Growth Without Venture Capital: The Bootstrapped Bioscience Playbook | Ivan Liachko (Part 4/4)

Intro - 00:00:06: Welcome to The Biotech Startups Podcast by Excedr. Join us as we speak with first-time founders, serial entrepreneurs, and experienced investors about the challenges and triumphs of running a biotech startup, from pre-seed to IPO, with your host, Jon Chee. In our last episode, Ivan Liachko shared the scientific insight that led to founding Phase Genomics, how he and his co-founder built the company from the ground up, and how a simple idea, tracking which DNA sequences touch, opened the door to powerful new applications in genome assembly and microbiome research. If you missed it, check out part three. In part four, Ivan reflects on the evolution of Phase, from bootstrapping in a lab closet to enabling major discoveries in cancer, infectious disease and agriculture. He talks about building products without a roadmap, the role of constraint in sparking creativity, and why clever science, not scale alone, is key to tackling biology's biggest questions.  

Ivan - 00:01:19: So there's three applications, right? So one is genome assembly, and that's how we bootstrapped Phase, basically by doing genome assemblies for people. Now it's old hat. We've published like 300 papers on it. Like it's just everybody does it all the time. Now there's always competitors doing similar things. Then there's this microbiome thing where we built the whole microbiome discovery platform specifically for using this technology to map like A, to separate all the genomes out, to get genomes for new things, and also to figure out where all the antibiotic resistance genes are going and where all the phages are going. The third thing, and it's super important, and I think possibly the most commercially valuable part of this, is that because you know which part of the genome is how far and how close everything is in the genome. If something rearranges, you can see it. You know, for example, if you have cancer, if you have leukemia, right, one of the key features of cancers is that your genome gets screwed up. Like cancer is basically a genetic disease, right? Because, I mean, obviously there's other things. There's proteins. But at the heart of it, there's almost always some kind of genomic rearrangement or mutation or something that leads to the progression and development of this cancer. And so if you've got leukemia, they would do a bunch of tests on you. And what they would do is they will take your cells, they would put them on the microscope slide, and they would look at your chromosomes. Chromosomes form these kind of like little butterfly shapes. It's called a karyotype, where you look at the chromosomes, how they're laid out. And some of them would be like, that one is longer than it's supposed to be. That one's shorter than it's supposed to be. That one looks like two of them got glued together, right? And this was done 100 years ago. And it's basically every diagnostic lab does this. Like every cancer center does this. This is super entrenched. And there's a couple of other methods that do similar things. What you're looking for is the formal name for it is structural genomic variation or structural variation or chromosomal abnormality, right? Where genomes get basically rearranged. Now, let's say you have two cells from the human, same person. But one of them, one of the chromosomes, like one arm got flipped. Let's say you sequenced both cells. Would you see it? Because the sequence is the same, right? So if you have mutations where it's letter changes, that gets detected by sequencing. But structural rearrangements are difficult to detect by sequencing because the sequence doesn't change. And so you're looking for signal like, oh, man, maybe I can find a weird sequence read that catches like a piece of gene A and a piece of gene B and they got fused together, right? But it's very, very hard. Structural rearrangements are hard to detect. Sometimes in many cases, straight up impossible to detect by regular sequencing. And so people still do this microscopy stuff, right? Where you're looking, but you're looking at DNA with your eyes. Like, what are you going to see, right? Like it's like, you know, you can only see gigantic things, right? But suddenly, I have a way to sequence your genome in such a way that I will know how far away every part of that genome will be from each other. So if something got flipped, I will see it immediately. And so what we did was we basically leveraged this technology to create a way of essentially doing what karyotyping does these days, but in a much higher throughput, much higher resolution way. And we're doing a lot of clinical work with, you know, people here in Seattle, like at the Hutch, at the University of Washington, other places. We're working with, you know, Stanford, Harvard, like we're working with tons of universities, commercial partners. But the idea is to say, you know, you have this technology. For 100 years, we've been using these very manual, very laborious tools to detect these super important cancer markers, gene fusions, et cetera. Suddenly, there's a next generation way of doing it with sequencing. And it's not because we have a new sequencing machine. It's because we're capturing a new kind of information. We're catching these touchings, and the touching tells us what's far and what's close. And we use that to reconstruct your genome. And it's like, that's one of the things that I really love about it is that it's not a brute force approach. It's a cleverness-based approach. It's a new kind of information that lets us do new things. And so, you know, we started out Phase. We started doing it as a service. We bootstrapped, right? Eventually, we put them into products. We sell kits now. In fact, I have one of our kits right here. So, you know, we have kits. We have these boxes that we sell. We also built the software for analyzing this data. So that's basically what it is. And so that's the underpinning technology under Phase. We're now doing a lot of super interesting work that will be announced soon on, like, what do you do with the information, especially on the microbiome side? We're capturing all this microbial novelty. All the, like, these microbes are all, like, crazy alchemists that do new things. Bacteriophages are basically little, like, homing missiles to kill bacteria. And we have the world's largest repository of phage-bacteria interactions because we've been collecting them for so long. We have this big project with the Gates Foundation where we're just sequencing wastewater from around the world. We have all these, like, animal and human. We're doing fecal transplant work where what happens when you do the fecal transplant from one patient to another? What happens to the microbial community? There's so much, like, I don't have time to talk about all of it, obviously, but I'd be happy to. But within these phages, there are proteins, right? So phages kill target bacteria. There's a lot of people using bacteriophages in the therapy space, using them as basically targeted precision antibiotics. There's another thing you can do with it. Phages have these proteins called endolysins or lysins. This is the protein that the phage uses to kill the host when it tries to break out. If you just take that protein, that protein will wipe out a field of bacteria in seconds. Like, it's crazy how fast they are. And there's never been a case of resistance noted against one of these lysins. And so we now are doing all these cool projects with some foundations and some others. We announced one we announced. We're actually doing work with the Gates Foundation and the Grantham Foundation on enteric methane. So basically using proteins like endolysin proteins to kill bacteria and archaea that live inside of cows and make methane. If you knock enteric methane down by, like, 50%, it's the same as, like, you know, there's depending on who counts what, but, like, it's, like, taking every car off the road in terms of...  

Jon - 00:07:38: Oh, my God.  

Ivan - 00:07:39: Like, it's crazy. Like, I'm learning. I don't know anything about these, but as I'm learning. But using these endolysin proteins to reduce methane emissions in cows. How do we get there? We got there by figuring out the three-dimensional structure, which, you know, doing this goat assemble. Like, it's crazy, right? Like, it's like... And it's all because we figured out this new information type. And suddenly you can figure out cancer genomes. You can assemble genomes for plants and animals. You can do this microbiome discovery. You can find new antibiotics against random resistant pathogens, right? Like, and it's all just because of this new information quirk. So that's kind of like the story in a nutshell, you know? And I think as we move into the future, more and more focus is going to be on information systems, right? So we see it now. We see it with AI. Information is like everything these days. And because Phase has access to this really unique information type. That we're doing so many different things in oncology and infectious disease and agriculture. We're basically positioning ourselves as this, you know, it's already positioned essentially as this like nexus of discovery of generating all of these useful applications that people couldn't solve these problems before. So that's what we're really excited about is moving into the next era of biology, biotech, life sciences, really armed with a unique data type that has so many really cool superpowers.  

Jon - 00:09:09: That's so rad. That's like incredibly rad because like, I think exactly what you said, it's not a brute force technology. It's a clever technology. And that's where you see these like incredible, just like. Of course, back in the day, it's just like, the only tool that you have is a hammer, everything looks like a nail. Maybe we just hammer more.  

Ivan - 00:09:29: And we're guilty of that. We're like, we have a hammer, there's a million nails, and we are guilty of doing the hammer. 

Jon - 00:09:36: As is everyone. As is everyone, if you're kind of steeped in a specific technology, it kind of shapes your worldview. But, you know, that's kind of what you're talking about. There's like these revolutionary moments where it's like, ah, we now have this screwdriver and we can actually like unlock things that, you know, were just not possible. Even if you tried to brute force it, it is not possible. I can see how even within my organization at Excedr, you kind of get set in your ways, but sometimes it takes that paradigm shift that just completely unlocks it. And exactly what you said, like, you know, we're living it right now. AI is like front and center. And, you know, I guess just like questions when you were just like starting Phase, you met your co-founder. I think you said he was, he worked at Microsoft. And you also, there's, I'm going to imagine there's like a tech transfer process to this too. How did you meet your co-founder? How was that process of getting this technology out of UW? You know, and what were those like early days of like, you mentioned that first product was how you bootstrap this thing. Talk a little bit about that.  

Ivan - 00:10:39: Totally. So we met because I ran a D&D campaign in my house for years.  

Jon - 00:10:44: Yeah.  

Ivan - 00:10:45: And he was my DM.  

Jon - 00:10:47: Yeah. Sweet. Hell yeah.  

Ivan - 00:10:49: He was married to one of the grad students in our department. So we had this D&D thing that it was all science. It was like watching a bunch of scientists play D&D is incredible. There's a lot of like, you must open this treasure chest by solving Fibonacci sequence.  

Jon - 00:11:03: Yeah, yeah.  

Ivan - 00:11:04: It was like a lot of like, which bird will I transform into? What are the different speeds of birds? Like, it was like, there's a lot of that. And we did that for years. And then, you know, because we're all talking about this stuff all the time. And as you know, I was like, hey, you know, we're going to spin out this company. He was like, I'd like to join. And that's how we started. So we had a good marriage of like computational. He was much more, you know, he was obviously a software developer. And I was more of like the lab guy. But we also had different, like he was like super organized. And I'm like the chaos child.  

Jon - 00:11:39: Yeah. 

Ivan - 00:11:39: So it was just like a really good. I think one of the things that made us really strong is and how we were able to lift this up is because we had this complementarity. And it was it's very important for teams when they're starting out to get complementarity like that, because you need people who are different than you, who complement things you're not necessarily best at.  

Jon - 00:11:58: Absolutely. And so you had your first product, which you're, you know, basically using as like the what the beach had into the market.  

Ivan - 00:12:06: What we did was so it wasn't even a product at the time. So we started work because, again, remember, I didn't know anything about commercialization. 

Jon - 00:12:13: Yeah.  

Ivan - 00:12:14: I had literally never worked at a company before.  

Jon - 00:12:18: Yeah. Yeah. Yeah.  

Ivan - 00:12:19: And so we had a lot of help from the tech transfer folks at UW. There was a lot of cold calling of random advisory types that I was like, you don't know me, but I need advice.  

Jon - 00:12:31: Yeah, yeah, yeah, yeah, yeah, yeah.  

Ivan - 00:12:32: Eventually, we got licensed and all that stuff. We had early customers. So because the way this happened was we were doing all these genome assemblies with this new technology, and people were finding out about it from conferences, from publications, et cetera. And there were labs who just literally showed up at our door and were like, can you do this for us? And there were at least some big Ag companies. That had, you know, like scientists from Ag companies would come and be like, hey, we want to do this project, but it's not proprietary, it's proprietary stuff. We can't publish this. So you need to have a company. So that kind of gave us another one of those little bird, like nudge out the nest kind of things. Where I was like, okay, people are literally offering to pay us money for this. And that's what we did. And we started, we went to the, there's an incubator on campus at UW, University of Washington. We went in there, they were walking us around. They were like, you can rent this bench, you can rent this bench. There was a closet that had a couple of desks in it because they were storing, I don't know what they were storing in there. But like, and I was like, that closet looks like big enough for two or three people. And it's got a desk in there. How much is it to rent the closet? And they were like, dude, that's just a closet. That closet has a door that none of these other benches have. And I'm going to be on the phone with customers all the time. And so we rented the closet. We were literally, you know, two of us in a closet. I filled out my lab. We put in like five grand a piece or something like that. It was an eBay-based laboratory setup.  

Jon - 00:13:58: Yeah, yeah, yeah.  

Ivan - 00:14:00: It was everything. We dragged a desk. We needed a desk that was like, you know, for lab stuff, you want like either a blacktop or like some metal top. You can't use like a regular office desk. It's wood. And so we like dragged a metal desk from UW Surplus. And because it was regular desks are lower than lab benches, I bought bricks at The Home Depot. So we literally had a lab desk on bricks. And I think we sold our first million out of that closet.  

Jon - 00:14:29: That's freaking amazing  

Ivan - 00:14:31: Yeah, over the years. And it was, you know, kind of the usual startup thing where it was like, are we a real company yet? And then we like got to get the cards and we're like, oh, I think we're real. Now we're real.  

Jon - 00:14:41: Yeah.  

Ivan - 00:14:41: But it wasn't, I remember our first ever conference backdrop, right? Because we're also like, we hit a lot of conferences. We do a lot of like vendor stuff. And so we're selling, we're on the road. And so the first time we got this like backdrop with our logo and like Phase Genomics and it does all this stuff. It was like one of those, like where you, we see a vendor and they're like, hello, sir, would you like to get some free reading material?  

Jon - 00:15:04: Yeah.  

Ivan - 00:15:05: That was us. Right. So we built, so we, we got like the logo, we had to do the boxes at some point we had kits. And every one of these moments where we were like, now we're a real company, like that banner went up. We're like, oh my God, we're so real. You know, we had already sold like hundreds of thousands of dollars of product. We're like, it was that banner that made us a real company.  

Jon - 00:15:21: Yeah. Yeah. Yeah.  

Ivan - 00:15:22: The website goes up. Ooh. Like we started with a website that was literally just, it was the website equivalent of one of those restaurants that don't have a sign in the front and there.  

Jon - 00:15:32: Yeah.  

Ivan - 00:15:32: Like a secret door in the back. It was like that. It was like Phase Genomics. It was like, you need to know what we do and then email us. Like that was our website. And then, you know, like super organic, super shoestringy growth, a little bit of like friends and family money helped us out. We started getting a lot of SBIR grants over time. I mean, you know, I wrote a couple of grants that got funded. And so so little by little, the ball started rolling. But it was that it was very scrappy and super like because we never really had a lot like we're not really we don't have much in the investor. Like we have a couple of investors that have put in some money, but but not much. And so everything has been kind of organic and growing over time.  

Jon - 00:16:13: When did you feel like you're ready to roll out your next set of products? Like, I feel like that's like, you know, for a lot of folks out there, it's kind of like rolling out your next product is like, it's a big decision.  

Ivan - 00:16:24: It is a big decision. And we did it in a terrible, terrible way where we just tried stuff on people. We would assemble these. We're like, somebody wants this and they're asking me, can I get this in a kit? And I go, okay, I'm just going to throw these things in a tube, put some tubes together, put stickers on them, put them in a little box, send them off. It was like that. It was like super janky. We never, like a lot of companies, you know, there's like a process, there's product managers, they figure out all the features, everything is set out. We never had the resources to do that. And so we would basically do it, I mean, inadvertently, the lean model, which is like MVP tested on customers, MVP tested on customers, iterate, iterate, iterate. We did that not out of like commercial wisdom, but out of necessity, right? You know, eventually we got a little better at it. Now we're a little bit more intelligent, I think, about how we do it. But that's how we kind of got in there.  

Jon - 00:17:19: I love that. It is the constraint that is like really, it really forces your hand. But like, ultimately, it's like, that's the most efficient way to do it. And so you're, you know, you now have a product suite, and you also do, you know, you work on collaborations with service and offer services, like, who are the folks that, you know, you work with the most? What is the archetypical, like, customer field? And also, like, what is the kind of partner that, you know, finds the most value from your guys product and services?  

Ivan - 00:17:49: So most of our customers are scientists of some flavor. In fact, when I say most, I mean like almost all.  

Jon - 00:17:55: Yeah, yeah.  

Ivan - 00:17:56: Some of them are obviously clinician scientists. Some of them are in industry. Some of them are academics. Academics, probably the most numerically. And, you know, it's just sort of the field, which field they're in. If they're trying to assemble a genome for a plant or a fungus or something, they could be a basic researcher. If they work for an ag company, they might be doing plant genome assemblies. If they are working for a pharma, maybe they need some human cell line assemblies or some kind of model organism that they're working on. Then there is the clinical side of things, the cancer side, which is basically clinicians with patient samples. Again, we're a research use only company. These are not diagnostics. But they are things that are diagnostics in the future. But you're analyzing cancer genomes. The idea is there are sort of three ways you can think of what to do with that technology. One is leaning towards improved diagnostics in the future, right? Another one is you're discovering new, like, gene fusions, new genomic rearrangements that can be linked to therapeutic outcomes or different treatments. And then there is, like, patient stratification. The idea is, and we're showing a lot of data now that, like, you know, we're going to AACR next week, that basically shows, like, if you're armed with better data, your patient segmentation becomes way better, right? So you can predict how people are going to respond, you know, their risk sort of profiles and things like that. And again, it's all about getting better information, right? Like, the old school methods are great. They show how important it is to analyze these genomes, to look at cancer genomes. But because they're so low res and manual and laborious, there's, you know, if you just do it better, you find more stuff. You find more stuff, you have a better patient segmentation strategy. So it's sort of like there's diagnostic angles to it. There's patient stratification angles to it. And there's also just straight up discovery of new rearrangements and new gene fusions angle, which is more like sort of pharma-centric. And in the microbiome space, it's pretty much everybody's some flavor researcher. Some of them are doing like fecal transplant, more clinical work. But because we're now spinning off little companies focused on utilizing some of these phage proteins to do different antimicrobial things, that's a different thing. We've sort of become sort of a research institute with our own assets, and we're spinning off a couple of entities. And so we still do services and products, but we're also starting to leverage the data we generate for things that don't have anything to do with our technology per se. That's kind of the Hail Mary that we launched when we first started Phase, is that this idea that the technology gets sales. And we help scientists do great science and we help discover all this stuff. And as scientists ourselves, that's a huge point of pride to us because my scientific output right now is way higher than it would have been had I been a professor. But on top of it, because we think so much about information, we now have this other information that is valuable in and of itself for different potentially therapeutic applications. Right. So we're thinking a lot now about, okay, we have this have this massive phage database. What can we do with it? I probably have the world's largest collection of novel CRISPRs. Right. Like we have all this other stuff. That really trying to exploit them for different applications, but we're trying to approach it. That has to be approached in a more intelligent way rather than our usual, let's just try everything. You have to say, okay, what is the final outcome? What is the need? Who's the customer? What is the market there? If it's going to be a therapeutic or an antibiotic or something, you can't just try stuff. You have to try on strategy and all this. So that's kind of where we are now. And so driving sales with our existing products to kind of keep the machine going, but also we're starting to see a lot of these really cool spin outs coming. None of which we've announced yet, but we will at some point.  

Jon - 00:21:45: That's so rad. That's so rad because I think I already mentioned just how things can be very prescriptive in company building, generally in the zeitgeist. But I just love the way that you guys are going about it because you have this core growth engine. It's your core technology that is driving the growth and allowing you to explore these avenues. And again, you never know these opportunities. You're like, I'm sitting on a boatload of data and there's a ton of opportunity that can come of this. And this is a by-product of the core engine.  

Ivan - 00:22:16: Yeah. And there's a lot of things that we just aren't leveraging because we just can't do everything. Right. And so that's, you know, a little bit of a wink, wink to listeners, but like, you know, people come to us and they're like, Hey, I want to, I'm trying to do this thing. And we're like, okay, well let's form a spin out, like find an investor, find the CEO, let's spin this out, have a little company. Because there are so many different assets that are in that data that we're not even touching yet. We're always looking for other ways to leverage it. Then again, one of the things that I really love about it is that it is, again, it's really about clever things, simple things, the power of information, the power of new kind of information that just opens doors. Like I'm in love with this concept.  

Jon - 00:23:02: Yeah, I mean, we find the same, you know, on our side, these like kind of data insights. So because we're a leasing company and we work with tons of, you know, emerging biotech. And having done this, it's almost like year 15 now, we just have an enormous amount of like, we've done so much analysis on emerging biotech where we can kind of see trend analysis or just like where we can kind of like see around curves a little bit of like what's kind of coming up, what's getting funded, kind of stuff like that. And also just understanding the guts of like how like emerging biotech companies are like spending their money operating and like that. And we have yet to, you know, really truly utilize it, but you kind of like just by running the business and like you just kind of like, and doing it for long enough, it just kind of like builds that like, kind of like the snowball. It's like a tiny little, kind of little one. And then as it keeps going and the longer you do it, it just like starts to become this like massive thing. The saying with no compounding, it's like, it looks flat until it isn't. Like you just get kind of hit that critical mass and it just goes crazy. And so we're talking a little bit about like kind of the strategic vision of Phase and obviously like you talked about how no money is free and those checks always, they come with some sort of strings attached in some shape or form. Can you talk a little bit about your decision to, it sounds like I'm making an assumption here, that you decided to not take the money. And is there, do you have a philosophy around that? Is it because of the strategic vision you have for the company? Or kind of how are you thinking about that, like your fundraising philosophy and how you capitalize the company? 

Ivan - 00:24:40: I think about this quite a bit. I mean, it could be a philosophy. It could be that I'm just really bad at finding money. We've been really good at getting non-dilutive funding. So we have gotten quite a lot of money from various funding sources that are like SBIRs, foundations, Gates Foundation, others. I think the real thing is I kind of foresaw the future a little bit. And so people are raising big rounds. There are investor expectations. And I say, like, these kids are great, but I can't. I'm not going to sell a billion dollars of these kids. I'm sorry, VC. I can't. Like, this is never going to happen. And I'm like, okay, I could convince somebody maybe that I will. But it's going to bite me later because I won't. So what happens is you promise this hockey stick. Nothing hockey sticks like that in our space. Once something is going, you can be like, okay, I can put a bunch of salespeople behind it. I can do whatever. I can expand. It'll go a little bit faster, but it's not going to get the typical VCs expecting something totally different. And so we kind of understood, I would be really getting into some borderline unethical, like if I started pitching this for real rounds, it would come and maybe not even unethical. I would just like, they would gamble on us and then we would disappoint them. And then they would take the company away, which is totally reasonable for them to do this if this had happened, right? And so I was always very cautious and we had a few early investors that were like, look, this is going to be a lot, like we're throwing a Hail Mary. One day, the assets that we generate are going to be humongous, but we don't know what they are yet.  

Jon - 00:26:18: Yeah, yeah, yeah, yeah, yeah, yeah.  

Ivan - 00:26:19: I know that I'll sell some of these, but I'm not going to return your fund with these kids' sales. And so let's focus on the big idea. The big idea is what you're saying. It's nothing, nothing, nothing until it's something. And I think that's where we are now, is that now it's becoming something. But it took 10 years to get here. And so in part, I was just like, I think we're just better at getting money from scientists than from investors. I can excite people about the scientific implications. We can write really good grants. My people are all super, like I don't have any salespeople. Everyone is a scientist. Not that there's anything wrong with having salespeople, but I'm just saying like we sell through science only, right? And so I'll go to a conference. I'll give a talk. People will come to me. They want to buy stuff, right? You know, we write these grants. We get grants funded, right? Like a $2 million SBIR, like that's not nothing, right?  

Jon - 00:27:10: It's not nothing.  

Ivan - 00:27:11: And so, you know, we've gotten like I think probably $20 million or something over the years and non-deluded.  

Jon - 00:27:16: Freaking awesome. 

Ivan - 00:27:17: And so, but the power of science, right? The power of like innovation and science. And I just thought that, you know, it's a combination of strategy, but also just like how it happened. That like, that's a way that's a little bit more realistic for this particular technology and product. And I have lots of friends who, you know, started other companies, not too different from mine in terms of technology and kits and stuff like that, who didn't hit marks. Market went down, VCs pulled out, no more company, right? So I know folks like that. I also know folks who are successful. So it's not like everybody's the same, but that was just us. I think we're just like scientists at heart, you know?  

Jon - 00:27:55: Yep, absolutely. And I think the one thing I would add is just like knowing exactly what you said, knowing the game that you're playing and having just like taking a hard look at whatever it is that your technology or platform, whatever it may be. And like, I think it's exactly what you're saying. It's like not every outcome has to be a venture outcome. Most businesses in the world are like in between there versus like a, you know, a mom and pop and on one end, a venture scale business on another, there's a ton of gradation like in the middle and there's nothing wrong to be in there. Cause like I think exactly what you said is just like. You probably could do that pitch. It's like this will, every human on earth, like we'll be able to, you know, we'll sell to, but I think, you know, having that insight is very prescient because it's cool because like, you have like this, like it almost, you talked about like, it's almost like art. It's like, you have this creative freedom that like, it's not like I haven't worked at Phase, you know, it sounds like I'd love working at Phase, but it's just like, you're on this adventure to choose your own adventure. And you're kind of have this thing that's like that core engine that just like drives it. And it's just like underpinned with rad science, which is cool. So as you're looking forward, you mentioned you're starting to reach this inflection point one year, two years out, what's in store for you and what's in store for Phase?  

Ivan - 00:29:10: So I think that we are reaching a point where our cytogenetic cancer tech, you know, it's becoming sort of like a reality to a lot of the clinical folks. So I think for us, the next year or two will be transforming from, you know, a purely sort of like research tool to something that's moving more and, you know, more in the clinical kind of space. Maybe not a full-fledged diagnostic, but at least get it, you know, actual docs using it for patient care and things like that. That's what we're going to try, or at least, you know, companion diagnostics or something along those lines. So I think we think we will move into a more clinical environment, whereas the research stuff, again, we're focusing very heavily right now on solving the big problems. Like antibiotic resistance is, you know, people think about cancer because you make more money with cancer, but antibiotic resistance is by far a bigger problem in terms of social impact. So we're thinking a lot about these antimicrobial programs with our phage database, with our endolysin database. So that's where I think we will move is we're going to be doing more work to accelerate the development of these kind of anti-infectives, like proteins. And then on the cancer side, we will be moving the cytogenetics product more into the clinical regulated space.  

Jon - 00:30:28: Sweet. That's so exciting. I'm incredibly pumped for you. This is like, what an opportunity set.  

Ivan - 00:30:34: It's a crazy time to be at such an inflection point, right? Because there's the political inflection point and there's power. There's never a dull moment, right? 

Jon - 00:30:44: Yeah, never a dull moment at face. Well, one, I've had a blast and I've learned a ton. It makes me wish I was still able to be at the bench. It was a long time ago. I kind of hung up my lab coat a long time ago, but I got to relive it. It's at least like how I felt in this conversation. So thank you for indulging me. And in traditional closing fashion, we have two questions. One is, would you like to give any shout outs to anyone who supported you along the way?  

Ivan - 00:31:10: There's so many people who have supported us along the way. I feel like if I say one, I'm going to miss others. I'm going to feel bad. I should have prepared a little more.  

Jon - 00:31:18: It's okay. It's okay. I, I-  

Ivan - 00:31:21: Everyone who is supportive.  

Jon - 00:31:22: Yeah. Yeah. Yeah. And that's totally cool. Like I feel that. I think what I take away from that is like, it truly takes a village. 

 Ivan - 00:31:28:I think it would be impossible for me to name a person because it's a million people, literally. Not literally, figure it out.  

Jon - 00:31:36: Yeah, yeah, yeah, yeah, exactly, exactly. I guess for me, if I were to shout out, it's like my wife. You talked about that.  

Ivan - 00:31:44: But that goes without saying, right?  

Jon - 00:31:45: Yeah, yeah, exactly, exactly. I'm just like, holy crap. I would be homeless. I would have not a roof over my head. So like, you know, but I totally hear you. It's like these are incredibly complex things that we're tackling. And it takes a lot of hands. But the more hands makes for light work. And then the second question is, if you can give any advice to your 21-year-old self, what would it be?  

Ivan - 00:32:10: I would say that, well, A, that things get better because, again, it was a rough time. But also that the passion I had for science, to stick with it, it's worth just keep doing that. Right. That you don't see where it's going, but it's going somewhere and it's going to get there.  

Jon - 00:32:31: Man, I mean, like, I wish I had that advice when I was younger. So, you know, I don't know a better place to end the conversation. Ivan, you've been so generous with your time. Thanks again. The next time I'm in Seattle, I'd love to meet up, grab a coffee.  

Ivan - 00:32:46: Come and visit us.  

Jon - 00:32:47: Let's go stop by Vita and like, just like hang out. And, you know, so thanks again. We have a very broad range of listeners and I think everyone's going to be able to find something, whether you're a scientist or a business person, valuable from this conversation. So thanks again, Ivan.  

Ivan - 00:33:02: Thanks, Jon. Thanks for having me.  

Outro - 00:33:05: That's all for this episode of The Biotech Startups Podcast. We hope you enjoyed our four-part series with Ivan Liachko. If you did, consider subscribing, leaving us a review and sharing it with your friends. Be sure to join us for our next series featuring Aaron Edwards, co-founder and CEO of KiraGen Bio. KiraGen's mission is to eliminate solid tumours with AI-driven, multiplex gene-edited CAR T-cells by advancing cell therapies that break through immunosuppressive tumour barriers, enabling effective and durable cancer control. This is achieved by combining advanced AI with a deep understanding of biology to develop targeted therapies that promise to reshape oncology care. As co-founder and CEO of KiraGen Bio, Aaron leads a team of innovators dedicated to advancing CAR T-cell therapies for solid tumours. Together, they address the complex tumor microenvironment using combinatorial gene-editing techniques to push the boundaries of what's possible in cancer therapeutics. With a decade of cellular immunotherapy experience, Aaron has driven advancements in CAR-T and TCR-T therapies at Bluebird bio, Beam Therapeutics, Eli Lilly, and more. Armed with a Harvard MS MBA blending science and business, Aaron guides KiraGen Bayer's development of next-generation cell therapies, overseeing strategy, fundraising, and partnerships. Aaron is committed to bridging the gap between groundbreaking scientific research and real-world application, creating ventures that address critical medical needs and significantly improve human health. He's passionate about translating cutting-edge biomedical research into therapies that can change lives, driven by a belief in the power of science and technology to solve the world's most urgent health challenges. With deep experience in cellular immunotherapy, gene editing, and biotech leadership, Aaron offers a unique perspective on advancing next-generation cancer therapies, making this a conversation you won't want to miss. 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.