The Bank Heist Model: How to Build Your Startup Team | Sergey Jakimov (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, Sergey shared stories from his childhood in post-Soviet Latvia, his years training in tennis, and the path that led him from a parliament internship to graduate studies in Budapest. If you missed it, check out part one.

In part two, Sergey talks about student life in Budapest, the uncertainty of what's next, and the accelerator event that sparked his first startup, a CFD venture he launched at 22 with no experience and nothing to lose. He also walks us through his pivot into medical devices, the bank heist model of assembling teams, and how he later built in clinical data, speeding trial recruitment, selling outcomes to pharma, and helping stand up national biobanks.

Jon Chee - 00:01:21: How was just living in Budapest?

Sergey Jakimov - 00:01:23: Oh, it's cool. For a student, it is extremely welcoming. It's not expensive. It's pretty cheap. It has a very distinct atmosphere to it. It's a very historical city. It's an imperial city because, you know, the Austro-Hungarian Empire back in the days. So all the palaces, all the castles, all that imperial, monumental stuff is there. It is beautiful architecture-wise.

We did rent, honestly, for pennies. We ended up renting with a course mate of mine. We teamed up together, and we rented a post-revolution type of apartment, this old apartment, which was like 300 square meters. It was absolutely massive. It had zero renovations done with it since, like, 1950s or something.

Jon Chee - 00:02:08: Yeah.

Sergey Jakimov - 00:02:08: But it was absolutely massive, and I absolutely loved it. So whenever you have an opportunity to visit Budapest, somewhere is best, but any time of the year is best for you. You should absolutely go, no second thoughts. This is a tremendous place to be.

Jon Chee - 00:02:22: My wife is Hungarian, so I ought to get out there.

Sergey Jakimov - 00:02:25: You absolutely should. No. Budapest is still one of my, if not favorite, European capitals, honestly.

Jon Chee - 00:02:32: Very cool. And while you're getting your Master's, was this when you started to get the entrepreneurial itch?

Sergey Jakimov - 00:02:39: In a way, I mean, you're going to call it an itch. I started to think, "What's next?". I was still doing my side gig work and whatever online, but this MA is sort of pressures you to pick your paths. And a lot of folks that I went to the university with from BA, they went to work governmental jobs. Like, they went to work in the Ministry of Foreign Affairs and, you know, in the economic ministry in Latvia and whatever. And a lot of folks that I went to the university in Budapest, they went to work in consulting. They went to work with McKinsey. Someone went to BlackRock. So, you know, good positions, good companies.

I was not sure what I wanted to do. I was not sure. So it was this situation where my mind was wandering. And I do remember it pretty vividly. Everyone around seemed to have this very clear understanding of what they wanted to do with their life, and I didn't. And that was, I wouldn't say it scared me. It didn't scare me, but it did raise some uncertainty. Because, well, everyone is so focused and so crystal clear about what they want to do with life and how they want to work in a big company and do this and do that. And I was like, you know, I have absolutely no freaking idea. I was absolutely no freaking idea. And I was pretty sure that I didn't want to work at McKinsey. I mean, again, no shots fired at McKinsey. It was not appealing for me in a way that I would commit my life to it.

So in one of the trips back—I was still second year in MA—trips back to Latvia, a friend of mine actually offered me to just attend one of the events in Riga that one of the tech accelerators was putting together. And it sounded like mumbo jumbo to me back in the days because it was like, you know, "deep tech, science-based startups, blah blah blah". So I ended up attending this event, and I ended up meeting co-founders. And we ended up working on the same idea eventually for the first company I co-founded. And this is how we got into thinking first about what I wanted to do.

And what I wanted to do, really, is I still did not abandon my interest in life sciences because, look, my whole life, I'm struggling with this concept of added value. Okay? So whenever you do something, it should bring added value. What I cannot stand is uselessness. Yeah. No. Seriously. Like, it's not that everything you do should have a meaning. Absolutely not. The point is whenever you do something big and whenever you try to pick a vector, make sure it's useful and make sure it's actually interesting to you.

So, and I was like, well, I can't say I failed to become a doctor. I never tried to become a doctor. I didn't necessarily fail, but I did not start. So, I did not even try, which sometimes is close to failing. So I failed to become a doctor, in all fairness. And I was like, well, these guys in the deep tech space, like, in all these deep tech startups—and I was looking at the industry and people are building companies in biotech and whatever, not in Latvia, but elsewhere —I was like, well, I mean, they are doing this, and it doesn't seem impossible. Right?

I didn't know anything about it. That helped, as I understand now, because whenever you don't know anything about a specific industry, well, you're kind of standing there with your pants off. But at the same time, you don't have the boundaries that were imposed on you by education or whatever prior experience. So you don't have this automatic "no, it cannot be done" type of situation. So you kind of assume everything as a blank sheet.

And I did not have anything to lose, honestly, absolutely zero. So this is where I thought I might try it as a founder. I might try it as an entrepreneur, whatever you want to call it. I don't like the entrepreneur saying; whenever people ask me about entrepreneurship, I always imagine a person who actually sells something and buys something, does this clever "buy cheaper here, sell more expensive there" type of thing. I have this very cliché concept in my head, so I'm not an entrepreneur by any means. But, yeah, I thought I might become a founder.

Maybe there is a hack. Maybe there is a pattern of how to build these companies without having an education in a specific field, just by surrounding yourself very much so with soulmates that were good in something. And it has a lot of details to it, but conceptually, it turned out to be true. Conceptually, I think that building a deep tech company or building anything, pretty much, like being a founder in anything, it's like planning a bank robbery. It's like putting together a crew where, you know, you need a driver, you need someone to pick locks, you need someone to not sell, and you need someone who has the intellectual capacity to come up with a plan. Absolutely same thing. So it's like you just surround yourself with people that are very good at these certain aspects that you identify for yourself as key areas in whatever industry. And chances are—I mean, the success rate is still super low—but chances are that you managed to pull something off. And this is what happened with the company number one.

So that was started. It was a company in the engineering space. So deep tech, not life sciences yet. Very much the first try. I was 22, and I was still in Budapest. So I was still kind of graduating. I went back to Budapest to finish my coursework and my thesis, which I was very much writing in the last day, honestly. Like—

Jon Chee - 00:08:08: Yeah. You're running a company.

Sergey Jakimov - 00:08:10: I was actually running a company, but it was an idea of a startup that we started to kind of put together and glue together. I was a disastrous academic. Maybe I could have excelled in some things, but being in academia is not one of those things. I graduated with a good diploma and a good GPA and everything, but being in academia was not for me. So I finished my coursework, my thesis, and I went back to Riga. And I thought, well, I had a bit of money saved up, so I thought, well, why not try the founder's route?

Jon Chee - 00:08:40: Very cool. And what was it about the founder's route that resonated with you? Or did it resonate with you at that point?

Sergey Jakimov - 00:08:47: I was trying it out. I did not have any expectations of building a business, of being an entrepreneur. I also had nothing to lose. Literally, I had nothing to lose. So, like, a few thousand euros that I saved up? Not really a huge deal if you think about it. I didn't have any business background in my family. My mom, my father, they were never in business, so they were working, like, normal work. They had a job. That's what you call it. So I had nothing to lose. It was just basically trying to learn a new skill by doing. That's it. I can't say I heard a calling or a voice from above or something. I just thought that I would try, and, intuitively, it did not feel as something alien, so I tried.

The first company was in engineering. It was in CFD modeling originally. So CFD stands for Computational Fluid Dynamics. My co-founders and technical co-founders were good at simulating the behavior of fluids in closed environments. CFD modeling is something that everyone uses in the aerospace industry. For example, like NASA is using CFD to simulate, you know, the aerodynamics of things and air flows of things and the water or the liquid flows of something, you know, ending up with most probably the flow of fuel and the fuel lines of a rocket. And we did it for a closed environment, and our application that we found was in the oil and gas industry.

We found our first customers there, and we did raise the first money. Interestingly enough, we only got the first check—it was a €50,000 investment —after we secured the first contract with an oil and gas operator to actually trial us out. And that was really funny because, in hindsight, if you think about it, that was an absolute disaster of a setup. That was a very poorly staged bank robbery, that one. Because the founder was 22, no experience, and the oil and gas is one of the most conservative industries out there. You literally get into the room, and they're all like 50-year-old dudes that were doing this for like the last 30 years, and their grandfather was doing it as well somewhere, God knows where. And the processes of getting the oil out of the ground in oil and gas did not change much in the last 100 years. It's still basic physics. It's all sensors and simulations now, but it's still basic physics at the core of it. So whoever entered that room needed to have some sort of reputation in the eyes of these people, and I did not have a single reputation point at all.

So it was a super miserable experience, but we managed to land the first contract, first trial pilot, and the first investment. And this is where we kind of started to develop there. And with that company, we worked with operators in Europe, Latin America, and the Middle East. So that was kind of the first step. Seems like a pretty good first step. It was the least obvious thing to do. If you ask me, would I voluntarily do it 15 years ago, right when I was 18, I would have second thoughts about actually doing it. I wouldn't lie to you. I would not dive right in.

Jon Chee - 00:11:55: You needed to be that naive 22-year-old to jump in first.

Sergey Jakimov - 00:11:59: For sure. And, honestly, the position of having really nothing to lose in a good way. It was not that I was starving under the bridge. It would not be true. But I was just an average graduated student that was 22 years old, so why not? That was the first stab.

And then the second stab was a second company that I started almost in parallel to the first one, actually. Same setup, but I was desperately into life sciences. And with that company, it was the first stab at life sciences. It was in medical devices. And this is where I think we ended up being one of the first groups out there to create what is now called drug-eluting coatings or drug delivery coatings for orthopedic implants—for reconstructive surgery implants, all the titanium plates and screws that surgeons would use to reconstruct someone's face or, you know, spine or whatever that is after traumatic injuries. And we later also moved into dental implants.

And our thing was most of these implants were made of an alloy, titanium alloy, but it still has its own problems with bio-integration. And sometimes these things are getting rejected by the body of the patient. So the answer of the industry would be to coat them with something, and mostly that something would be like a one-layer hydroxyapatite coating. Hydroxyapatite is synthetic bone. It's just a powder. Right? And then you have a bunch of methods like plasma spray and whatever. And what we had done is we've adopted the method that was originally not used for these type of applications that came from the industry, and that was high-frequency magnetron sputtering. And this is where we basically vaporized it, and then we made it adhere to the base alloy instead of blasting the implant with something that kind of deposited it. Depositing is the right word.

And by doing so, we basically ended up being able to create very thin and very flexible coatings so that they do not crack under pressure when the surgeon is physically installing an implant. Because I don't know if you imagine how a hip surgery looks. Right? But what do you think is one of the most used instruments, tools of an orthopedic surgeon?

Jon Chee - 00:14:05: I don't know. I can imagine it is a brutal surgery.

Sergey Jakimov - 00:14:09: So, like, a hammer, a chisel, or a saw would be my top three of the orthopedic surgeon tools. So these coatings should be very flexible, should be durable. And for that, they should be very thin and very adhesive to the base layer. So they should stick pretty much. They should not delaminate.

And then we went further. And because of our method, we were able to deposit multiple layers. We created a sandwich of these coatings. And by playing with the temperatures of how we treated these coatings, we could essentially regulate the dissolution time. At some point, we also ended up being able to make them of different morphology. So some would be absolutely flat. Some would be porous. And the more developed the morphology is, the easier it is for osteoblasts for new bone to actually grow to the surface. And because of that being porous, we were also able to kind of impregnate it with basic drugs such as anti-inflammatory or something like that. We would basically just soak it at some point in one of our early prototyping. So, yeah, that ended up being pretty efficient with reducing, locally reducing, inflammation, and as a consequence, raising your bio-integration success rate. So dropping the rejection percentage, that was the second step.

But what was evident by that time was that the pattern of building these companies and just pretty much starting something—successfully or not successfully doesn't really matter—but the pattern of things that you need to have as input variables and then certain manipulations that you want to achieve in the process and certain milestones you want to show and certain things that enable you to raise money, they were pretty much translatable from industry to industry. Right?

And then the other interesting thing that we observed was that you can actually learn a new skill pretty fast. You can get to terms with a new industry fairly fast. You really need, like, half a year to reach a PhD level of conversation in that specific industry if you actually are involved in it, building something in it, interestingly enough. So you don't necessarily need a degree to understand what's happening around you. You, of course, need specialists and highly educated people around you when you're building very specific things. Like, I do not pretend to be a molecular biologist. But in order to sustain a conversation and understand what sort of people you need around you, it's actually pretty fast. Whenever you have your butt on the line as a founder, the learning process is just tremendously fast.

Jon Chee - 00:16:36: I love that. And there's so many directions I want to go with that because I completely agree that I think sometimes, particularly in the life sciences, there's an inertia to just follow this track of get this degree, study this thing, focus on that thing. And then at that point, you unlock the opportunity to tackle this problem. It is not to say that having highly educated specialized people is not important. It is. But there is still value of coming in with exactly what you said, not having the hang-ups. I think everyone would surprise themselves how quickly you could learn if you just apply yourself rigorously to it. And I think, too, the bank heist imagery in my head is always thinking about like, Ocean's 11 or something where it's exactly that. You kind of just need the right people for the job. And then, obviously, it's important that everyone works together. And, usually, that's a person that's like glue that just kind of keeps it together and everyone working in sync.

Sergey Jakimov - 00:17:30: Interestingly enough, very often, it is the least specialized, so the least educated person on the topic. When we were talking about vertical education, right, not horizontal. The horizontal skill set is a bit different, but in terms of the vertical, the depth of the knowledge, that glue very often—the founder and the CEO, whoever—very often is the least educated, but that's okay, you know, because of the capacity to kind of collect these people around.

So I'm absolutely not a fan of the "drop out of school" type of religion. I think that there are cases when this just comes organically as something that, like, there is no other way, sort of thing. And then it becomes a tremendous success story and, like, things that they would teach you at Harvard Business School and whatever, the whole Zuckerbergs of the world type of dropouts, creates a multibillion-dollar company. But in general, I think that, especially working in biotech, the value of education is tremendous. I am absolutely against this widespread, almost ideology of, "You don't need education or you don't need standardized education to achieve things or to build things".

You might not find your specific degree very useful as you go along in your founder's route. But what you will find useful is the skill set that a good university actually teaches you. And that skill set is research. That skill set is being able to filter the signal from the noise because any university would basically force you to dig through a ton of material on any topic and then being able to digest this material and distill it to some sort of sense. So all these things, you just get training in being consecutive in your work and organized, and it's not a bad thing. Literally, it's not a bad thing. So I think this is what education gives you. So I'm absolutely against this "dropout of kindergarten" type of thing and, you know, go build because this is where we're heading.

I mean, honestly, looking at some Silicon Valley stuff that's getting published. First, people were encouraged to drop out of the university or grad school. Then it's the very first years of your kind of BA, so undergrad, I guess, that would be in the US. And then now people are dropping out of high school. To start companies? Yeah. To start companies.

Jon Chee - 00:19:53: I did not know that.

Sergey Jakimov - 00:19:54: There are cases like that already. I think there are a couple of Y Combinator founders right now who are almost like high school dropouts or something. And, again, as someone who likes statistics, there are always these outlier cases, which interestingly enough just reinforce the rule. And the rule is get the education. Don't dig yourself into paradigms that you don't believe in. Don't try to get yourself in an academic cage if you don't want to, but take the best out of the school and the high school and the grad school, whatever that is. It helps. It helps to discipline yourself.

Jon Chee - 00:20:33: You're still forming your worldview and developing your critical thinking. At least when I think back on what education has unlocked for me, at least in the business context, it's really just how to think and the discipline. It really showed you how much hard work is necessary to get through any hard, complex topic. It's not just, like, you can just breeze into it. Like, it sounds like your school education was different. I know hustle culture is, you know, whatever, but it's just, like, hard things require—

Sergey Jakimov - 00:21:04: A—

Jon Chee - 00:21:05: —lot of work and organization and critical thinking.

Sergey Jakimov - 00:21:08: They do. The interesting thing that I've observed in other founders is when someone actually launched the company, and it took off straight away without any work. And I'm very happy for these cases. Again, these are edge cases where they are the outliers. But very often, it also generates the wrong neural feedback loop inside the brain of that founder. And this is where actually working hard for something is more sustainable long term. Because whenever you realize that you've actually achieved something with less effort, you're like, "Oh, got lucky. Nice. Let's enjoy," type of thing. But I know that things might be different, and I'm prepared for the things being different potentially versus you just think that it's all going to be easy, and it most probably won't be easy.

But, yeah, I mean, again, my whole thing, honestly, whatever I did was statistically unprobable , starting from the whole school type of upbringing, as you called it, all the way down to even the things that we do now. All of this was not evident in any sort of way. Maybe that's why it's fun, and that's why it's surprising every day to a certain extent as well. But it was pretty unexpected, for sure. Yeah.

Jon Chee - 00:22:26: It just reminds me of your childhood of learning by doing and just being out there.

Sergey Jakimov - 00:22:31: The childhood is like SEAL Team Six. Watch a documentary on the nineties in the post-Soviet space. The YouTube is full of that stuff.

Jon Chee - 00:22:38: Yeah. You're just like, starting a company is a cakewalk.

Sergey Jakimov - 00:22:41: So starting a company is not a cakewalk, but dealing with all sorts of random phenotypes of people is a skill that university can't teach. Like, you actually need to do it.

Jon Chee - 00:22:51: Yeah. I feel, I mean, look. You're on your bike, and you're probably meeting people of all walks of life if you're spending your time 90% outside just biking around.

Sergey Jakimov - 00:23:00: Some of these people tried to take your bike. Oh, no. I'm usually joking about it, but I'm not joking about it. So, like, you literally learn how to fight with any object that you find nearby. Yeah. And that is from a stick to a stone, whatever is there.

I had countless encounters of me actually fighting my way out of something with a tennis racket because I was going to the session, and someone literally starts to poke you outside with an aim to steal your horse bag or whatever. And I do remember at some point, I was still very, like, I was small. I was like 10 years old, maybe. And my absolute dream was a proper tennis bag. You know these bags which they wear when you watch the US Open or, like, now it's common. Back in the days, for me, it was not common at all. So I only had my tennis rackets were always in these simple holsters, that type of thing, and that's it. I wanted a tennis bag really bad. And I got it for my birthday when I was like 10 years old or something, and it was a Nike tennis bag. And I still remember it very vividly. Like, it was a black one with the sick Nike swoosh and the word. Yeah. I was cherishing it. It was huge. It was almost the size of me. And I was in a very dedicated way. I was plowing my way every evening or every second evening to the stadium with this thing. And sometimes people, it was an asset. Sometimes people wanted to take it. No joke. And then you need to make your choices. And I was very adamant about not giving my Nike bag to anyone. I think at some point, some of those guys just thought that I was mentally not okay.

Jon Chee - 00:24:38: Yeah. And they're just like, "All right. We're backing up. We're going to let Sergey just go".

Sergey Jakimov - 00:24:44: Now it's funny. I can't say it was funny back in the days, to be completely honest with you. So it's pretty rough sometimes. But, again, we're here. I'm still alive.

Jon Chee - 00:24:54: I like the balance of learning by doing that you have and learning via education. Because I think when you go too far in either direction, it's a gradient. It's not either/or. It's not like drop out in kindergarten and go start a company, but it also doesn't mean spend your whole life in school. There's a balance to it, and it's contextual.

Sergey Jakimov - 00:25:15: And all the hard skills that I've ever learned were actually these translatable hard skills such as stats is a hard skill, statistics is a hard skill, like any quantitative methods. It just teaches you how to look at things, at patterns, whatever. Same for the research, same for all the writing and essaying stuff we did at the university. It was not for the sake of becoming an award-winning author or something. Right? It was for the sake of being able to process information and put this information into a condensed format. Something that a lot of people will now be deprived of because they're now using ChatGPT quite a bit. And that is the skill that a lot of people are losing because you kind of don't need it anymore. What you're skipping, though, is that you're also losing your brain capacity potentially, but whatever.

I was never submerged into a specific doctrine of thought. And a lot of professions that are defined, if you wish, such as a doctor, a nuclear physicist, pick one, right, an engineer of some sort, they are submerged in a specific paradigm of thought, a specific set of hypotheses, and a specific set of truths that they have, and they take for granted because it was proven that way. So that's just the way it is. And I was never subjected to that, interestingly enough, and I've thought about it. And this is why I kind of took everything as, "Yeah, maybe, maybe not. Right? Whatever. We can try it out," sort of thing. And it helps.

I see it now in biotech founders, by the way, interestingly enough. Some of the founders doing the craziest stuff out there. It's not necessarily like we would invest in them or I would invest in them as a fund manager. But sometimes the most daring hypotheses, which sometimes lead to success, by the way, come from founders that do not have biotech backgrounds, and they were not submerged into a specific limit and borders of thought of what is orthodox and what is unorthodox in a specific field. That's very interesting. I think it helps to a certain degree as well. You just don't have the authorities in a way. Absolutely.

And there was the book I read, Robert Dugan, Pharmacicholics, and—

Jon Chee - 00:27:19: I think it was, like, ultimately resulted in, like, Keytruda or something of that nature. No science background. Yeah. No science background. And, again, this is not to say that science backgrounds are important, but there's an element of, like, I'd like that just, like, maybe not being able to look at these problem sets with open-mindedness.

Sergey Jakimov - 00:27:39: Unconventionally, indeed. I mean, science backgrounds are extremely important. Whoever is watching, please go and get your science background. It's very important that you get one so we can advance the industry. Actually, we have enough visionaries in here. We actually need people that know well to do things now.

Jon Chee - 00:27:58: Exactly. And I totally agree. I think it just comes back to having the ideal optimal bank heist team. Like, everyone's got to play their part. Yeah.

Sergey Jakimov - 00:28:09: That's true.

Jon Chee - 00:28:10: Your first stab at your first company wasn't perfectly Ocean's Eleven status.

Sergey Jakimov - 00:28:14: It was Ocean's Three.

Jon Chee - 00:28:16: Yeah. Ocean's Three.

Sergey Jakimov - 00:28:18: But then again, it kind of showed that it was possible to get into the other segment. And then I spent another three years or so maybe. I didn't start anything. I actually joined other companies in the space where I wanted to end up, which was aging diseases. Essentially, the suspect. Right? Everything that kills us with age: cancer, neurodegenerative, cardiovascular. And because I had a lot of this experience of building an early stage and going through preclinical into clinical with medical devices, but still, I have quite a lot of understanding in regulators and intellectual property protection.

At that point somewhere, I actually started to teach here at the school and graduate school of law. I started to teach intellectual property and venture capital, like, how knowledge-based capital, how intellectual property actually forms the core of deep tech companies and how this is the major asset.

So I spent, like, three years essentially helping others to package themselves going from preclinical to clinical. I helped them raise money, and these were not Latvian companies. These were UK and US mostly , but how to package them in terms of IP, how to communicate with the regulator, and how to build up the case going from preclinical animal models into the IMD approval, into the human phase of clinical trials, and that helped quite a lot as well.

And then the third company came, which was already in the pharma space.

Jon Chee - 00:29:17: Can you talk about that?

Sergey Jakimov - 00:29:21: I can to a certain extent. So I met with Gary, who is now my partner in the fund, and a bunch of other stuff was built. So we met in 2018, and we started, two of us and our third co-founder, who is now the CEO of the company, actually. So the company was not sold. It's pretty successfully operating. We started a company in the clinical data space.

So we hypothesized that the industry was facing a huge—still facing a fundamental problem. Taking a drug to market takes, like, 10 years. A lot of this—two years is per candidate development, and then it's your preclinical work. And then the last six years, it can be essentially clinical trial work. Right? So Phase 1 to Phase 3. And clinical work can be sped up very significantly if you streamline patient recruitment because patient recruitment is still a very manual thing that your clinical research organizations do, and they do it on behalf of study sponsors, aka pharma companies, so the ones that are paying for the studies.

In most of the legislations, pharma companies are not allowed to directly contact patients. So clinical researcher organizations (CROs) are basically the contractors that are doing all the clinical trial work on behalf of a pharma company. You hire a CRO, and they develop a protocol. They do recruiting. They do all the dosing. They do pretty much everything, like a turnkey solution type of thing. And they're very manual because CROs basically rely on their relationships with doctors or patient organizations or specific hospitals. And these networks of influence of CROs are very regional very often. So, like, a CRO working in Sweden will have connections in Sweden, will not have connections in Hungary or Romania or wherever, far from Sweden. And the whole thing is very manual. These guys are getting paid per patient enrolled, and then they are charging a bunch of other services to pharma. They're very comfortable. They're not really interested in doing it faster.

With pharma, though, every single day you cut from the clinical trial process—and this 10-year cycle is a tremendous amount of unrealized revenue that can be realized. Right? Because the patent cycle is normally 20 years, and then you patent a compound in the very beginning. So, when you have it through a candidate, you patent something, and then you spend another 10 years testing it with a very low probability of success, a horrendous amount of money—hundreds of millions sometimes during these 10 years—and have the approval at the end of the day. And then you have 10 years, if everything went smooth, to recoup for all the losses that you've generated in the first period, plus earn something on top. Right? So it's a big bet. It's a very long-term bet. And this is why, by the way, whenever people talk about pharma companies, they often don't realize that they think in like 20, 30-year increments. Strategic thinking of a big pharma company is like 20 years ahead. It's not next year or not even five years. It's somewhere there. Because the drugs that are now in the pipeline, in the testing pipeline, are the ones that are meant to generate revenue through 2035 or something like that.

And when I thought, well, there is a ton of data laying around hospitals and all the—you call them patient custodian institutions, but mostly hospitals. It is usually not allowed to get the data out physically because in the EU, it's considered to be a breach of GDPR. HIPAA is the US legislative framework. It is more flexible, so it's not that harsh as in the EU, but still, you cannot just throw patient data around.

So we thought, well, can't you extract metadata from these hospitals, from these institutions, anonymized metadata? So why can't you extract a snapshot which just essentially pointer variables to what sort of patients are there in that specific institution? I might make a not very successful example. I don't mean it to sound like intimidating to patients or anything, but it's like a warehouse inventory type of thing where you're not physically in the warehouse, but you know that there are these many boxes of that type somewhere, you know, in Wyoming, somewhere sitting. Right? So it's the same thing. And you don't physically move the boxes out. You just know they're there. And this is what we did.

So this is how we approached things, and we created this first tool, which we call the Curator. The company is called Longenesis, so Longenesis Curator. It was basically a bucket search engine that streamlined the identification of potential trial candidates for pharma. So we were able to say, "Well, you know, potentially, for example, 10 people with diabetes that would match the criteria for enrollment for your trial are in this hospital right there". And that created quite a big of a difference because, you know, not geographically bound to a specific location, cheap, and super fast.

So we went as far as with some of the pharma partners, we sat down on a Zoom call, like, live screen demonstration. We were like, "Well, you know, let's pick a trial that you are doing". And they would pick a trial, and we're like, "Off you go. This is a potential cohort". It's not that we guarantee that these people are still there and that they are 100% enrollable. But according to these very base input variables and input criteria, they might be eligible. And if you consider even a 30% enrollment success rate out of that cohort right there, you're halfway done with your enrollment, which would normally take you, like, two years. And the rarer the disease, the more difficult it is to find the patients. But then the more severe the disease, the higher the cadence of the disease, so like cancer, for example, or very aggressive forms of cancer, the harder it is to find the patients and form the trial cohort. Because, a, the patients are sometimes rare, and, b, they progress from stage to stage very fast. So if you're recruiting for someone in glioblastoma, for example, the brain cancer, which can basically kill a patient in six months, that's challenging to even test something on someone and enroll someone in a trial.

So we did this, turned out pretty successful , and then we moved down the ladder even more. We introduced one of the first electronic consent management solutions for digital for patient consent as well as a bunch of tools for real-world data collection. We call them Longenesis Engage. Essentially, everything that you want to collect in terms of feedback from the patients that big pharma company started to use, starting from clinical trials ending up with market access studies.

And the market access studies are when, let's say, AstraZeneca says, "Well, I want to introduce a new type of ibuprofen in California, and I have absolutely no clue whether people will buy it or not". And it's everything. It's like the shape of the pill, the size of the pill, the color of the pill, the shape of the blister, whatever. So you need to collect a lot of this consumer data, and a big pharma company has zero clue how to do it. Yeah. Like, zero clue. But it's valuable. Right? Because it's make it or break it in terms of sales very often. So real-world data collection tools were also used for that. We had big pharma using it all over, from clinical trials to that kind of penetration type of stuff.

And then we progressed even further, and we ended up partnering with a bunch of governments on building national programs in either preventive care, such as breast cancer prevention in Europe, or national genome programs. So building out national biobanks, one of which we helped to build in the Middle East through one of the Middle Eastern governments. We pretty much helped build the infrastructure for the largest biobank in the world as of now, when it comes to the sample size.

So that was the third company. And that already was a very, I wouldn't say calculated, but a very consistent move into the pharma space , a very consistent work on what this pharma space or the niche in that specific pharma space, and on the specific inefficiency that they can work on to actually speed up things and generate this value at scale. So I think that was a much more calculated effort versus the previous ones.

Jon Chee - 00:37:39: Very cool. I mean, what a demo. You're just, like, put up a Zoom call. You're just, like, tell us the trial, and then you just, like—

Sergey Jakimov - 00:37:46: In a way, the interesting thing is there is a tremendous understanding gap, which is explainable. It's not that it's bad or something or someone is smart or someone is not smart. It's just there is a tremendous understanding gap between the general public and the perception of how the big pharma industry works and the actual way of how the pharma industry works. These are two very different pictures right there. And the general public seems to very often seems to demonize the big pharma industry. Sometimes, of course, the big pharma industry gives the public the hints to demonize it. But eventually, the general public does have very little understanding of how big pharma works and why things happen the way they happen and why drugs cost the way they cost, et cetera, et cetera, et cetera.

So the interesting part about this demo that you mentioned is that one of the things that the general public thinks is that big pharma is this all-knowing, all-anticipating, super-smart type of establishment, right, which is on the edge of pretty much anything, all the cutting-edge stuff. And that's not true.

So if you take cancer drugs, for example, I think 14% of first-in-class cancer drugs are actually internally developed by pharma. Fourteen percent. All else is acquired from small biotechs. So pharma basically feeds the IP of others. It's very slow to move in its own R&D. It doesn't even pretend that it can. So it's good at distribution and sales and fueling the R&D at the very last stages, but it's very bad at innovation.

And in the very same way, you can always sell to big pharma if you offer them ready-made solutions. It is a huge misconception that you can approach a big pharma company with this very fancy AI for drug discovery platform of yours and say, "I'll sell you a subscription to it". Or in our case, "I'll sell you a subscription to our tool. Go poke around. Go search for patients". No one gives them. Like, no one really cares. The only way to sell to big pharma is come over and provide a full problem description or a full problem blurb and then show how you're going to spectacularly make this problem disappear. It's like, "We know that you have this trial that is failing to recruit for two years already. This is the solution. Like, there you go. Sign with us. We'll make it happen".

Jon Chee - 00:40:13: You have to make it a layup.

Sergey Jakimov - 00:40:14: Yeah. Same with assets. Same with AI for drug discovery, for example. Like, "We actually have a molecule that we've designed. This is the data. We have an asset. Let's partner on the asset". And this is the language that big pharma understands. It does not understand the, you know, "Here's the platform. Go play around with it". So it doesn't really buy the capabilities. It buys the output of things and the results of these capabilities. So this is how we approached it, really. It was fun.

Outro - 00:40:43: That's all for this episode of the Biotech Startups podcast featuring Sergey Jakimov. Join us next time for part three of our series, where Sergey shares how he moved from founder to investor, co-launching a longevity fund built on access to top university spinouts and a highly experienced scientific advisory board, and why he takes a pragmatic, disease-by-disease approach to aging. He'll also dig into selling to big pharma, what patient outcomes-first investing means in practice, and how the traction from his first fund set up the second, a pet health-focused fund.

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.

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