Bioprinting 3D Human Tissue To Discover And Test New Treatments With Viscient Bio's Keith Murphy

0:04Keith Murphy: Welcome back to the business of biotech. I'm your host Ben Comer, chief editor at Life Science Leader, and today I'm speaking with Keith Murphy, founder and CEO at Biziant Biosciences, a private biotech company using 3D human tissue models to develop new medicines. Keith is also executive chairman at VivoSim Labs, previously known as Organovo, a company he founded in 2007 that provides bioprinted tissue models for toxicity testing and drug development. Before Organovo, he spent 10 years at Amgen, where he was, among other things, global operations leader for the development of Denosumab, a.k.a.

0:46Keith Murphy: Perlia and Exgeva, which became a blockbuster product for Amgen many times over. Keith is an inventor, a biotech investor, and an entrepreneur, and I'm thrilled to have him on the show today to talk about building Organovo and proving the utility of bioprinted human tissue. his current work as CEO at Vizient Bio and the regulatory policies that could help change how drug safety is tested and lower the cost of development. Keith, I'm really delighted to have you on the show today. Thank you for joining. Thanks a lot, Ben. Thanks for having me. Sure. I want to start off with your background, Keith.

1:24Keith Murphy: You studied chemical engineering at MIT and did a senior design project with the great Bob Langer. How did your experiences at MIT shape your path into biotech? Well, it really pushed me into biotech, I would say. You know, I wasn't sure what I wanted to do as a chemical engineer, even, you know, in junior year. But then senior year working with Professor Langer, you know, he was a great leader, a great professor, a great scientist. And I really got interested in biotech from working with him and his work on tissue engineering and drug delivery especially interested me. And some of the, in particular, some of the heat and mass transfer challenges that have to be solved to make those things successful, in fact, were the narrow interest I had as an engineer.

2:16And so when I was looking for roles and what I might do, that actually shaped it because one of the opportunities that I saw coming out of school, one of the job opportunities I looked at was specifically a Bob Langer technology, which happened to be at Alkermes in Boston. And that's the job I took coming out of undergrad, was working as a process development engineer for Alkermes.

2:42Keith Murphy: And that was that was what a sustained release protein plant, like a once once a month human growth factor, I believe is correct. Yeah. So there were a couple of different technologies. It was an oral sustained release project and a injectable sustained release for for proteins. And the latter one is the one I worked on more in the end. Yeah, we worked on the development of human growth hormone once monthly. and I helped to lead the process development for that as the representative to that program of the department. And yeah, that was launched after I left, but I did such fun things as making the hands-on phase two drug for that with the team and designing the protocols to make that stuff, which was a fun setup and it's an interesting technology and it derives from all of Langer's work.

3:36Specifically, it was a previous company, I think Enzatech, that Alchemuse had bought.

3:40Keith Murphy: So, OK, so then from Alkermes, you joined Amgen, where you were steadily promoted over a 10 year period. What what could you tell me about that experience, Keith, and and maybe how it led to the founding of Organovo? Sure, I guess at Amgen, I first I was technical. Amgen basically wanted to do sustained versions of its proteins. Right. So leading biotech company wanted to do sustained sustained long acting EPO, sustained long long acting GCSF and other things. And yeah, so I was part of a group of people that were actually brought in around the same time to form a new arm of the company to do that within pharmaceutics and process development, let's say.

4:27And, yeah, worked on those kinds of things for a while, four or five years, tending to lean over into team leadership in a technical sense and leading, you know, leading teams of folks doing more than just that, but across the spectrum of drug delivery and different innovative ways to do things like needle free injection, not simply sustained release, things like that, or where I ended up working on the technical side. And then Amton was just a great company. It still is. You know, at the time, it was a wonderful place to be. Really a lot of energy. When I first got there, you know, you'd be walking down the street and there'd be a party and you're like, what's going on?

5:06I'm like, well, we're opening a new building. So you'd go over and have a bunch of barbecue. And, you know, it was a really vibrant, you know, can-do place. Really had the ability to recruit top, top people. So it was a great environment to be in. And I really enjoyed that. When I was there, it probably went from about 2 ,000 people to about 12 ,000 in the 10 years I was there. So there was tremendous opportunity as well to grow with the company, I would say, and that if you delivered, you could grow in your roles and your opportunities that were given. And the people there, I was in Dennis Fenton's organization.

5:40So for people who know him, kind of legendary within that company and in the larger world. He's been a director of places like Genzyme and other things as well. And, you know, he was – it was just a great, great group. And so, you know, got the chance to grow with that, went to business school at UCLA while I was there. You know, full-time I went to business school, so did that. And then when I came back from that or when that was ending, I got an opportunity to be the global operations leader for a number of products. When you're starting out doing that, you know, you're going to manage smaller products.

6:19And I manage things in phase one and phase two. You're on the development team with the group from, you know, the regulatory and the development leads, the commercial lead. And that was a great experience. And then when that drug, the rank ligand inhibiting monoclonal antibody, the nosumab, when that was in phase two, I got put on it. And that just grew. And that became like the lead development program for the company. probably at the time the biggest development program that the company had done, you know, it ended up being, I believe, about 14 ,000 patients in 31 countries and seven concurrent indications was the clinical trial program.

6:58And so it was a lot to do, plus plan for the commercial launch that included, you know, contract manufacturing sites across the globe. So it was great. It was a really fun program. And I learned a lot. I think one of the biggest things I had the opportunity to do was be with a really a team on the commercial and clinical integration of the plan. Right. That that just seeing that and being there and helping with that was really powerful and good education about the business. Yeah.

7:26Keith Murphy: Well, let me ask you this business school or the school of Amgen. Which did you learn more that's helped you as an entrepreneur and company leader? I mean, I'm a big fan of, you know, the experience leading to greater opportunity in the entrepreneurship. I think entrepreneurship is kind of more inherent than taught. And so I think, you know, I think I've probably learned more on the job. I would say business school, there's a lot of things you learn. They're just not the same things, right? Right. Yeah, right. So they're both useful, I guess, is what you're saying. Um, uh, so after 10 years at Amgen, you decide to found Organovo.

8:06Keith Murphy: Can you, can you talk a little bit about maybe that decision and, um, just how you were able to fund and stand up the company? Yeah, sure. Yeah. So, um, you know, it was an interesting path I took to entrepreneurship because it was around 2005 when I started to think what I would do next. And, you know, I had great opportunities at Amgen. It was a great place to be, but I wasn't sure. You know, I actually thought that the smaller company environment, Alchemist, that I had been with because that was about 60 people when I was there, that felt like it suited me more. And it felt like the larger next opportunities at Amgen weren't the ones that I was seeking necessarily.

8:45You know, there were some great things to do there, but that the next steps above what I was doing didn't have a lot of attraction for me. And I kind of came to entrepreneurship by process of elimination. I'm like, well, if I'm not going to go do that job and that job and that job, which would be the natural next step within the company, I thought about it. So, well, what am I then? What do people do if they don't stay within the large company environment? And then by process of elimination, I kind of realized entrepreneurship was logical and fit my skill set. But, you know, one good thing about the role I had been playing was that there was about a thousand FTE executing on the plan that I was developing, the strategy for operations that I was developing.

9:27I had to go around to different Amgen sites around the globe and sell that plan and make sure those teams were on board, on track and on timeline. and also matrix it with all the vice presidents of all the functional groups and make sure they were, you know, aligning their team and their strategy with what we were doing and that they bought in and that they had their input as well, of course. And so that's a matrix role. So I just felt like, hey, I've actually kind of shown some of the skill set of an entrepreneur. So I felt confident that I could get in front of people and sell things and bring a whole plan together.

10:00And then so I felt confident from that perspective. And I knew that technically I had a lot of technical insight and because I had the background as an engineer. And I said, well, let me try and leverage all those things at once and then jump into entrepreneurship. I thought hard about the risk, but then I said, well, maybe the risk of not doing it is greater. I thought, okay, so if I try now, I'm young enough that if it doesn't work, I've got a safe landing at an AMGEN. I can come back or I can go somewhere else in the industry and maybe I get three swings too. I can try and do a few different things if the first one doesn't pan out.

10:35So I felt confident about that in that sense, and it was worth the risk. But nonetheless, I don't know that I fully appreciated how hard it was and all the sacrifices that would be necessary after that, too.

10:49Keith Murphy: Well, let's talk about bioprinting, which, you know, was one and kind of one and the same with the foundation of Organovo. That's what you were pursuing. But how did you first become interested in that specific field? Well, my take coming out was I need a great technology. That was what compelled me. I wanted to help patients, but through a cutting edge technology that was hard to develop and that no one else really had access to. And I was fortunate enough to meet a biophysics professor through a couple of colleagues of mine. And they both worked at McKinsey. They were a colleague of mine that I knew from the industry and the professor's son.

11:31And we got together and started talking about this bioprinting technology. One thing that I really felt was interesting to me about how it came together was that I had particular insight from my technical background about why this technology was great and could work well. you know, just from having been proximate to Langer's work, working directly with his drug delivery work, and then being at Amgen working, you know, both Alkermes and Amgen working hands-on with these kind of polymers. They're the same polymers in the drug delivery side that are used in tissue engineering. And I saw how some of the tissue engineering challenges were not being easily solved using these polymers.

12:14And what the professor had, Gabor Forgotch, he was out of the University of Missouri. And what he had that was really compelling was a way to make a scaffold free tissue, which really, to me, was the technical insight I had was that that could be really powerful and get away from some of the negative impacts of having polymer. When you think about one reason, you know, 2D cells or biology on a Petri dish surface doesn't work, it's really the attachment to the plastic, the tissue culture plastic. And, you know, people take a lot of shortcuts, you know, collagen sandwich culture, basal groups of cells that can be feeder cells and things like that to get around that.

12:56But if we could make a tissue that actually didn't interact primarily with the plastic, but that all the cells interacted together apart from the plastic, that seemed really powerful to me as a way to get away from the changes to biology that tissue culture plastic can induce. And that was, that's really why I jumped to do it because I thought that was the breakthrough.

13:16Keith Murphy: And on the like the funding and startup, how did that come together? Okay. So then on that side of things, um, you know, basically, um, I did, I reached out to my Amgen network. Fortunately, Amgen had been very successful and the number of people there had been successful. And so folks like the global head of, uh, the head of, um, global marketing, You know, were some of my early angel investors, basically, to get the company going. And I just said, hey, I think we can make this work. You know, I really think we have something here. Raise the money first that way and then expanded it out to wider sets of angels.

13:55We got a ton of non-dilutive capital by working our butts off and getting grants, getting deals with pharma early on. So we had deals with Pfizer. We had to deal with J &J early on before going public. Those both gave us great funding, let us make scientific progress, let us learn what these partners needed, and looked great when we eventually needed additional investment.

14:21Keith Murphy: Yeah, helped to bring in additional funding, I'm sure. Yeah. We also got a seed investment from Sequoia Capital, which helped too. So we weren't in their main fund, but we were in their seed fund. So that was really nice too. So now you have your own company by focus on bioprinting. What were some of the biggest early obstacles that you encountered in trying to make bioprinting commercially viable? Well, it's a challenging thing to do, bioprinting and making these tissues. We actually started with blood vessels, partially because the professor's work was making a pig blood vessel. His primary work on establishing this platform was in making a pig blood vessel.

15:03And what we said we would do is, you know, make it take steps to making it immediately more possible as a product by jumping into making it a human blood vessel right away and taking it from being a single layer of smooth muscle cells to being a three layered construct that had fibroblasts, smooth muscle and endothelial cells. So we were biting off a lot. But, you know, the team stepped up and did it. One of our early chief scientific officers, Marie Cheta, really made it sing by pushing the team appropriately to challenge themselves to kind of find solutions for some of the things that were going on.

15:45And at one point, I remember to solve some of the technical challenges, the team had to come every three hours and work with these constructs for weeks on end because we were making these blood vessels that we'd hold for three weeks to grow them. And every three hours, especially, I guess, in the first seven days, they needed to be tended to. And so we just had a plan. We had a very small team. It was like five people, you know, but someone has to touch it every three hours. So that's tough. And it's tough on a team, but the team really stepped up. And we did those things. And we got to some tremendous blood vessels.

16:14And essentially, we took the professor's technology in-house and developed that as well. and I would say we went from the professor and his team at Missouri making, you know, 10 pig blood vessels in 2008 and then by 2010 we made, you know, 10 blood vessels a week. You know, we could make 10 blood vessels a week if we wanted to. So, you know, we had really done that. The other thing we did was we actually worked with a great company, Invitech, which is an Australian and San Diego-based company, And they did the product development for us on the bioprinter itself. So we said we got to keep the delivery end of this identical to what's happening in the professor's lab.

16:56But we need X, Y, Z control that's automated. We need an interface with the computer where we can program it. And we needed all that to be much more robust in OEM equipment. And that worked out great. They were wonderful.

17:08Keith Murphy: And did you have a specific application in mind even at that very beginning, kind of early stages where you're making those blood vessels? or did, you know, through the process of actually doing it, did that evolve? Well, it evolved a lot. So, you know, pivot is a word we learned a lot about, right? But early on, our initial plan was to deliver the blood vessels for transplant to do specifically, you know, and this is still a need. It's actually a big problem still. We didn't continue pursuing the blood vessels and no one has solved this issue. You know, when you're – once you're past the knee, the smaller blood vessels, three to five millimeter blood vessels, they don't work well.

17:52Like artificial materials, synthetic materials don't work well in those small diameters. And if you put something through the knee, the fem pop from oral artery to the popliteal artery, that transition, that's – you get a lot of kinking when you're bending the knee and things like that. So there's a lot of problems at the knee and below in these peripheral bypass surgeries. Yeah. So, you know, we had some great people. I mean, we had the chief of vascular surgery University of Wisconsin on our board and we were doing that. We were doing micro vessel surgery in mice to deliver these things. So, yeah, we were doing that.

18:28And then that transitioned when we took the company public. We just, you know, we transitioned to really saying, OK, what are we going to invest the go public money in? And it became more about liver tissue. That's been that's been a big focus since then. But before then, it was the blood vessels.

18:44Keith Murphy: Got it. Yeah. And I did want to ask you about the process of going public. I think that was 2012. Is that right? And it was through a reverse merger? Yes. Yeah. And that is, of course, a pathway that's coming back into vogue. 2026 has seen more than twice as many biotech reverse mergers compared with last year, 2025. I wonder, Keith, what you could say about the reasons for choosing that route to public market at that time. Yeah, sure. Well, you know, there were really two options at that time is go bigger on VC side or go public quickly because we hadn't taken VC money at that point. And we were really efficient from a capital perspective to that point.

19:28Like I said, we had a lot of, I don't know, we almost had maybe 60 % as much non-dilutive capital as invested capital. So that really, you know, gave us options. And it was very difficult to go public around those times, though. It was not an easy way, you know, time 2011, 2012 was a market more comparable to today, I would say. And, you know, where there's not IPO windows open. And so if we were going to do that, it would have to be through an alternative route. And then, you know, we just looked at it from our stockholder perspective. And, you know, we ended up with the founder group ending up with still collectively 30 % ownership at the far end of that process.

20:05And so that was one thing we targeted was like if we went through the traditional, that would have been 10 % or less. Right. So so we thought that was attractive. We found a boutique bank that had done it before. Really interestingly, they had also taken a Bob Langer company public through that same route. So I got to call up Professor Langer and say, hey, I'd love to talk to you about how that went. Was it a good route? Did you think it worked? You know, tell me about the bankers. You believe in them. Could this work? And that was – they had done other successful companies by the similar route.

20:39And it really could work. And Bob had good things to say. So I think that worked out. You know, being able to vet it and everything was really powerful too. I kind of got to see the business case of something working to buy in. But that made it easy to do. And it worked great. You know, when we went public, we got the funding we needed. We had good investors and sticky investors. And then, yeah, things were very successful. It worked out great.

21:03Keith Murphy: One more question, if you'll indulge it on just the kind of public markets situation of today, the IPO market is recovering. How would how would you say today's environment compares to 2011, 2012? And what is and what does that mean for founders, you know, weighing their options? Yeah. And so there's a lot of, you know, a lot of companies seeking to do reverse mergers and things like that now. I would say the difference is that there's reasonable private capital available. And the world has changed from, you know, the availability of family office capital and things like that. There's a totally different level of private capital.

21:42it's the public markets that have deteriorated a little bit and had some problems. And so, you know, there's private liquidity and other things going on that are much more, that are very different from where it used to be. You had nothing like that in the past. It was almost public or nothing. And so that's a very different world and gives people options. But you see plenty of people, even great companies, really great, really great companies that definitely would be in the prime shelf of an IPO market if there was an open IPO window, and they're still trying to do alternatives. They don't always go that route, but they look at them, and some of them do them.

22:20And so I think that's still a way for everyone to go, and hopefully more often, though, they're bringing a lot of private capital into the deal.

22:30Keith Murphy: I want to jump ahead to Organova's disease model, which produced this FXR agonist program that Lilly acquired in 2025. It's now testing it in combination with mirakizumab and Crohn's disease, I believe. How did a, I guess, how did a platform company end up discovering a therapeutic at Organovo? Well, that's a very interesting story is multiple steps. So you'll have to tell me, should I go through the steps at a big picture and then you can drill down? Yeah, I think that. Yeah, sure. Okay. Big picture. We were doing – what we did with our invested – with the IPO money and then we raised over$100 million in secondaries at Organoma.

23:15We had deals with Lazard, Oppenheimer, Piper, Jeffrey at the time and others and Jeffries. And so we did a whole bunch of deals. We had good capital and we were well capitalized. And we invested that in a sort of staircase strategy with the liver. It was we can do liver tox with a liver tissue model. Then we think we can get into disease modeling and then we can do the transplant tissue. But the board was probably more focused. I brought in a great board. You know, we had wonderful people, Tamar Hausen, who had run, you know, SR1 at GSK and had been corporate, had a corporate development at other places, BMS and stuff.

23:57And then, you know, the former CFO, Beckman Coulter. So we had great, great folks, but they were a little more enticed by the tissue engineering side because that was the attractive, you know, buzzy thing. And so but I kind of ended up being more attracted by saying, like, hey, well, how can we affect a billion people's lives the fastest? And I think that gives you the biggest win for investors as well. Right. We're going to have the biggest impact on patients and the biggest win for investors. And I said, for me, after doing this for a few years, it became about the disease modeling a little bit more.

24:35And I pitched to the board, hey, let's take what we're doing but add to it and we can do the disease modeling and develop our own compounds. And the way to play that would have been MASH, right, which Vizient ended up doing. But the board preferred not to. They were worried about the additional capital expense. I was only pitching 10 % for the first two years of growth of the capital expense. But, and I had a great person to come in and run that. I mean, I had a guy who had been a head of external innovation at another top 10 pharma and had sold a biotech company to the pharma to get in there and new drug discovery.

25:17He was willing to come and be our lead on that. But the board just didn't choose to do that. So I said, hey, I'll go do it. I'm going to go do it in a private company. Let's partner together still. I'll license the tech or actually use the tech as a CRO and license it in the new company. And I'll go make a company that does liver mash. I'm sorry, mash liver fibrosis, you know, mash disease models, because that was where my passion was then. And I thought that was the biggest win. And so I went and did that. You know, I started Vizient. We did exactly as I just said. We stayed close to Organovo.

25:51We used the Organovo technology through Organovo's hands. We hired them as a CRO. And they, being interested more in the revenue side and growing that, were happy to do that. They took the revenue side of that business arrangement and that all worked out for everyone. So that's what took us over into that arrangement. And then when they were moving towards the liver tissue for transplant but then kind of had trouble with the timelines for that, then I came back to Organovo and said the plan would be when we shifted that, let's go into the disease model. And then specifically, we had done a project before I had even left at first, which was an intestine project with Merck.

26:33Merck had funded us to do some liver tox work plus an intestine model. And we built a great intestine model. And then we repurposed that into a disease model when I came back or we finished the work of making it a disease model when I came back. And that's what led us down the discovery path.

26:51Keith Murphy: Got it. Okay. Okay, and Vizient Bio, you found it in 2017, is that right? Yeah, that's right. And the Lilly deal that I mentioned previously with Organovo, that was 2025, is that right? Yeah, 2025, right. 2025, I think shortly thereafter, Organovo rebranded as VivoSim Labs, and as you described a CRO service business. And you've kind of described how the two companies work together. How do you, well, let me ask this, how do you split your time, you know, and, you know, keep the two companies distinct and work between both? You just have to do, you know, 50 hours of work or more for each all the time.

27:36So, you know, it's a little hard, but it works out well. And so, you know, fortunately, I'm kind of at the point in my career where I'm happy to work all the time. And so you just have to get the stuff done for both companies. And as executive chairman at VivoSim, that's the – it's CEO equivalent plus the role on the board, right? So it's still running everything. But the key thing there is I would say VivoSim has a public company, has a really nice infrastructure and great team members. And it makes it easy. You know, I think that having the resources to run it appropriately makes that makes that really easy.

28:17Got it.

28:18Keith Murphy: OK. For listeners to the podcast who aren't tissue engineers, can you describe what you know, how the 3D bioprinted liver tissue, what it actually looks like and maybe how it's built? Well, sure. Yeah. And so essentially, one thing to know is that it's not all bioprinted tissue. It definitely started that way. I would say in 2014, we kind of looked at what we had built and said, we're probably 10 years ahead of when this is useful. And we started to back down on the complexity, in fact, I would say. Oh, interesting. So, you know, so we've built since then between the different companies methods to do higher throughput, simpler models that keep enough of the biological relevance to be useful in a context.

29:08I'd say the bioprinted model is the most complex and the best representation of the final tissue in the biology, which you can get aspects of it properly represented in simpler models. So bioprinted, to bioprint something, the core of the professor's technology and learning was that you could make something scaffold free. And we do that essentially by having a gel inside the bioprinting ink that carries the cells with it. But the gel is only a couple percent. And so the gel is 5 % or less. The cells are predominant. That's really the innovation we introduced was that, you know, many people will make like an organoid.

29:52An organoid is going to be matrigel with cell islands inside of it almost. Okay, the gel is the matrigel. Gel is matrigel. Not for us. Right, right. Organoids, right. The gel is the matrigel. And maybe 30 % of the volume is cells and 70 % gel. That's been the state of the art. What we did is we said, let's completely invert that. Let's start with 98 % cells and a very small amount of gel and make the gel go away. And then it's 100 % cells. And so we make tissues. We really do make tissues. And we have patents around that that really cover, you know, making those tissues in that complex way. We were the first to introduce endothelial cells in a way where you got incredibly robust vascularization.

30:37I mean, it's basic vascularization. It's protocapillaries. But, you know, there were top professors in the field at conferences, flexing at conferences about their eight cell layer thick tissue when we were easily readily making 40 cell layer thick tissue. And so, you know, we really had done a great job mastering that. And so – but I said, you know, with the technology, we had to leverage the ability to make non-vascularized tissue, the simple – you know, we can make a thing a millimeter thick. What do we do with that? What problems can we solve with that? We can't go solve all the tissue engineering problems that are in the future.

31:15And since then, you know, 10 years have passed. There's great academic efforts out there making good progress on making actual blood vessels inside these tissues. But essentially, to get back to your question about what you do, is if you want to make something that's a tissue, you would just reimagine the architecture, the 3D architecture of it as a little Lego house, right? You're going to put – what bricks are you going to put in what positions that represent the individual cell types? And, you know, you can work at a 200 to – 100 to 200 micron size, a voxel size, you know, a cube. And then you imagine putting cells or a cell mix, either one cell type droplet or a cell mix in each of those spaces in 3D space.

31:59And you would just layer it. You would layer it up. The instrument goes and layers it. The key thing with bioprinting and all 3D printing is that you do need to think about how to solidify that, right? So if you think about in 3D printing, if you're working with a wax or something like that, it has to solidify fast enough for the next layer to be put on so that you don't get sinking and things like that. We have the same problems that we had to solve. So there's different ways to do that. But the gel materials help with that. And essentially, we had to work with it in a way where we could allow the gel to disappear with kinetics that supported the cell adhesion molecules taking over.

32:43And then eventually, extracellular matrix on the more, you know, the cell adhesion molecules are on the 0 to 24-hour time frame. They're highly relevant. And then extracellular matrix, more like 24 to 72-hour time frame, they start to take over and make the tissue robust. And we had, you know, these blood vessels would grow when we made blood vessels, for example, with the extracellular matrix grew so that they could withstand, you know, 1200 millimeters of mercury by 21 days. So, you know, your blood pressure is measured in millimeters of mercury. So if you're 120 over 80, that's millimeters of mercury.

33:19So we had something that was 10x human blood pressure that it could survive, you know, within 21 days.

33:25Keith Murphy: So in a bioprinted or just a, you know, a tissue like you're describing, how many cells are in that tissue? Like how many total cells? Yeah. So let's take a liver as an example. The liver, bioprinted liver, it's three millimeters across half a millimeter thick on a transwell surface. So that's one million cells. And then because of the costs of that, but also, you know, the difficulties of maintaining it and all that, there's a higher throughput version, too. That's the best fidelity because you also have a lot more architecture in that. You've got much more relevant architecture going on in something that size.

34:03Different cell types is two, right? Yeah. Well, we have four different cell types. But then we also took the – just in the context of drug discovery at Vizient specifically, we said, okay, now we've got this bioprinted. We published with David Brenner of UCSD and Sanford Burnham that taking patient cells who have MASH and putting them into that liver model, we could retain the phenotype by handling it the right way and get MASH phenotype in that model and C-deposited collagen. You know, we matched all the known compounds that have been in the clinic in terms of whether or not they reduced fibrosis in the human.

34:46They matched that in our models. So all that we did with the liver, but then with the bioprinted liver. But then we had to make it more useful in a drug discovery setting by making it higher throughput as well. So we also built spheroids in parallel. They don't have architecture. They form a little bit of capillary, but they don't have robust structure in them. But they have all four cell types, and they give a lot of the – within a given target, for example, once you're looking at one target's biology and effect on fibrosis, you can see, you know, you can see a lot of activity. So it's a, it's an abstraction, but it can be an okay abstraction in, in many settings.

35:27And so we found a target and we did these, you know, sceroids that are, you know, thousands of cells instead of a million and they're 200 microns across, which is like a, you know, a fifth of a dime width or something like that. Right. So that we could make many of those and we could do 96 well plates. And then we could test. We did a, you know, for one of our drugs at Vizient, we synthesized 500 compounds and we probably tested 200 of those in SAR in the actual spheroid tissues, which was tremendously powerful for really informing the discovery work.

36:05Keith Murphy: Okay. So the spheroid tissues where it was a kind of way to scale, you know, what we're doing. That's right. Yeah, we said we need you can't just have one model for drug discovery. You need to think about drug discovery and what each step needs and really pitch to that. So we've developed ways to do that and tools to do that. And then we even think the next next step and next level. One thing that's really interesting about these practices and using in particular, you know, it's not just that what we've mastered is the 3D aspect of it. We also bring another strong leg to the stool from a scientific perspective, which is that we focus on using primary cells because we think that best represents the disease.

36:50And our way of retaining the disease model, retaining the signature of the disease in the disease model when we take primary cells is the 3D tools that we use because you can retain a mash signal. You need a 3D model to show fibrosis, right? Collagen deposition on a dish surface is not relevant to the tissue condition. The tissues are aberrantly going to behave on a 3D tissue culture plastic surface. And so we really focused on primary cells, and that really adds a lot of the value to it. And we see the actual, we think, disease signal carried over epigenetically from the patient. And that's been a huge key to our success as well.

37:35Keith Murphy: On the 3D bioprinted human tissue, and maybe we can use the liver toxicity model as an example, but I'm curious how that compares to a rodent model. And maybe it's not a one-to-one comparison, but, you know, what would you say about, I guess, the innovation of this type of NAM, you know, versus what's been traditionally used, animal models? Okay. And I can talk about liver tox as well as disease modeling and all that. Yeah, sure. Yeah. Okay, great. Let's do that. So if you think about just the concept of inducing a disease in an animal model, the scientific challenge is very high, right? First of all, you have to know what the disease is.

38:23We don't know what diseases are. We measure biomarkers of disease that we think represent the disease. And then we go to an animal and we try and induce something that would match those biomarkers of disease. And a classic failure case would be MASH, you know, fatty liver disease, where people induced fibrosis in an animal with an industrial chemical for the first couple of decades of work and said, oh, look, we got a we stained for fibrosis. It's there. Therefore, that's the same thing as a disease induced in a human with 30 years of a bad Western diet. And that is not the same. And we've proven that again and again now by trying drugs that worked in the animal.

39:01So it's not only the species difference. It's the difficulty of inducing a proper disease model. And one thing that we do very differently by using the primary cells, as I said, is we know that the cells have the right disease. The scientific and engineering challenge is can we keep it around, right? It's just a much different challenge. I think it's an easier challenge to broach. And we've done it successfully. We did it in IBD to make the drug that we sold to Lily. You know, we were doing it in we did it in MASH. So I think it's it's a great it's a great way to look at it. Now, that's not to say that animals haven't done a lot of great things and have great utility.

39:40It's just they're different. And then, you know, with let's say looking at liver toxicity. So VivoSim is using human models that are, you know, made of primary cells, again, from individual people. And then you expose the drug and see if it causes liver toxicity. Well, that – there the species difference is huge, right? Because, you know, the rats have had a very different evolution than humans. And, you know, they're more robust to certain toxins and maybe more susceptible to others. But they just don't show everything is toxic that ends up being toxic. And the challenge is in a drug development setting, you're spending – if you make a mistake and pick a drug that has rat talk – that looks clean in a rat and other species but ends up being liver toxic in a human, you spend$50 to$200 million before you figure that out.

40:37Because you make that decision at the lead optimization, the lead in candidate selection. Right. You test it only in animals for a while. Then you're going to test it in humans. And if you're lucky, maybe you see something in phase one. But realistically, it's going to be something that's more on the subtle side because it wasn't picked up in animals and it wasn't seen in other studies. It's going to be more on the subtle side. And the other thing that really differentiates use of a human model from both animals and, you know, clinical studies is that we're sectioning and looking at these things from the start.

41:10Right. Right. We can take this thing at three days and look at what's going on with your drug. Whereas the human, you're waiting for a clinical signal to emerge, a symptom to emerge, or something measurable, blood chemistry, to emerge over time. Very different. I can look – we're going to be able to eventually AI train, I think, with actual just bright field microscopy. The images at three days are going to tell us if that thing is going to end up with liver toxicity showing at 21 days when we section and stain it, if that makes sense. You know what I mean? Yeah. Like we can play with these things.

41:41There's live imaging emerging and all sorts of things that are good technologies that are going to help us. But it's just a world of difference, the level of understanding you get to. Transcriptomics, we're getting into the liver tox transcriptomics. We're not only going to be able to tell people if their drug is toxic. We're going to be able to give the chemists hints at a mechanism and maybe they can steer around some of the problems earlier and faster.

42:05Keith Murphy: Yeah. I mean, and to your point, even if you are, even if there are signals showing in phase one, you still spent a lot of money doing those animal studies, you know, before that. And these problems persist. They're real problems. So we haven't published this yet, so I have to be careful. But let's just say there's a top 25 global pharma company that's had two drugs fail due to liver toxin in the past four years. We can see both of those clear as day in our mouths, like as toxic. You just wouldn't take them forward if you were working with us. So I don't even think there's a case anymore for the FDA to not be using our model or a model like ours.

42:38There's others out there. And say, you know, we require something to be screened in this because, you know, if you look back at flutamide or some of the drugs that were toxic, these things just they're like huge beacons in our model. Like this is a toxic drug. They weren't discovered in animals. And people have backfit animal models by little tweaks and say, oh, now we could have seen it. But that's a backfit model, right? We know that those models are backfit. These things are just literally taking a human biology and making it accessible in a dish and then finding out if there's an effect on that or not.

43:11It's a very natural experiment. You know, people probably, honestly, in my opinion, we've got, you know, people have tested, multiple companies have tested hundreds of compounds to validate these or qualify them, however you want to phrase it. and, you know, beyond that, I think anybody requiring much more before they start to use these is thinking too much about it and getting stuck in something. It's just like, to me, it's as valid as, hey, if a 14-day animal model shows you something right now, that's a signal you got to worry about. In our model, if you look toxic at seven days in our model, you know, you probably shouldn't take that drug forward, right?

43:45What are you trying to work around? Hopefully at that stage, our sweet spot with VivoSim is taking people's compounds when they have like 12 compounds and they're final and they're about to do lead selection. And we just say, hey, two of these have red flags. Don't take those. They would not have gotten that red flag as part of their data set before. And they would have had a one in six chance of taking one of those forward. The real rate is about 5 % that they end up with a liver toxic compound later. But for some programs, they're just closer to liver tox issues. So that is more that shine. It's like for a lot of companies, it's zero out of 12.

44:21But for some companies, it's two or three out of 12 that flare up. And then they just pick one of the other nine and you're golden, you know, so it's a really easy process, too.

44:31Keith Murphy: Yeah, there was a I had a guest on. It's been probably last year, at least six or eight months ago. And I can't remember who it was, but I always remember this analogy when I'm talking about, you know, animal models, which is he said, you know, imagine if if chocolate had to be approved by a drug and like your your animal model was canines. Like, you know, we wouldn't have chocolate. Right. Right, right, right. That's very true. Yeah. On on like FDA's consideration of these models, you know, this most listeners probably know this. Federal agencies are pushing toward FDA, namely pushing toward new approach methodologies, NAMs and away from animal testing.

45:12Keith Murphy: Are there new policies that you would like to see the FDA introduce to, you know, to help accelerate that transition? Are there any regulations currently on the books that you think need to change? Yeah, I think so. I think the number one thing for me is I firmly believe at this point it's unethical to put a drug into phase one that hasn't been liver tox screened on somebody's platform that looks at human cells in a complex way. It's just to me, it's not ethical anymore. We've we can pull out things and we can pull out things that are still getting through the system. And so FDA really needs to think about that.

45:51I think that's the number one thing just as a regulatory. You know, they are – they would not let something move forward that had a big flag in 14-day animal talks. There's no different anymore. It's no different. We have a useful system that's got enough data. We're past that. Then I think then what we also need to do is think about – and the FDA is doing this really well, you know, how we can stimulate more use of these models. And FDA has a roadmap for adoption of these. what everyone needs to do there is get away from the false, the sort of like false argument that, that I see a lot of people get into, especially on LinkedIn.

46:27For some reason, people are obsessed with like, we're going to get rid of animal models. Oh no, we're not going to get rid, you know, don't get rid of animal models. Yeah. They just did that. That's the, that's the argument that people get lost in, right? We're going to completely replace animal models and they just, everybody wants to, you know, the outrage of, of the social media age is just to fight about that when the real answer is like, let's use these things in a complementary way as fast as we can, get as much data from non-animal models, from the human type models we're building, get as much data to compare things as fast as we can, and then displace and stop using the animal models that don't add value over that, right?

47:06And so, you know, obviously, ADMI and distribution and all this stuff, systemic talks, there's a ton of reasons we're going to have use of animal models for a long time. But you can complement with things and then start to learn, well, maybe we don't need to do as many things in animals, especially I think about investigative talks where people are solving problems when they come up in another species with a lot of expensive animal studies to resolve things. But just doing 3D human models comparing, for example, if a rat liver tox problem comes up that you want to explain is probably specific to the rat, it might be more efficient to do that work in models of our type with rat cells versus human cells.

47:50You could probably answer those questions for, you know,$400 ,000 in three months versus$1.2 million over six months with animals, right? So there's things where we'll displace animal use naturally. And the FDA can push forward, I think, policies that, and legislators, we need to get legislators involved to push this forward. One thing that we're promoting from a legislative perspective is that we actually give incentives to companies to include more human model data. So NAM model data where, you know, FDA has some carrot for people like that. Now, what's that going to look like? We don't know yet.

48:28But one thing could be a lottery ticket for a priority review voucher. You know, just because you include animal data, you're not going to get a priority review voucher. But maybe you get a one in 2 ,000 lottery ticket for one. And then everybody's incentivized to put additional data into filings that helps them get their hands around these technologies, that helps FDA get their minds around these technologies and where they're useful. And everybody plots the chart faster to a better future just because there's more data.

48:56Keith Murphy: I like the lottery idea. It strikes me, you know, like given some of the, you know, the last year at the FDA, it seems like you'd almost have to have like one of those old school bingo things, you know, where you just see every company's name go in. You see them like analog. Think about how fun that would be, too, right? To have that event. Yeah, we need full transparency on that. And I think there's some of your PricewaterhouseCoopers listeners are really salivating right now because they want to run that process. Yeah, absolutely. Absolutely. Absolutely. We are we're getting to the end of our time.

49:29Keith Murphy: And I realized, Keith, that I didn't ask you, you know, about, you know, the current status of of what you're doing with, you know, development programs at at Vizium Bio. Like, can you give us a sense of kind of where you're at and, you know, when you might get into the clinic? Yeah, sure. So what we did with the discovery work, we did essentially target identification and validation. And it's a great technology for validating things. We spent a lot of effort making sure we could validate targets in six different ways. So you can use tool compounds. You know, we can use siRNA, for example, to knock out a gene.

50:12We can overexpress genes with lentiviral overexpression and things like that to make sure that we've got, you know, a pathway that really is central to a disease. One of the challenges is that what we tend to find is, you know, most biotech work, if you took the big picture of biotech right now, a lot of the work is obviously new modalities. Let's hit a target that's validated with a modality that allows us to hit it that we couldn't have before. So you're going to, you know, maybe hit something with protein degraders that you couldn't or siRNA that's attractive as a target, but you couldn't hit it any other way than in the liver with an siRNA or something like that.

50:48We end up with a very different paradigm using these methods. We see targets that nobody else can see. But that creates, you know, then you have a lot of work to do to get people's heads around the targets because they're novel targets. But we validate them many different ways. There's usually, you know, there's been enough work done on the across the genes that are out there that usually there's preclinical knockout work done and safety is established and things like that for even the novel targets. And so we go and we and we pick things that are unlikely to have side effects. And then we look at opportunities.

51:20One of them, we actually did a deal where we in licensed of rights to a drug that's a known fibrotic drug. So using these tools in fibrosis is really interesting to me and continuing to do that because there's a lot of antifibrotics out there that have been tried in cancer indications. We tend to work in soft tissue, other soft tissue diseases, but fibrosis is a really attractive play for these 3D models. And then there's antifibrotics out there, you know, waiting for something or that were developed but can't be taken forward in their own indications. And we essentially were able to find something that had enough patent life and an attractive portfolio way to go after fatty liver disease with that.

52:04So we've in-licensed that for North America and Europe and are moving that. That's a phase two ready drug. And then the next thing is a IND enabling stage drug that's entirely in-house developed. We did all the medicinal chemistry. When I say entirely in-house, you know, a lot of India, China, CRO. But other than that, you know, we developed that and known all the rights to it. And that drug is passed. You know, we did take that into some of the traditional animal models for MASH to demonstrate that it works there. That's still a validating step for many pharma, I would say. Probably about 40 percent of pharma probably wouldn't even look at something that was only in the other models today.

52:44Keith Murphy: But then you could have been confident without doing the animal study. But you did that essentially to double confirm. I personally would make bets. You know, I'd have to understand the big picture. There's a lot more. Like if you have GWAS, you know, if you have other forms of genetic validation and pathway validation like metabolomics and things that validate a pathway, I would make a bet personally on some of that stuff with just the human model that we have. But, you know, now that's certainly not universal, not even close, I would say. Plus, you do need the animal exposure anyway to validate other things.

53:21There's reasons to have longer term exposures and things.

53:24Keith Murphy: On that phase two in license or phase two ready candidate, is that awaiting like some funding for phase two or what will prime that? That's the next step is to raise venture for phase two for that. Got it. OK. Yeah. But the good thing is it's mash. Right. So, you know, I think the latest, you know, Roche picked up 89 Bio, right? So, you know, you're talking$3 billion deals for things that finish their phase 2A, right? So, you know, so there's a lot of heat in MASH, which really helps us with our process there. All right. Final question, Keith. Your top priorities for, let's say, the next six to eight months.

54:08move things into the clinic, move things forward. And then, you know, what I'm really interested in too is expanding the use of this technology. I think we've really established a way to do almost like an industrialized way to do target identification and then move things forward. Finding the best indications to do that in next. You know, we've got a really well-established liver model, moving it into additional liver diseases, rare liver diseases. Primary sclerosing cholangitis is really attractive. Things like that, where I think there's brick walls in front of the industry that we can break through.

54:46IPF, you know, doing more in IPF. Vizient has established an IPF model as well. And then, you know, at VivoSim, we're basically at the tipping point for, you know, really fast growth with this in the liver tox services, as well as we repurposed. So you mentioned earlier, we sold that Crohn's disease drug to Eli Lilly. We repurposed the intestine then into VivoSim as a way to predict diarrhea for drugs. So that's helping in antibody drug conjugate development, other oncology drug development, where, you know, really things are often dosed until they cause diarrhea as one of the primary side effects.

55:29And we can help people dial that out. And that's really attractive. So growing, growing the impact of those technologies for other companies through VivaSim is really big this year, too.

55:39Keith Murphy: Well, it's been it's been really fun and educational speaking with you, Keith. Thanks so much for coming on the show. Thanks a lot, Ben. Really enjoyed the conversation and dialogue. Thank you. We've been speaking with Keith Murphy, founder and CEO at Vizient Biosciences and executive chairman at Vivo Sims Labs. Vivo Sims Labs. I'm going to never get that right, I guess. I'm Ben Comer, and you've just listened to The Business of Biotech. Find us and subscribe anywhere you listen to podcasts. And be sure to check out our weekly videocast of these conversations every Monday under the Business of Biotech tab at lifescienceleader.com.

56:14Keith Murphy: We'll see you next week. And thanks, as always, for listening. Yeah.