Jacob Glanville - Centivax - Part 3

Intro - 00:00:00: Welcome to the Biotech Startups podcast by Excedr. Join us as we speak with first-time founders, experienced scientists, serial entrepreneurs, and biotech investors about the challenges and triumphs of running a biotech startup. Gain actionable insight into navigating the life sciences industry in each episode as we explore the business of science from preseed to IPO, with your host Jon Chee.

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Jon - 00:00:31: And so for DB, it sounds like started before the Ph.D. program. First off, how did you find your co-founders? Obviously sauce on and what were those early days like? Building the team, finding your first Lab space. Obviously doing biotech, got to need a lab. How did that come to be?

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Jake - 00:00:48: So I approached my co-founders with this plan. I wish I'd kept the napkin. It was literally written on a napkin where I was like, look, I think there's this opportunity to build a biotech with no traditional venture. And I was like, there were three stages, and each one of them was a protocol. The first protocol was I was like, I know that there's a bunch of people trying to hire me right now because I got these pipe papers out and I was on the speaking circuit in protein engineering and antibody engineering. These pegs these big conferences about using deep sequencing to analyze phages libraries and improve them and to analyze immune responses and improve them. And I was like, a bunch of people want to hire me to go do this. Because the sequencing instruments were commoditized. There are even new ones coming online like the Illumina. But the analysis really wasn't because it required someone who is an immunologist computational biologist with good algorithmic background and also just like, not sloppy, was willing to get their hands dirty and do the blue-collar work of building a web server. And kind of the boring part, which honestly, a lot of computer scientists, they feel like they're too good for it, where it's like that's actually 90% of your job is like, curating data and making sure everything looks smooth and like.

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Jon - 00:01:51: The plumbing

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‍Jake - 00:01:53: Being really OCD. Yeah, you want a palace is only good if the plumber does his job. Otherwise, that is a pile of shit.

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Jon - 00:01:59: Yeah, that's how I feel.

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Jake - 00:02:00: So I think it was hard to find those people. I think there was probably like eight people in the world that were good at this at one point. And so I was like, I bet we could put something again, like a better version of that laptop. We can put it up on the Amazon clouds. We don't need to buy a supercomputer. We can just basically rent the world's biggest supercomputer as we need it. We can make a web space interface that anyone who's our client could go log in and upload their data and have it all analyzed. And I could build an even more, better and awesome version. So that would be the first vertical, and we'd go license it out. I'm like, I already know there's a bunch of companies that would be interested in becoming licensees. Then with those resources in, I have this idea for how to build an even better library. And so we would be able to build that library and then we'd license out that library. And conveniently, we've just given people a piece of software that lets them figure out how shit their current libraries are. So you've noticed it's a bit shitty. Well, guess what? As luck would have it, I built this super fine, excellent Superhuman library. You'll enjoy this. And Superhuman was basically a rejection of synthetic libraries. I had taken natural libraries and I found that they were redundant for a lot of the same clones that wasted space. And then the average fitness of the molecules wasn't very good because of the random pairing. And not everything that comes out of human is suitable to become a drug. I had spent a couple of years using synthetic methods to optimize the diversity. So the mathematically they looked very diverse. But the problem is that all those antibodies had no longer gone through the selection pressure being displayed on human B cells. And so synthetic libraries had this problem of polyspecificity and some folding problems and stuff if you weren't careful. And I had improved that, I'd made that problem less bad. But there still was a long way to go. And so with Superhuman, I was a way to kind of go back to nature. I'm like, I have this idea of how to build a library. We can solve the redundancy and the fitness problems of natural libraries, but benefit from all the desirable characteristics and make them massively more diverse at the same time. And so we'll license that. And then the third tier was, I guess that's like tier 2.5 was we were going to build up a team to do services because for every company that can license the library, you have 20 companies that just want you to make an antibody for them. And they'll pay a premium for that, but they don't have the infrastructure to do it themselves. And then the final thing was all this was going to pay for us to take antibodies in this universal vaccine thing. I was going to test to try to take it to clinic. And so that was the idea. And then it's more or less basically what we did with one big difference. So, yeah, we started off it was originally just three of us, all with some programming background. So we built that software platform and had it all licensed out. And we were making pretty good money, right? We were charging pretty handy penny, like on annual site licenses. And then I wanted to go do the next part. And one of my partners was like, what the hell? We were able to sit on ass and collect money. Like, that sounds really expensive and risky. Let's just stop and I was like, no, we can do way better if we push further. And it was actually pretty hard to convince them to go do this. And part of how I accomplished it was I met a bunch of faculty at the University of San Francisco. They have this Master's in Biotechnology program, and in the fall, they have grad students who are getting a Master's. They probably have industry experience, and they want to have an advanced research project. And so I said oh. I pitched to them, hey, how would you like to build this dream library with me? And it was a very ambitious project. I thought maybe I'd get someone interested. And instead, I had so many applicants, I had to narrow it down to seven. And this was the fall of 2014. My wife was down in Antarctica for three months, so I was like, by myself? So I worked my ass off. I was going and bringing up a whole bunch of blood samples up from a blood donation clinic on the peninsula. I would bring them up. We would process them to isolate the Lymphocytes. We'd go through this whole process for isolating the right genetic diversity from the right frameworks and then going through this assembly process and over the course of, like, I guess, that whole fall. And then into spring of 2015, we had brought Superhuman 1.0 online, and I had done it without a lab because they were like, look, we don't want to keep IP. We just want you to provide training to our students. And I was there the whole time.

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Jon - 00:05:42: That's cool.

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Jake - 00:05:42: And so I was able to the genetic diversity because I had run the math. I knew how many people I needed, how much blood per person I needed, and how to construct this massive library. And I could fit it into this shoestring of a budget to get past one of my partners being resistant to the idea of taking the risk, right? Because it was cost with no guarantee of return. And then I had argued. I was like, look, man, I've already created a revenue stream and then automated myself out of the loop with that first thing, let me use some of it to go get us higher, right? And so we built that. At a certain point, we did have to get lab space, and that was the scariest part in the company, because we suddenly had to go rent, and we rented from JLABS. You suddenly have much bigger monthly budget coming in for a lab space, and you have still no guarantee of success. And as is normally the case, my Superhuman 1.0, when we started analyzing and stuff, there were a whole bunch of assembly defects. The first time we built it, there was a bunch of because I was building it by cheap from me teaching grad students, and I was having to innovate on some of these protocols and stuff. And so when we got to the end and we did my thing where we used deep sequencing to check the work. There was a bunch of problems with the library, and so we had to go build Superhuman 2, and I had to go notify our early clients. We had four early clients. I notified them, hey, look, I just did the key. I just want to warn you, we just shipped you samples. Like, don't use them yet. It's going to take us a few months to go fix it. Two of them canceled. They're like, fuck it. We're not going to do we're just doing it for you, Jake. Anyway, we cancel our subscription. The other two were like, what are you talking about? These antibodies are awesome. And so they were using our library even though it was like, only like 5% intact. But the diversity was such it was actually big than the other libraries they'd used previously, and that was encouraging but scary. We then completed Superhuman 2.0, and that's when the company really took off, because super 2.0 was just radically improved library to previous efforts. There's a number of companies that are copying my method, but I sold it. Fuck them.

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Jon - 00:07:20: Yeah.

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Jake - 00:07:22: So we had that, and then we started licensing it, and Pfizer picked up a license. Boehringer Ingelheim, Gilead, a bunch of other companies started picking up a license to it, and then we had a revenue stream, and that was a pretty small team. I hired people from USF because they'd been trained with us. They graduated, they knew all of our protocols. We worked together. And so, like, piece by piece, I would hire an additional people. You don't need that many people if your model is to license out the library. You need enough people to run the library and QC it. And we had some hiccups. You don't always get it right when you hire people in, and so you have to figure that out. Like, I learned from my dad. You have to change that structure if you need to with the team, like, pull off the Band Aid and get it right. And so those are never fun days, but you do that. And slowly we grew. I think the relationship with USF was outstanding because we had more interns that kept coming in on these projects. And then the good ones, I think I probably had 60, maybe 70 interns over the course of the years. They're all good, but the ones that were like, a good fit for us and were compatible with the kind of lab work we wanted to do and got along with our team, we would hire them. And so I had this ability to pull in a whole bunch of fresh recruits who were trained on our methods, and that let me expand the ranks as I needed them. Of people that were extraordinarily vetted because they'd just gone through a twelve month interview process, basically through a paid internship, you want to bring in some silverbacks as well. So we started bringing in more senior people. I managed to get one visa for this super brilliant computational biologist friend of mine named JP. So he came over and joined the party sauce and came and joined the party. We had other people that I kind of pulled in on the thing and so it got pretty successful. And then during this whole period in 2014, 15 as well is when I built an animal facility in Guatemala to start testing the universal vaccine thing. And again I was running it on the super cheap because it's that first set of data that primes the pump, which is the hardest. And that's why I used USF as like our labs for the initial development for the antibody discovery programs. And I used Guatemala and land my father had available and relationship with the university. And my brother was a construction worker so he was able to be a foreman to help lay the thing out and build it to spec according to the animal healthcare specialist. And we were able to run these rapid tests because that's the hardest part is when you have no fucking data and it's just an idea but you're like this idea is amazing. The math looks beautiful, it's worth a shot. And how do you squeeze that number low enough that you're not going to drive your partner's nuts with the money that we could have just put in our pockets. Which totally that same partner thought that them all I think was a boondoggle the whole time. This is Jake wasting our money. But he didn't say no. He just grumbled a lot but let it happen because I think we were making enough money elsewhere that it was like worth the risk. And I did, I kept it super cheap. But it was enough kicking and screaming to validate the technology and enough data that I could then go bring it in front of Bill Gates and the Gates Foundation. And then they supported us to do the larger heavy hitting studies we did in the United States afterwards.

Jon - 00:09:57: Badass. I was going to say did all of that take place in JLABS?

Jake - 00:10:01: Most of it did. So we were in JLABS for almost three years. I think JLABS is cool because it's like the Amazon cloud. You rent what you need. JLABS is a similar principle. So we started off with like half a bench in a room because we were a small team. I think we had like three lab members and they were grumbling. They're like, dude, you can't ridden half a room. And I'm like, watch me. And they're like, all right, fine, we're going to take out the benches on the other side.

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Jon - 00:10:24: I'll do it, I'll fit here, no worries.

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Jake - 00:10:27: But they let us do it and pretty soon we were ready to go. Okay, now we want the other side. Great. All right. And then we slowly took over like the next room over and the offices were getting overfilled. And so I think by the time we're at like maybe twelve people, we kind of had overgrown JLABslS.

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Jon - 00:10:40: And so it was like the physical. Too many bodies in the space. It's time to get our space. Okay.

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Jake - 00:10:46: There was like awful pictures in our office of just horrible crowding. Like the labs were constantly occupied and we were driving JLABS nuts because our stuff was like metastasizing into the common freezers and stuff. But fair enough, they're like, oh guys, you could get the fuck out of here.

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Jon - 00:10:58: Yeah, it's time to go.

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Jake - 00:11:00: And that was also when we started expanding. We started doing service projects and at first we did like four, the next year we did eight. But then we were looking at doing like 16. We're like, this is crazy. We had automated a robotic bead manipulation device called the KingFisher Flex. That's actually this one. When I started interacting with you guys, what happened was we were like, fuck, we need to get more of this instruments in. And again it's like, how do you grow a business where the cash is tight but you need it for growth? And that's when we're like, I know we should be doing leasing. And honestly that enabled us to scale because that's a huge problem. That's why you go in an incubator is because you need all this extra equipment to do the thing you do, but the incubator doesn't have all the equipment you need and you're not going to be able to scale. Whereas leasing enabled us to lay us out the entire spec. We needed to be able to go through that big inflection point. So we started, we've got that KingFisher Flex, which we had an automatic feed manipulation robot that let us pan. Like we could pan twelve things in parallel so we could run multiple projects at once all the other devices. And then when we needed to move out, we got a $1 million loan from a group called Broad Oak that enabled us to basically just to carry with you guys and get what we need. We moved out to a space that was like seven and a half thousand square feet. Got a whole bunch of equipment in, mostly good and easy. I remember there was that one piece of equipment, there was a headache for us. In retrospect, I do not get new pieces of technology. I always want a couple of years of other people to work out the kinks. But in general everything worked out quite well. And then I just started loading in more people. And conveniently I had people interested in what we were doing. So more senior people wanted to come in and hire. And then I had this army of interns that I was able to go hire a couple in. We grew pretty quick. I feel like we were hiring maybe one or two a quarter. I think what happened is we moved out and over the next couple of years, we grew up to 36 people. I think at the time of acquisition, I think we ran something like 35 programs that last year, prior to the acquisition, was a huge expansion on the number of programs we were executing on and then industrialized it.

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Jon - 00:12:45: I was going to say like, I mean, one props on the grad program that's like I was thinking about it and coming out of a grad program, just like, I need some experience. Someone please. That catch 22. How do I get experience? Oh, you need experience. And you're just like, okay, so that is awesome that you were able to provide that to grad students. Which then in turn, obviously, it's mutually beneficial. It's kind of back to the negotiations. Little for you, little for me. We get this done together. And JLABS seemed like it was an ability to piece by piece, okay, maybe more than half a bench, full bench. And then, okay, we have twelve people on a bench. Maybe we need our own space and Superhuman one two out of that experience. What were the ones where really kept you up at night? Or just like challenges that were really hard and how did you work through it? Or we talked about finding loudspace as being a hard one. Were there any other challenges you had to work through that were like, really got to think hard about this one?

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Jake - 00:13:41: I mean, the ones that kept me up at night, I think were in the beginning it was is finding way to solve it right? Because I think Venture is actually not that good at disruptive innovation or new. I think that there's actually kind of a missing piece because it's externalized academia. But then the selection pressures in academia, there are exceptions. They're super innovative faculty doing amazing things. But on the whole, I don't think the selection pressures drive towards that. And so I think there's this missing piece of someone who's got a cool idea and how do you kick it off? And so I think figuring that out and I think that gets back to my mom and yeah, my dad's practical business problem solving and my mom's creative theory. That's how I end up my crazy plan of having an animal facility in Guatemala and then work with USF to build these things. Because there were things that I was so passionate about. And I feel like I kept waking me up at night, but I was like, how the hell am I going to get the money necessary to execute? And so I think managing my partners is what it came down to. Once I had the plan, just to be like, look, I think this is worth a risk. And once I had that in place, the next tier up is not fucking up the execution. It's the hardest when you start because you don't have all the years of protocols and everything else mapped out and you're working with new people and that's like definitely when errors will happen, errors of communication. And I think what happened there is I was super present, so I was there every night. I think if my wife hadn't been in Antarctica, I think the company would have failed. At least the superhuman wouldn't have come together because I needed to be there every night staying with them. And I think my energy also caused people, they worked hard, they were working till like 1:00 or 02:00 a.m. Some nights on these long nights. And I was there double checking everything and making sure everything was running properly and calling in favors from postdoc friends of mine who could come up and give some advice on certain types of cell processing and stuff. And same thing in Guatemala. I flew down there so much, I set up the thing myself, the actual samples, and I went there and I was there present. And I think that process of the founders being present and doing the work to make sure that there isn't an error in communication early, I think was how I handled that risk. And it was hard. It was a good period in my life where I could have I have kids now, I can't be flying down to Guatemala over and over again or hanging out at night at USF. I was doing some of that this semester with some of the students and it was hard. And my daughter misses me, she cries when I leave and so I don't want to do it. But I also as a consequence, less stuff happens on those projects for sure. And so I think that solved that step. And then your next step is you have a small team and it's small enough, everybody knows exactly what everybody else is doing and it's easy to talk to. This is other level that happens when you get enough people in or you get more senior people in where people have different ideas on how to get things done. And so you start having this drift problem of protocols and process and verbal miscommunication. And I think that's one that I think can kill a lot of small groups and I think some teams just have never solved well. And I watched my dad handle it with the menus where he just would constantly go in. He'd sample the food, ask people questions when he had new people in and make sure they aren't drift and doing weird stuff. And he would just check because he's like, you'll be amazed how much. Like, new people for sure, don't expect they're going to know anything and just make sure they have a buddy system and they're going to do it. But the second one is even the people who you think have it down, their process might drift a little bit over time and he'll have to go and you're overcooking the shrimp. How many times do I have to tell you? And just check? And so he uses a buddy system during training. And I was really religious about protocols, which is kind of about we have a single fixed protocol, everyone adheres to it, and about having a lot more positive and negative controls than you think you might need. And I think I locked out. I had some team members that were very precise, and they helped because they were at least a nucleus of complaining about that being like, we need more protocols. We need more. And I think that stuff helped us escalate and do well. That part can really break you, especially if you get a senior person in who doesn't agree, then you need to fire that person, or you need to come to an alignment because otherwise you have inconsistent patterns of protocols. And we're not had that. Different groups had different protocols and stuff, and then they get in arguments about the interpretation of data. It was crazy. And so I didn't want that. And I think in order to industrialize, everybody has to do things in the same way and have the same positive negative controls and take the time to even though it's boring, you have to go record all your ALiquots. And freeze them. And then do the testing the next day and store it in the same folder so everybody else can find it, including me. I can check your work. It's like, that kind of boring stuff. Nobody wants to do that. Everybody wants to save the world. Nobody wants to fold the laundry. That's an important step on business growth. And so I think those parts are challenging. The next one is realizing what you really need. I think it was exactly the questions you said. We're like, why don't we just have a Liquid handler? I think there's a tendency for people just, like, live in whatever they're in right now without imagining how it could be different. But you're absolutely right. It's like, look around, being like, what the fuck? Are we doing it this way?

Jon- 00:17:52: Why I'm coming in every morning thing just kind of a small angle for me. It's across the lab was like, way fancier labs. I was like, they have it. Why can't we have it? I'm over here, and they just said it, and they're going to lunch, and then I'm over here, just like, I want to go to lunch. That would be great,

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Jake - 00:18:12: But that’s totally it, man. And I think it's because academics are bizarrely cheap. They'll come into my company and they're like, what are you doing? Making your own media? Don't do that. You're just going to contaminate things. You're going to waste time. It's not that expensive. Your time is more valuable than that media or to the media. Right? And so I think there's that kind of training. I have to do the opposite configuration for people coming from big pharma where they want to go in and just solve every problem with $100,000, where I'm like, yeah, have you thought about it? But there needs to be some of that energy of being like, why are we screwing around? There's some instruments that we could get now that could transform our work through and our productivity and reduce errors. And I think that kind of thinking is important. I think it helped me that I watched Renault grow through that for four years. And so I had a lot of exposure to instruments and variation and what people liked. And I had a reasonably big network of companies that were sort of like my anthropological experiment, where I could see what they were up to and ask them questions. And so I had a perspective of how people did things differently. And if I felt like something could be done faster, I'd go investigate if there's an instrument to do it and what the advantages were. And I had team members who were thinking that way as well. And so they would say, hey, Jake, I think we should do this this way, in which that gets to your company that's also being able to afford it. Because I think that it's a tendency, if you think you have to buy everything, to say, well, we're already budgeted. We can't afford to spend 2 million on CaPEx this year, and so we're just going to do it by hand, or we're just not going to go do that extra test or something. I was like, no, you know how biotechs work, right? It's the fucking ramp. Yeah, you don't have that much right now, but you're about to do a Series A. You're to do all these next steps. You have this trajectory where the time value of money works out in your favor, where you can go radically accelerate right when you need it, right? Which is like proving getting more useful data and more things demonstrated up to the next raise and being able to go faster. The business proposition makes a lot of sense, and it was for us at DBIO, like, when we needed to scale, I'm presuming a big customer of yours. We were, like, starting to get a bunch of equipment because we were going through this massive ramp, and CRO was, like, cheering us on. They're like, yeah, get more stuff, make it go faster.

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Jon - 00:20:03: Go faster, faster, faster.

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Jake - 00:20:06: And then basically, if we knew if an acquisition was going to happen, they were just going to go buy all the equipment, and that was the path. And they were, like, helping. They actually even helped us subsidize some of that expansion. So I think that really helped. I think once you have stable protocols, reliable protocols, I think you have good instrumentation. The next thing you need is, like, Clear Hierarchy and Leadership. And the final thing, which is the one I don't think I'll ever stop thinking about. Which is the Balance of the Hierarchical versus the Organic Model. And it comes down to what I was saying earlier, right? The Hierarchical model will execute extremely well, but you're not going to innovate and the whole ship will move very steadily in the wrong direction. Sometimes the Organic model, you have lots of innovation, but the ship can just like be stuck there in the waves while people are rowing in different directions. And so my solution to this, because you need both in startup culture, is what I call the Respiration Model, which is when we're all sitting down and we're talking, everybody's opinion is to be listened to and encouraged. I want to hear the debate, I want to hear all the ideas. And if someone proves me wrong, it's your job as leadership to be like, that's a good point. It makes them to know that they score positive points by pointing out an error. I'm not going to always be right. I want someone to tell me when I'm wrong. But the thing is that's the organic phase, once a decision has been made, then you are firmly in the execution mode and it is absolutely not acceptable to change the plan after the meeting. Everything in the meeting is good, but now you are executing. And so instilling that set of expectations on a team is really critical towards being able to adapt as a Biotech has to, but also be able to execute and not just screw around, which certainly I've seen startups do where they don't really accomplish that much. And I worry they sometimes try to hide the fact by using a lot of hype to get around the fact that they're dysfunctional in terms of execution. So I think that's really important. That's something that it takes work. You have to reiterate the importance of it. You have to be like weird combination of firm yet humble because you need to be able to hear people. And if you realize someone's right, you have to walk back and tell them if you told them they were wrong publicly, go tell them they were right publicly and make it so that the community recognizes that it's ideas that are being discussed and not egos and create that correct cultural environment. And there needs to be some tension because some people get work done. You can't just like I'll be hanging out playing guitars and having some wine. But you need to make people feel comfortable that if they speak up, they're not going to be punished for it. In fact, they'll be rewarded for it. And that ideas are what wins. And at the same time, once the plan is set, then there is not flexibility to go fuck around. You have to go execute per the plan outside of the room, or report back on why things need to change. If you can get that right, then you're really jamming and you get a lot of work done and a lot of productivity comes out. So think that's the last piece that you kind of have to line up to execute.

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Jon - 00:22:33: I can just feel myself taking mental notes. It's like, all right, it's the respiratory model and that's like a great visual, like thinking about it. And I think at Excedr we're trying to do both kind of thread the needle on that and obviously we don't want to go too far in one way. And sometimes they'll always kind of balance like a pendulum a little bit, but just like always trying to get back to that balance. I think people almost like assume or at least seek perfection, but it's never going to be perfect. It's always this thing that is bouncing back and forth. But as long as you are trying to get back to that balance, I think it's like super critical. So you've grown the business, you're now your own space. When did you decide it's time to move on to the next? When was that for you?

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Jake - 00:23:11: Well, CRO reached out, right? And we had a couple of other groups that got interested that we were kind of unusual. We were a profitable and growing business without investment and we were starting to become one of the most credible antibody discovery groups. There was a good group out there called Adam-ahab who had done some good work on the east display system and they really honestly didn't have that much good, credible competition for a while. So I think we were the first ones to come in that could give them a run for their money in terms of the number of programs we could go after. Look, they had a great system. They had this yeast display system that was cool. But the superhuman library was vastly more diverse and it let us go after more challenging epitopes. And then also we were very good at engineering the antibodies for enhanced stability. So we were kind of a growing force in the field. We were doing lots of discovery contracts and our success rate against challenging targets was great. We could go after GPCRs and ion channels and single amino acid changes on peptide mac complexes, like all the tough stuff we could nail. It like the superhuman library was basically just a carpet bombing of every possible epitope on the surface of an antigen. It was like total war. Powell Doctrine, like victory by overwhelming force was the whole principle. And you'd have to affinity mature, so you have a range of affinities. If you wanted really high affinity antibody, you will get a huge number of antibodies, but they wouldn't necessarily all be high affinity. And what you're doing with diversity is increasing the amplitude of the poison distribution that governs affinity ranges. So you still have not that many ultra high affinity antibodies, like a couple and then a good number of reasonably high affinity antibodies. But you'd get any epitope you wanted, you'd have loads of hits and for a lot of new applications, affinity wasn't that important. We get affinity mature things if we needed to, but like, for car t applications and directing payloads to certain tissues. So those sorts of applications, it wasn't necessary. In particular, when car t popped up, we got very popular. Lots of companies wanted to use us because we had as robots to automate rapid discovery and hit single amino acid changes on cancer discriminating surfaces and things like that. So that was good. But I also knew that these transgenic mice, I thought they were a good system. It was like a really nice animal model. You go in there, you immunize some mice, and you chill. Like, managing QC is probably your hardest part of your job, and they produce human antibodies that were pretty good, and they have built in affinity maturation. So if you want some really special epitope, we were better. But I think if you just want a high affinity antibody against a target, those were very competitive systems. And so I saw that landscape. I still felt that we could crush any other technology when it came to challenging epitopes or sophisticated engineering. But I also felt that it was getting more competitive. And there were other companies starting to copy my exact, like, literally copy what we were doing. And CRO was this huge company with global reach that had all the other assays. So they had the in vivo stuff, they had in vitro, and we didn't do any of that. We basically said, look, we started your antigen, we'll go ahead and run, we'll produce the antibodies, but it's on you to do the functional assays in in vivo and all that stuff, because otherwise we'd have to create like, new assays for every client, and it just didn't scale in the same way. So being able to plug into a partner, they could actually do the entire thing from start to finish. So I felt that that made sense. I felt that Superhuman 2 was radically better than Superhuman 1. I could make a superhuman 3 that would still be better. But I sort of already hit the hill of the really big improvements, and I'd already built like, a VHH library, single light chain library, all the cool types of libraries. The panel was complete, and the other thing that was happening was that I was getting this amazing data back from the universal vaccine technology, the pigs, my little piggies in Guatemala. The data looked amazing, and I was like, I think this has to become my life. And so I felt that the time was right. I felt we were at a good point to do an acquisition. It also was like the risk profile. We had one partner who just told me, I don't really know if I have the risk stress stomach for biotech. I think being able to cash out would be really attractive to me. And so I think it was a natural thing to go. Okay, let's go ahead and get this service business acquired. I will spin out the universal vaccine technology to a new company and a couple of other internal engineering things we've been working out. I'd spin out to a new company, they would acquire Distributed Bio, and then I would create a new company called Centivax. And so the timing worked out really well. It was around the time when I was being filmed for the Netflix documentary series along that time I found that I had received the Gates Foundation Award. This in the Pandemic Threat Grand Challenge Award, which enabled me to run my studies in the United States at facilities where they could Live Challenge spray the animals in the face with virus for pigs and ferrets to show we could protect against viruses like twelve years in the future. And so suddenly, my super humble study down in Guatemala was now being I met Bill Gates twice over this and we talked about the project and he was excited and we were able to run these amazing studies. And so it was time for that thing to come online. And then the other, of course, crazy thing that happens is the pandemic hit and suddenly work. I was working on that nobody gave a shit about. It seemed like a fantasy. Suddenly was like front and center, and I was like a pundit on national media to give people advice on dealing with a pandemic, where I was kind of like, really? I'm the best guy you can find for this fuck sake, we're screwed. But I did my best, and it was just good timing for the technology because the world got that kick in the ass to be like, yeah, we really need broad-spectrum vaccines. And so it was just a good launch for what we were doing. I think mostly it was a positive. I still think that people are kind of crazy when it comes to estimating risks around pandemics, but I think that in general, it has given rise to an acceleration of a whole bunch of technologies that help us some helpful funding sources. Although less than I'd like. Hear me, government, you should put your money into universal vaccines. Wouldn't it be nice if we had them?

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Jon - 00:28:14: Yeah. Joe Biden if you're listening, more money, please. Helicopter in.

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Jake - 00:28:19: Make it rain, Joe. They're working on some things. They have this thing called ARPA-H, which is quite cool, and some other efforts. So I think good positive progress has been made. Sinovac is certainly appreciative of the NIH and the DOD, Naval Medical Research Center, Rare Gates Foundation, NIMBLE and the other government and foundation support we've. But I naively assumed that someone would say, oh, how about we go take like, 0.1% of the money we spend on the military and let's go try to fix this problem which affects the military, include global health security and national military security. And I'm surprised that more money was not spent on this problem. And then I did not get more. In case you're wondering. Government, yeah, you can throw me some and I will bring you some universal vaccine faster. I'm going to do it anyway, but it will be faster if you give me the money now. So just calculate how much it's going to cost you every day. You don't give it to me. Give me a 10th of that and we're in good shape.

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Jon - 00:29:09: I'm like reflecting back on kind of the arc of it all and two things that stood out to me during this period of the transition and spinning out centrebacks. The first thing that really stuck out to me was like a co-founder or someone who was talking about, hey, the PH in my stomach, it's turning. I don't think I can do this much longer and perhaps we entertain something. Let me take chips off the table. And I think we were talking about this before, but I think for founders who are thinking about entrepreneurship, that's like a real feeling that you got to be honest with yourself. If you feel your stomach turning and you're like, this risk profile is not for me, probably listen to your gut about that. And I think your gut is telling you something for a reason and not listen to it usually doesn't really work out well. And something else that it stood out to me too was it sounded like your time at DB, you're doing a lot of things and I think what you said that really stood out was, I need to spend my life on universal vaccine, and, you know, Excedr we do one type of equipment with one type of people. That's what we do. And it's kind of that focus. I think there's a lot of exciting things in the world, for sure, but there's only so many waking hours in the day and I empathize like, I'm going to dedicate to this. And it really resonates with me because all the time you get people like, hey, will you do an airplane? I was like, no, I won't. We're not going to lease an airplane. We're doing Liquid handlers. Um, we'll do a flow cytometer, we'll do that. But let me put you in touch with someone who will do an airplane. So that focus is just critical.

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Jake - 00:30:32: I completely agree. I think you want to crush it. I think that was like a learning curve for me. When I spun out Cinevax, I had multiple different things we were working on and I was kind of derisking them. And they're not that expensive to derisk early, but A, it annoys the hell out of investors because they want to know what the thing they're investing in and the focus area. And for good reason. I think there's value in portfolio, but if you spread your attention too thin, you're not going to get anything done. Well, right and there was a natural point of inflection where it was very clearly like of the things that we'd inherited, the universal vaccine was the best IP, the best data, the most derisked, and it had the greatest global impact. And so it was clearly the winner. And that was why I was derisking multiple things, trying to figure out what's that thing I work on next? And that one was clearly it. It greatly simplified our pitches. I didn't even bother telling people about the other stuff. I had it like in the freezer and then frankly, that's how we're doing the business. Like all that other stuff is just we're licensing it out to somebody else or parking it because it enables a certain fluidity of execution when everybody knows this is the thing we're working on and they can go, okay, what more can I do on that thing next? And more time we can spend to make sure that we're measuring twice and cutting once. You can really crush at that one thing, you're doing extremely well, and I think that decision make sense once you have something that works. And so I think we had reached that and we're like, okay, let's go all in. It's risky when the hockey tentacles are flipping around trying to figure out which one is going to be most successful. But once you've got it lined up like you guys do, you don't really need the optionality, you need the execution. And more time spent on that thing will result in more success. And so you pick the thing that's going to be the biggest impact.

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Outro - 00:31:58: The Biotech Startups Podcast is brought to you by Excedr. Don't want to miss an episode? Make sure to search for Biotech Startup's podcasts in Apple Podcasts, Spotify, and Google Podcasts, or wherever you get your podcasts, and click subscribe. To learn more about our leasing program, visit our website www.excedr.com. We provide research labs with equipment leases on founder-friendly terms to support a path to exceptional outcomes. On behalf of the team here at Excedr, thanks for listening.

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