academic really understanding IP and making sure that if you have an idea and it's coming out of the university, you have to be very careful about how you handle that.

Jon Chee - 00:04:32: Yeah. Like, don't just go to, like—and just say it on a mic like at—

Caitlyn Krebs - 00:04:36: Right.

Jon Chee - 00:04:37: Careful what you say on the mic because then it's in the public domain, and that could be a make or break for you. And I'm glad now there are tons more resources.

Caitlyn Krebs - 00:04:46: There are so many resources.

Jon Chee - 00:04:48: So many. So, like, now is a great time to, like, be able to just, like, self-learn. Like, there's so much resource out there. But back in the day, it was, like, really nothing. Like, actually nothing.

Caitlyn Krebs - 00:05:00: There was nothing. In fact, when I was at BayBio, the first—I'll call it an incubator—really popped up, the San Jose Incubator bioscience incubator. And they basically said, "Look. We're gonna offer you lab space, and we're gonna bring a bunch of services." So they would bring in lawyers. They would bring in accountants, your point about financial literacy. And that was really, I think, the first time where now you have accelerators and programs, you know, virtual ones, and there are so many of them, but that was the early days of that. So, yeah, I'm kinda proud to say I think it was ahead of the curve there.

Jon Chee - 00:05:35: Yeah. Definitely. And it was much needed. Like, definitely much needed.

Caitlyn Krebs - 00:05:39: Yeah. One other thing just kinda thinking about my career is I love being on the edge of, like, cutting science and technology, and that is really the theme throughout my career. It's not that I think I can predict the future, but I just am enamored by new technology and science, and I think I just pick up on it a little bit early on. So we're doing the endocannabinoid system now, but, you know, I've been in prediabetes and Alzheimer's and cancer genomics early days. And so that's, you know, just something that most scientists do, too. Like, they just love the science and the tech, and then it drives them to build their businesses.

Jon Chee - 00:06:19: Absolutely. And I'm guessing at BayBio, you were able to get a ton of exposure to, like, the bleeding edge.

Caitlyn Krebs - 00:06:26: Yes. Yeah. You would see, as I mentioned, these young entrepreneurs coming in wanting to build businesses with some really interesting technology, and you saw a lot of it very early. And I could also learn what not to do. I'd see company biotech companies failing too. I think at the end of the day, it's really all about the science and the data, and so you really have to have really good foundational science and IP also to actually build, you know, a viable business.

Jon Chee - 00:06:55: Absolutely. Yeah. And I think exactly. Just so you said, like, knowing what to do and what not to do—

Caitlyn Krebs - 00:07:01: What not to do.

Jon Chee - 00:07:02: Also very important. Again, the thing that breaks my heart is, like, seeing the same mistake repeat. Like, oh god. Like, that problem was solved. Like, that was solved a long time ago.

Caitlyn Krebs - 00:07:14: Although sometimes you have to make the mistakes, right, to learn. Like, that's the—yeah. Yeah.

Jon Chee - 00:07:19: The only way. I guess this is very human nature.

Caitlyn Krebs - 00:07:21: Yep. Yep.

Jon Chee - 00:07:22: That's just a human nature thing. Like, what I always say is just like, I can tell you how hot fire is, but you really don't know until you touch it yourself.

Caitlyn Krebs - 00:07:29: Yeah. That's good. Yeah. That's exactly right.

Jon Chee - 00:07:32: Like, yeah, that stove is really hot. I don't recommend touching it. You don't really know until you, like—no. No. Touch the thing.

Caitlyn Krebs - 00:07:38: I have little kids. They've learned that lesson the hard way.

Jon Chee - 00:07:41: Like, it hurts.

Caitlyn Krebs - 00:07:42: It hurts. Yep. You are gonna be burned. Yep. Get some ice.

Jon Chee - 00:07:46: Yeah. Yeah. You will not like this. And so, you know, it sounds like you're getting exposure to the bleeding edge. And was that kind of, like, I guess, a cue for you? Like, I need to join the bleeding edge.

Caitlyn Krebs - 00:07:57: Yes. That's exactly right. I was like, "Okay. I'm supporting all of these biotech companies now. I wanna be in it. I wanna be part of a company. I wanna be building products." And so that led me to a company, Entelos. It was a modeling and simulation technology company. So, again, like, way ahead of AI. I mean, we had biological models in computers and in silico, and we could simulate, and pharma was our customer: mechanism of action, clinical trial design, doses. And we had different models. We had a cardiovascular model and a diabetes model, RA model, and so we had something called virtual patients at that time. They're now called digital twins.

Jon Chee - 00:08:39: This is so crazy. You were—this is so crazy.

Caitlyn Krebs - 00:08:42: We—yes. We were doing this twenty years ago.

Jon Chee - 00:08:44: Yeah. This is mind blowing because, like, I think people are just like, "I'm the first." It's like, no. No. No. No. No. No. Caitlyn was the first. No. Caitlyn was the first.

Caitlyn Krebs - 00:08:53: We were doing this a really long time ago. Yeah. Yep. And so it just takes time. At that point, I was doing business development. BD was, like, the new hot role back then, and I really wanted to do BD. So I networked myself into a job at Entelos and got a ton of experience, basically selling, you know, modeling and simulation technology to big pharma to the big guys: J&J, Pfizer. We actually even worked with Philip Morris at the time. So a lot of these companies were cutting edge. They were looking at this twenty years ago. So QSP modeling, it's called quantitative systems pharmacology, basically, like PKPD modeling. It was born at Entelos, and everyone went to big pharma. And so you can probably find an Entelos team member at all of the big pharma today doing this modeling. It's pretty incredible.

Jon Chee - 00:09:45: That's badass. Maybe let's just set the table. What is BD?

Caitlyn Krebs - 00:09:49: Ah, yeah.

Jon Chee - 00:09:51: It's used a lot, and I'm not sure if it's quite defined. Like, sometimes people have different interpretations of what BD is.

Caitlyn Krebs - 00:09:58: Yeah. So BD, you're right. It depends on the company, really. So business development, typically, it's developing partnerships, bringing in customers, collaborations. It could be true sales. Some people tag it as a sales role, but really in biotech. In biotech, it is you either have a molecule that you're trying to license to somebody else, and it's doing that deal. So part of it is it's a transaction. Right? It's a negotiation. It's a legal arrangement. It's selling them on the science, or it's in-licensing. Right? So you're actually bringing a compound into your organization. For me in Entelos, it was basically selling research collaborations to big pharma, and that was very hard because this was new tech. They didn't trust the technology. The model was basically a black box kind of like AI is today. But the thing about modeling, and we're using it here at Nalu, and I brought Tom, one of the co-founders from Entelos, into Nalu because I'm such a believer in biological modeling. And in a model, you have to understand the biology well enough to actually put it together mathematically. And most of biology is a feedback loop. The endocannabinoid system is a feedback loop. And so if you can actually model it, you have to understand all of the biological inputs. You talked about estrogen. Right? So for us, estrogen is really important in endometriosis. It feeds these endometrial lesions. And so we at Entelos had sometimes software engineers who could tell pharma how their drugs worked better than pharma could because you had to put all of these pieces together. So they would bring in some of our scientists and some of our engineers to actually teach them about their drugs, and that was really eye opening for me as a young BD person, as a scientist, to realize that looking at it from a modeling perspective and having to really add the entire system up, really then you understand the biology. Because most scientists just look at it: "Oh, it's one pathway. It's straightforward. It's downstream." We know biology doesn't actually work that way. Like, it's a closed system.

Jon Chee - 00:12:18: Yeah. For sure. I was gonna say, at least when you're having those conversations with these big players, it's not something you can just like—you know, there's, like, a whole thing about vibe coding and, like, vibe—no. No. Don't—you could not vibe this.

Caitlyn Krebs - 00:12:29: Like—you could not vibe code this. That was the downside of the company is it was these very intricate bespoke models that then you would add pharma's data into—you know, siloed off from, you know, Pfizer and J&J's data wouldn't overlap, but it was a high-touch services model. And I wish you could have just vibe coded into these models because it would have been much easier for the scientists. But it—I mean, you know, you had to—there's a lot of public data that went into these models, a lot of proprietary data that went into these models. So that was a challenge. It wasn't as easy as just vibe coding like you can do today.

Jon Chee - 00:13:05: Yeah. Yeah. Totally. And when it came to, like, breaking the ice with these large players, it sounded like it was very much just like you had to, like, show them. Like, you had to just, like, show them the value, like, almost, like, immediately because it's like this novel. Or did you crack it a different way?

Caitlyn Krebs - 00:13:21: No. I mean, so from a BD perspective, right, like, a lot of pitching, explaining the models, explaining how they work. But my favorite term that we used to use is we do a bake-off. We'd say, "Okay. Give us a study that you've already run. You know the answer to. We will simulate it, and we will show you what our model says." And so this was, like, how you got in. This was, like, the pilot. They're—we're like, "Oh, we're so confident that we can model this for you." And that's when their eyes were opened. Like, you could simulate the results, but then you could tell them something that they didn't know about their compound or that they shouldn't have run three arms of the study they could have proved the efficacy with two, like, some very specific examples.

Jon Chee - 00:14:04: Love that. I love it, like, getting the—like, a kinda, like, tactical element to it. I think a lot of startups right now are trying to also figure out this BD element.

Caitlyn Krebs - 00:14:13: They are. They are.

Jon Chee - 00:14:14: It's like, "How do I get giant organization to want to actually take the risk to work with smaller organization?" But I love what you did was kind of just like, "This is super low stakes for you. You know the answer." Like, you know the answer. There's nothing novel. Yeah. Yes. I mean, there might be something novel, but, like, you've seen it already. Yeah.

Jon Chee - 00:14:34: This is not something that's, like, unfolding in real time that could just blow up in your face. It's like, this is in the past. It's done. You've count that as a win already. Let us take a peek at that, no skin off your back, and let us show you, like, how this thing works. And I think that's very elegant to do it because I think whenever I think about, like, working with these large organizations, much like when you were managing a 26-person board, it's, like, understanding their incentives, what they care about. And a lot of the time, there's, like—with large organizations, it's like, there's a risk aversion.

Caitlyn Krebs - 00:15:03: Yeah. The risk tolerance is so much different than a startup's. Yes. So—I've lived that so many times. Yes. Like, the companies wanna do it. Yeah. But legal, regulatory, yeah, that's where these things really break down.

Jon Chee - 00:15:17: Yeah. There's, like, a different risk profile that they're shooting for, but, like, finding a way to marry that—like, the startup energy with their energy and meeting at the right place—is, like, key to this, at least from what I'm hearing. And so it sounds like this role at Entelos was, like, very formative. You now are, like, figuring out how to, you know, basically work with these large organizations, and you learned a lot. When did you know it's time to move to your next opportunity?

Caitlyn Krebs - 00:15:46: Yeah. So I loved Entelos. I love the exposure. I also—what I learned at Entelos too was I actually love reading legal contracts. I didn't realize that because in a services organization, I probably did 40 deals while I was there. So I saw a lot of different kind of ways to—particularly with IP. I mean, IP working with large pharma, that was the big sticking point. But I knew I wanted to be in a product company. I knew I wanted to touch patients. I really wanted to understand the healthcare system. And so that's when I moved to Tethys, so the prediabetes company. And that's where I really got exposed to much different ecosystem within healthcare.

Jon Chee - 00:16:28: How did that opportunity come about?

Caitlyn Krebs - 00:16:31: I had, I think, a coworker from Entelos who mentioned this company. They weren't working there, but they said there's a really interesting company in the East Bay in Emeryville. I mean, I've worked all over the Bay Area too in Emeryville, which was kind of an up-and-coming place to have a company. And so I went and met with the CEO, and they were looking for a BD person. And so, again, just by skills translated, and I ended up at Tethys Bioscience.

Jon Chee - 00:17:01: Very cool. And was this form of BD different than the Entelos form of BD?

Caitlyn Krebs - 00:17:08: Yes. So this BD—this is where I really understood how to sell in. So this BD role was less of a collaboration, and it was a more selling into physicians. So it was primary care docs, and you were convincing them to use—it was a diagnostic test. It was five different blood-based biomarkers to predict your risk of diabetes. So, again, cutting edge. Nobody could predict if you're gonna have diabetes. In fact, physicians didn't believe that prediabetes was a disease. It was not a disease. There was no, like, ICD-10 code. There were no codes for it. And so you had to convince physicians that you had a test that would say, "You know what? You're not diabetic yet. You're prediabetic, but then you need to do diet and lifestyle." You know? This is basically a change of lifestyle to prevent it. And so we sold into primary care physicians. We also tried out a business model of selling into employers, into health systems. So I then really understood the full ecosystem of the healthcare industry: patients, employers, physicians. I would map the money. The money all comes from employers. So we looked at the ecosystem, and at the end of the day, the employers really hold the purse strings. And so how do you convince employers to use your product or your technology?

Jon Chee - 00:18:33: Very interesting. And I think that view is a rare one to be able to see and connect the dots.

Caitlyn Krebs - 00:18:41: Mhmm.

Jon Chee - 00:18:41: And they might feel, like, all over the place. But I think sometimes it's hard to keep all of this in your head. Like—and it's also, like, because the time scales are so long, it's hard to kind of do this, like, forecast. I put myself in—maybe your tech transferring out of school, this technology from academia, and you're just like, "I'm just focused on getting this proof of concept," like, first step, baby steps, like, crawl, walk, run. But it is important to also think about everything that's downstream because that also informs what you're doing right now, which is a really hard exercise.

Caitlyn Krebs - 00:19:15: Which is very hard. And in fact, I think this company is the poster child of that. So we had a test. We sold, I think, a 150,000 tests a year, which is actually a lot. We had thousands of physicians across the country using the test. They loved it. Pfizer Insurance was reimbursing: Aetna, United, Cigna. And so I actually—this was a case study for me in reimbursement. And so how do you get reimbursed? How do you price it? And in this world, there were basically diagnostics codes, so ICD-9 codes for a number of the biomarkers. But this is where the company failed, and this is your point about looking forward. If you don't understand the regulatory environment and this company made a mistake with Medicare—there was a woman basically at CMS who didn't understand the test. She thought it was exploratory. We had all this data, and Medicare—I remember the day Medicare decided they were not gonna reimburse for the test. And when that happens in healthcare, guess what? All the private payers shut it off. We had raised, I think, $200,000,000 by Kleiner or David. We had some very serious investors, and the company made a strategic error on how they manage the relation—again, relationships. Right? It was really about the relationship with Medicare. And so you're right. You have to look for—like, even now today, I have to look at how is my therapeutic going to get reimbursed? How do I show the data that backs up the claims that they will pay the price that I want them to pay? Like, you do. You have to look out into the future because if you don't reverse-engineer it, it will kill you. Unless this company—it died. It died because Medicare basically said, "Nope." Out of business.

Jon Chee - 00:21:05: That's the craziest part. It's hard enough to, like, solve the science problem. Right?

Caitlyn Krebs - 00:21:09: Yeah. It's—

Jon Chee - 00:21:10: It's already—it's hard enough. Right? Yeah. That's why I always think this is, like, a miracle. Right? It's, like, an actual miracle when it goes the distance. Right? And I think friends of mine who are kinda going through that process, similarly, just like a private insurer trying to get to Medicare, and they were saying—I don't know if this is still the case, but he's like, "There's, like, three people who, like, govern your faith on whether this thing gets Medicare reimbursed."

Caitlyn Krebs - 00:21:35: It's very true.

Jon Chee - 00:21:36: I was like, "What?" Like, how can the fate of your company and science just boil down to these, like, three people?

Caitlyn Krebs - 00:21:43: And you know what? It's like pitching to a VC. Right? You pitch to them. They might remember you. They see hundreds of companies, and they might forget you. And so it was this constant, like, "Are we at the top of her list? Does she remember who we are?" And you'd have to, like, re-educate her every three months. It was really challenging, like, very challenging. But you're right. You can get the science right. You can get the funding right. You can get the commercialization right. You can get physicians on board, employers. But if you miss—I mean, regulatory is, like, the number one. Like, if you don't get that piece and you don't get the reimbursement right, you're—you're done.

Jon Chee - 00:22:21: And so is that why—and and this is me just, like, theory crafting or just, like, formulating in my head—so a company wanting to go the distance all the way by themselves. Right? You have to have all this expertise in-house. But is the value proposition on doing a collaboration with a—like a large pharma who has handled regulatory day-in, day-out—is that a value proposition? You're like, "Hey. Like, in theory, I understand what it takes to get these three people on board with this reimbursement. However, you have a huge regulatory apparatus that I could benefit from," but you—obviously, that means you give up upside.

Caitlyn Krebs - 00:22:57: Yes.

Jon Chee - 00:22:58: Is that the consideration?

Outro - 00:23:01: That's all for this episode of The Biotech Startups Podcast featuring Caitlyn Krebs. Join us next time for part three where Caitlyn recounts building Tethys to 150,000 tests a year and winning reimbursement from Aetna, United, and Cigna, only to get blindsided by Medicare on maternity leave with a three-week-old, and how she turned a company shutdown into a consulting engagement that would produce one of her most important future co-founders. 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.