Finding New Opportunities In Obesity With Moonwalk Bioscience's Alex Aravanis, M.D., Ph.D.

0:04Alex Aravanis, M.D., Ph.D.: 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 Alex Aravanis, M.D., Ph.D., CEO at Moonwalk Biosciences, a company developing new therapies targeting adipose tissue or body fat that aim to improve upon currently available treatments for obesity, namely GLP-1s, using siRNAs, and biopsy. therapies. Alex was previously a co-founder and the head of R &D at Grail. He was chief technology officer at Illumina and also worked as VP of development and chief science officer at Sapphire, a company that made crude oil out of algae.

0:46Alex Aravanis, M.D., Ph.D.: I'm going to ask you about that, Alex. Now he's in his first biotech CEO job, and I'm excited to talk to him about the opportunities in obesity and why GLP-1s aren't the be-all end-all products in this space. Moonwalk just closed and oversubscribed $70 million Series B to move into the clinic. We'll also talk about licensing technology from China and why short interfering RNA is a compelling mechanism for cardiometabolic disease. Alex, thanks for coming on the show. I appreciate it. Yeah, it's my pleasure to be here, Ben. But I as we do, I wanted to start off with a little bit on your background, Alex.

1:26Alex Aravanis, M.D., Ph.D.: You earned a Ph.D. in electrical engineering from Stanford and an M.D. at the same time. Is that right? Yeah, I was in school for a while. That's true. Yeah. Did you have a specific career aspirations at that point? Like you were you thinking about how you could meld electrical engineering, you know, with with an M.D.? Or how did you, I guess, come to that decision to pursue both of those at the same time? It sounds like a pretty rigorous course load. Yeah.

2:02So, yeah, so I was trained as an engineer, did that as an undergrad, and, you know, liked studying all the different techniques. And it's a great background. Engineering teaches you how to build things, electrical engineering, how to analyze things. So it was a great training. What I found during my early graduate work at Stanford was that I was very interested in problems in medicine and biotech. And so over time, I wanted to see how I could use my engineering skill set and apply it to those types of problems. And Stanford was a great place to do that. The engineering schools across the street from the medical school, very flexible about having different kinds of advisors and so on.

2:46So, yeah, so eventually I spent most of my time at the medical school, you know, applying techniques in machine learning or, you know, digital signal processing devices, things like that to some really interesting basic science and medical applications.

3:07Alex Aravanis, M.D., Ph.D.: Was there a specific field of medicine that you were, you know, I guess, initially focused on or just interested in? Yeah, definitely neuroscience. So as an electrical engineer, I was always fascinated about the analogous wetware computing device in humans and in animals and how that related to all the different computational techniques and circuit design techniques that I learned as an electrical engineer. Obviously very different, but that's where I started in life sciences and medicine. OK. And then I mentioned in the intro, you were a co-founder at Grail, the diagnostic company developer of the Galleria early cancer detection test.

3:54Alex Aravanis, M.D., Ph.D.: Grail was originally spun out from Illumina, then fully acquired by Illumina, I think for seven billion dollars or seven point one billion in 2021 and then divested by Illumina based on an antitrust ruling. This was during the Lena Kahn tenure at the FTC. That must have been a pretty wild ride. Do you care to add any color to that journey? Yeah, I mean, a little bit. I'm not going to comment on any of the legality or business aspects, but, you know, at Grail, we were passionate about could we bend the cancer curve? You know, most people who die from cancers die from cancers where there is no screening test.

4:39So they just find it, you know, it's found incidentally or symptomatic. We wanted to see if we could do something about it. And we felt that sequencing technology with large data sets, you know, there was potential to develop a kind of a universal test for cancer. And ultimately, we were able to do that and show that it works quite well in clinical studies. And, you know, now there's a lot of people benefiting from it and it's commercial. You know, the companies thought being one company was a compelling case for being able to bring the test to more people, more parts of the world. And unfortunately, you know, certain government agencies disagreed with that.

5:25And, you know, I didn't share their opinion and they caused a lot of heartache for the companies. But ultimately, they're both doing well now and people are benefiting from it.

5:37Alex Aravanis, M.D., Ph.D.: And did you work directly on the Galleria test? Yeah. So I'm the scientific founder of Grail. I led the R &D, the clinical development, was an officer at the company. And yeah, it was a huge team effort. But yeah, one of the inventors of the gallery test. I mentioned Sapphire. I had not heard of this company until I knew I was going to speak with you, Alex. And I looked it up and it was fascinating. Algae-based crude oil. How did you get involved with that? And how close were you to succeeding? Yeah. Yeah. So that goes way back. So part of the theme of how I developed my career, which is I'm always interested in, you know, new technologies that could have a big impact on important problems and working with, you know, incredible people.

6:31And so at that time, it was early days in synthetic biology. So the idea of using, you know, manipulating biological in a way much more akin to engineering to build molecules and create systems that could produce, you know, certain chemical structures, things like that. There are a lot of different applications in medicine and in industry. So I got involved with that group. It's a fantastic group of also investors, Arch Ventures and others who I've worked with now for almost two decades. And we built a great platform. The microorganism we were using as algae has a lot of benefits. One of the biggest, obviously, is that it can, you know, use sunlight and carbon dioxide as it's to make to make matter.

7:24Over time, you know, the opportunity to do something and energy emerged and the company decided to make that a big thrust of it. So that wasn't, you know, so like a lot of companies, you know, you join, you're building it out and then, you know, as opportunities arise, you pursue them. And so I don't think I ever saw myself, you know, a priori getting involved in an energy company, but that's what made sense ultimately. And so we developed for that purpose. We had some really great demonstrations. You know, ultimately, you know, the economics of the energy business require very low cost of production.

8:03And, you know, ultimately that was challenging. Yeah.

8:07Alex Aravanis, M.D., Ph.D.: Do you think there's still an opportunity to make that a reality? I mean, an alternative to oil, I mean, that that in and itself is pretty compelling. Yeah, I do. And if I think if oil was consistently like two or three hundred dollars a barrel, it would be very compelling. But, you know, oil goes up and down. But when it gets to 40, 50 dollars, that that's very hard to compete with. So I think that, you know, obviously there's many reasons we don't want energy to be expensive. But if eventually it becomes unsustainably expensive, then, yeah, I think some of these alternatives will become viable.

8:51Alex Aravanis, M.D., Ph.D.: Yeah. You're a first time biotech CEO. I mentioned that in the intro as well. You're working in a red hot therapeutic area where you have some formidable competitors in Eli Lilly and Nova Nordisk. What what made you, Alex, want to tackle obesity with an siRNA therapy? Yeah. Yeah. So maybe I should say a little bit about the background of Moonwalk. Right. So sure. So myself and my co-founders of the company, one of which is Feng Zhang, who's at the Broad and Harvard and MIT and famous for his genome editing and CRISPR technologies and companies, was that we could develop a drug discovery platform that could find novel targets that hadn't been appreciated.

9:43So new targets within the genome or epigenome, where if we could modify them, we could change disease processes. And we had a great background in it. We do. So as the head of global R &D and CTO to Illumina had developed a lot of the genomics, epigenomics, transcriptomics technologies that generate vast majority of the world's data. And we learned how to process it and use it for things like diagnostics, which is what Grail does, but also for drug discovery. And we felt like, you know, with the right team and a focus on this, we could potentially add something unique to drug discovery. And so that's what we founded the company.

10:25We also had the Fung's genome perturbation technologies. So we could analyze the genome, the epigenome of unique samples of people, of animals, look for differences between individuals, for example, who are obese or non-obese, and then test them with these perturbation technologies. So we set up the platform. We looked at a lot of different areas we could contribute. One that was very fruitful quickly was adipose or fat cells, you know, and started to identify, you know, novel targets, novel genes and the evidence. when we were deeper in it, really supported those as exciting targets. And so then the question is, now that we have these really interesting targets, well, how do we so-called drug them, right?

11:15How do we, you know, effectively and safely suppress the genes and ideally only do it in the adipose cells and not other places? And that's where the recent innovations in sRNA, small inhibitory RNA technologies were a really good match, right? So, historically, these molecules were mostly used for what's called liver targets, so suppressing genes in the liver, but new inventions on the chemistry allowed them to get taken into other tissues, including adipose. And so, we evaluated some of those platforms, ultimately picked who we thought was amongst the best at doing this and then license those chemistries to use for our targets.

12:01And then the combination of that we think are very compelling therapies.

12:08Alex Aravanis, M.D., Ph.D.: You licensed the technology from Suze House Saran Biotechnology Company. Is that right? Yeah. Yeah. And it was specifically an adipose targeting. How would you describe, I guess, the technology that you actually licensed in? Yeah. Yeah. So as I mentioned, we have these genes that we thought were very good targets that if we could knock what's called knock them down, meaning suppress their expression in adipose, there would be potential benefits, including reduction in adipose mass, reduction in lipids, triglycerides, cholesterol, other things. And so the question is how to do that. and sRNAs are a great way to suppress a gene, right?

12:54But we need to get a way to get them into the adipose cells. And what Siren had invented is if you put these extra molecules on the sRNA molecule, they then had the ability to be taken up by adipose cells. So, there's a lot of complexity in that, but that's the gist of it. And so, we made sRNAs against our targets, so the sequences that would suppress the genes of interest, and then we added their modifications. And by doing that, we were able indeed to suppress these genes in animal models, and that led to some really exciting results showing that in obese animals, we could get weight loss and other benefits.

13:36And then with that success, we then made human versions of these, which, you know, we're now preparing to test in the clinic next year.

13:45Alex Aravanis, M.D., Ph.D.: Okay, got it. So, you were licensing the technology as opposed to a drug candidate. That's right. So, yeah. So, there's a lot, I'm sure you know, and some of your other guests who have licensed preclinical or clinical stage assets. We licensed the platform or chemistry that we then added to the sequences that we were designing against our novel targets. Yeah. And I imagine that maybe, I don't know, maybe not makes the actual in-licensing process a little easier. I mean, I don't have to tell you there's a lot of focus right now on U.S. companies licensing things. Typically, it's more focused on, you know, the clinical data and an act, you know, an active clinical product that's coming into the U.S.

14:35Alex Aravanis, M.D., Ph.D.: to be further developed as opposed to a straight technology like you've described. But were there, I guess I'm just curious if there were any kind of surprises that you ran into or did it go, you know, pretty easily, you know, in doing the in-licensing process with Ceron? Yeah, we've had a great experience and they've been a great partner. Um, the, the founders, uh, and, and executives of the company, um, are, you know, are, are they great training and work experience in the West. Um, so, uh, really familiar with, um, uh, kind of the, you know, how we're used to doing business, um, extremely credible and, and, um, high integrity folks.

15:22So, uh, that was really important to us. And then in the end of the day, you know, we did our homework, um, you know, kick the tires on the technology, evaluated it, you know, and everything suggested that, you know, yes, they're Chinese entity, but in the end, we wanted the best platform. We wanted to work with folks who we thought would help us collaborate through it. And it's played out really well. You know, there's always a tough business negotiation around the terms and so on, but sure, I don't think any different than than anyone else. So it's been nothing but a positive experience for us.

16:00Alex Aravanis, M.D., Ph.D.: How did you get to that short list of technology platforms that you were considering? You know, how did you just identify the ones that would be most relevant to Moonlock? Yeah, so we were looking for, you know, sRNAs that were adipose targeted. And so there aren't that many, probably less than 10. And then, you know, obviously the ones that are more advanced, meaning that they have some early clinical data and it's BNT risk, right? So that was a shorter list. So yeah, just, you know, you could count them on one hand. And then, you know, we looked a lot at, you know, their publications, presentations, you know, patents are always helpful to get a sense of where the technology is at.

16:48And then we met with the various groups and explored their interest in doing it. And then eventually that led us to deciding that Cirin was the right tech, you know, scientific and business partner for us.

17:02Alex Aravanis, M.D., Ph.D.: Got it. Okay. I want to ask a little bit about obesity and currently available treatments. I noticed the the Moonwalk website mentions a non non appetite suppressing mechanism. And, you know, that made me wonder if it's if it's possible. I assume that your hypothesis is that it is possible to lose weight, you know, in comparison to GLP ones, I guess, without, you know, appetite suppression. Yeah. So I think that maybe just start with some some of the science here. Right. So, you know, we all appreciate that there's a there's a diversity in and people's propensity to gain weight. Right. Relative to the right.

17:48There's always those folks who maybe I'm towards this, which is they tend to be able to eat a lot and not gain a lot of weight. And then there's. Yeah, those lucky people. Right. Yeah. Right. And so, well, what's the difference? Right. Well, you know, it's probably a few things, but one of them is they do have different genetics. Right. And we know that there are genes where, you know, that that can kind of tip the the balance of homeostasis one way or the other. Right. So our lead target, for example, is a gene like that where we discover that folks that have one or more copies of this gene that don't work well, which we call loss of function, they tend to be a lot thinner.

18:33Right. And so, you know, and they're healthy. They just tend to be thinner. And so what we think is going on is that, you know, there's a balance when you take in food or energy between storing it and using it. Right. And these folks are just skewed a bit more towards the usage and removal of it. Right. So at a high the highest level, what we're trying to do is give that benefit that those folks have to to anyone who would need it. Right. And this is where the use of human genetics is really is really useful and important. Right. Because in some ways you have kind of a proof point or natural experiment.

19:14Right. Which is that there are people walking around who kind of already have the treatment and they have the benefit. We don't know 100 percent that that link is there because it's it's an association, but it's very strong. And so that gives us confidence that, gosh, if you can kind of mimic that, then perhaps you could get the benefit. And then in on in addition to that, we looked at the epigenetics. So which is not the coding sequence, but how it's controlled through other kind of chemical modifications that work on the DNA, but are not the actual changes in the sequence. And again, there we saw differences that were pretty significant between in adipose samples or fat samples from between people who are obese and non-obese.

19:59And again, many of these overlaps with with our genetic studies. So suggesting, gosh, this gene, when it's suppressed and when it's or, you know, not functioning well, there's this huge protective effect. This would be really compelling to test as a therapeutic target.

20:19Alex Aravanis, M.D., Ph.D.: When you're describing, you know, different people metabolizing, I guess that would be the correct word. Correct, you know, correct me if I'm wrong. I'm just thinking of, you know, the person who can eat a lot and not gain weight versus the person who maybe eats the same amount and does gain weight was always think of being characterized as, you know, a faster metabolism or, you know, this person, they just have a really fast metabolism. So my question is, A, is that correct, like a correct characterization? And B, is your treatment impacting that rate of metabolism at all? How does that work?

20:58Yeah, I think in a very general way.

21:27Um, uh, you know, you can also exercise. That's another way to consume things faster. Um, it's, it's kind of hard to do that enough to really overcome, uh, eating a lot, but, um, that'd be another way to do that. And so, yes, uh, at a, at a very crude level, we are, as I said, kind of tipping the balance more towards, um, utilization of the lipids or, or, or fats versus storing them.

21:52Alex Aravanis, M.D., Ph.D.: Okay. And then thinking about Moon, you haven't got, you're planning to take your initial development candidate, I believe, into the clinic by the end of 2027. Is that right? That's right. For that initial candidate, how would you characterize the patient population that you plan to target? Yeah. So this will be our phase one study. So the most important thing in the phase one studies, you know, is to establish safety, right? So, we'll be doing, you know, initial studies starting at low doses, going to higher doses, very carefully monitoring, you know, for any potential, you know, safety issues or toxicity.

22:36Our preclinical studies in animals suggest, you know, or not suggest, demonstrate that it's quite safe, but we need to show that in a very careful study in humans. Once we get through that, then we are interested in starting to look at efficacy in a relevant patient population. And so, and that will start to move towards individuals who, for example, have a high BMI, right? And there's a whole range from moderately high to extremely high and disabling BMIs. And so, we're thinking about which of those groups to evaluate it in first. There's also related conditions, type 2 diabetes,

23:23hyperlipidemia groups that have difficulty controlling high cholesterol, things like that. So, these are all populations that could potentially benefit from this therapy. And And over a series of studies, you know, assuming things continue to be safe, we want to understand what the potential benefit is. Yeah. Yeah.

23:45Alex Aravanis, M.D., Ph.D.: I want to ask you in just a second about the 70 million dollar series B oversubscribed series B that you just just finished. But I before I do, I'm curious about how, you know, maybe your read on how investors think about the rate of weight loss. So do you do you feel like your product will have to, you know, take off a certain number of pounds and, you know, something sort of equal to what the available therapies do? Or is that is that less important, you know, when you can say preserve lean muscle mass or, you know, treat patients without some of the gastrointestinal side effects that that come along with the GLPs?

24:30Alex Aravanis, M.D., Ph.D.: How are you thinking about that? How are investors thinking about that? Yeah. Look, we want to contribute something that addresses significant unmet need and also can be used in a complementary way with existing therapies. You know, you could think of this as early days in lipid treatment or diabetes or high blood pressure where, you know, you don't have one agent that works on everyone and solves all problems, right? You want multiple agents, different mechanisms that, you know, for different patients who they either respond or don't respond or need a combination of things. So we have an incredible initial class, right, GLP-1s and the related targets.

25:18You know, really unbelievable how effective those are. That said, not everyone is benefiting and there are some challenges, right? So, you know, you hear these really impressive numbers, 15, 20, 25 percent. Those are averages. There's a distribution. There's a sizable fraction, a quarterish of people who lose less than 5 percent or don't get any. There's even some who gain weight, right? So a large fraction of people benefit, but there is a meaningful fraction, a quarter, maybe to a third, depending on the agent in the study, who are not benefiting. So we want to be able to help those individuals.

26:04Also, if a typical patient might be starting one of these medications in their late 40s, early 50s, and they want to be able to manage their weight for the next several decades, right? Right. When you look at, you know, how long people stay on average on these medications, you know, it's something like a half within two years, more than half the people are off them. And so, you know, why is that? There's different reasons. One of them is the is the side effects. Right. So for some people and it varies. Right. Some people, they don't have any issues. Some they have, you know, very significant GI issues, nausea, vomiting, diarrhea.

26:49And so that's a challenge. And then you mentioned the muscle preservation, which is that because, you know, people aren't eating, you know, for a couple different reasons. But one is they're just not taking enough protein and they tend to lose a quarter to a third of that weight is lean mass. Right. And so that's not how you want to lose weight. You want to lose fat mass, ideally, and no lean mass. And so those are all a consequence of the fact that it's the fundamental mechanism is its appetite suppression. Right. It essentially makes you realize. effective at dieting. Um, right. Yeah. Right.

27:24Is, is, is, is, is how it works. Um, uh, and so again, you know, I, I think, you know, uh, needless to say, these are incredible drugs and the side effects, I mean, um, while they can be limiting or actually, you know, in general, pretty benign, but, but ultimately, you know, having other mechanisms that don't work on appetite that can help people who don't respond, can't tolerate the side effects, you know, who are concerned about the muscle loss. You know, it's well recognized. That's a big opportunity by the companies that make those existing medications and by investors and by some of our advisors who run obesity clinics helping patients.

28:15So, yeah, we just there's no doubt that there's an opportunity if you can address those other features. And then, you know, obviously, the more way you can lose all things be equal, the better. But you don't if you have these other features, these are very attractive without this. You don't need to you don't need to exceed or surpass the top line weight loss numbers. It's really if you can get meaningful weight loss, you know, and without losing your muscle, without suppressing appetite, without having nausea, vomiting. And by the way, we didn't talk about infrequent dosing. You know, our therapies, because they're long acting SRNAs, we see activity up to six months.

28:59So the potential for quarterly or once every or twice a year dosing is possible. So that's really attractive, too, because it makes it very easy to stay on the medication. You don't have to do injections every week. You don't pick a pill every day. You don't have to, you know, potentially forget to do that. Yeah. So we're excited to see, you know, if if if we can see these benefits in the clinic and the safety profile.

29:27Alex Aravanis, M.D., Ph.D.: Yeah, I like what you said about, you know, the early days of the lipid lowering therapies. And it sounds like, you know, what you're saying is that semaglutide and terzepatide are not Lipitor and Crestor. Like, there's some room to get up to that point, right? Is that what you're saying? Well, in some ways, they are. But then now we have a variety of other agents too, right? Like, we have PCSK9 inhibitors and other things, right? And so, because there are folks where, you know, the statins, you know, they're not getting their cholesterol low enough. They still have risk. you know and there's several other you know new targets that for lipid lowering that are also in develop right development so that was the analogy more it was going for yeah okay yeah so all right so yeah the lipid lipid lowering yeah we might get a a gene editing pcsk9 therapy in a few years that would be a one and done cholesterol treatment so okay I take your point I did want to ask about the Series B.

30:34Alex Aravanis, M.D., Ph.D.: Congratulations, first of all, oversubscribed$70 million Series B. Did you have experience with fundraising in your prior roles, Alex, or was this kind of your first swing in doing something like a Series B fundraising as a CEO? So quite a bit of experience, but never as a CEO. So as a head of R &D, CSO, CTO at multiple startup companies, I was often part of the team that was doing the fundraising. Sometimes, you know, it was often me and the CEO kind of doing the pitch and, you know, and talking with investors, running, you know, diligence activities. So a lot of experience with, you know, a lot of total funds raised.

31:25So, you know, without that, I think it would have been difficult. And then also through all those experiences, I also knew a really great investor community. Um, so yeah, so a lot of experience, but you know, it's different, uh, when you're the CEO.

31:42Alex Aravanis, M.D., Ph.D.: Yeah. Yeah. I would imagine. So, um, you got, you landed$70 million. Um, what, how, what will that do for you? Uh, what, you know, how are you going to deploy that, that 70 million? Um, and I, I guess when, when do you expect to, to have to fundraise again? Like what, what's the next milestone? Yeah, I mean, that's exactly how we think about it, which is the key value creating milestones. And the fundraising is about supporting that. So it's taking our lead program, MW101, into the clinic through robust phase 1A and B, maybe even a 2A, 1B, 2A. So to really demonstrate the initial safety and show potential efficacy signals.

32:28And then we have a second program that's close to being a development candidate. It would fund that one also. And this potentially even, you know, depending on what, you know, how these programs go, even of doing a third. So we'd like to do a minimum of two, you know, proof human proof of principle, first in humans for two programs and maybe a third with this. And so the key milestones we're looking for is, you know, a positive readout in the clinic. And with one or more of these, I think then, you know, it'll be quite compelling to then do another fundraising to fund later stage studies, advance more of the pipeline.

33:13And then we'll be looking at a variety of different financing options than both public and private.

33:19Alex Aravanis, M.D., Ph.D.: Right. OK. It's early days to ask this question, but I'm sure you've thought of it. So I'm curious to hear how how you might respond on bringing the products all the way to commercialization. Is it you know, have you is Moonwalk set up to potentially commercialize, you know, a therapy and obesity itself? would you by necessity have to partner, you know, to come and maybe you'd be differentiated and wouldn't necessarily be competing directly by the time you get to market with, you know, some of the GLP ones. But I guess, how do you how do you think about that? Is there, you know, a point where you'll need to partner or you'll be looking to do a deal or are you open to, you know, taking it all the way through commercialization and beyond as Moonwalk?

34:15Yes, a few things to say. So, you know, right now there's no kind of preconceived path that we have to do. The most common path just statistically would be to either license a program or be acquired, right? That would be the most common before you actually get to approval and commercialization. I don't know what statistics are, but I'm guessing it's like 80, 90 percent of the cases. So, you know, that's a likely scenario. But there are scenarios and companies do it today. I can think of a few where for a variety of reasons, it really makes sense for them to do the initial commercialization. And so if that's what it takes to create value to patients and investors, then, you know, open to doing that.

35:09The way I think about it is like, who's the kind of natural owner, right, and can advance the program right now? That's clearly us, right? We're the right ones to do the science. We're the right ones to do the phase one. We could well be the right ones to do phase two. I think as it gets farther along and there's organizations that are really good at complex, large clinical studies, multi-site global ones, and then are really good at the regulatory aspects and then ultimately how to bring it into the complex commercial phase, it could well be that someone else is really the natural owner and it's going to do better in their hands.

35:52Got it.

35:54Alex Aravanis, M.D., Ph.D.: All right. What about top priorities, Alex, for the rest of 2026? We've established you're aiming to get into the clinic before the end of next year. But what's what's top of mind for you right now? You know, what are the kind of key areas of execution that you're focused on for the rest of this year? Yeah, I mean, there's a few. I think the area that, you know, kind of obvious that we need to execute on and be really excellent is on the early stage clinical development, right? So, up until now, it's all been preclinical. So, you know, great biology, great science, you know, data that supported us and gotten us to this point, really good partnering and manufacturing around the RNA.

36:43But now we need to be really excellent at the early stage clinical development. And so, building that muscle, that team, so that, you know, we do that really skillfully and quickly is going to be key. And so, along in the announcement with the fundraising, we also announced that we brought in a very experienced, you know, clinical development lead, who's our head of clinical development, Stephen DeJeggio. So, Stephen was most recently at Kylara, which is a company, public company developing GLP-1. So he's really well-versed in these types of studies, a real pro. And so that supporting him, making that transition to a clinical stage company, building those capabilities is, you know, that's probably at his top priority.

37:34I would say next is moving our second and third programs along. We want multiple shots on goal. We think each of these is unique and has its own benefits and creates a deeper, richer pipeline. So that's going to be important too.

37:51Alex Aravanis, M.D., Ph.D.: Okay. Yeah. And I noticed you have several. How many preclinical assets have you established at this point? Yeah. So we have over a half dozen novel targets that we think are quite promising. As I mentioned, you know, at different stages, we have one that, again, we have our final development candidate. We're working to prepare for the clinic. We have a second that's pretty close to that. And then we have about another four that could support a third program and maybe even beyond that. Yeah. Okay. Well, I appreciate you coming on the show and taking the time to speak with me, Alex. Yeah, there's actually one other area Ben would want to touch on, if you don't mind.

38:36Alex Aravanis, M.D., Ph.D.: Yeah, please. Yeah, yeah. So we didn't talk about AI, and it's a little bit of a buzzword, but I do want to say that it has been more and more important to what we're doing. And so we have a great team who has experience using this technology for biological applications. And by taking our data from which of our novel targets worked, didn't work, all of our genetics data, all of our animal data, and looking at and taking that and layering it on top of one of the large frontier models, we started to get really interesting results. So, for example, you know, we have these hypotheses that, you know, for example, these half dozen targets are going to be promising and roughly halfish of them did work quite well, which is a pretty good hit rate.

39:28You know, we started with hundreds and the ones that we really tested in animal models. And then you can ask it really interesting questions. Well, why did this target reverse this other one didn't work right? and it gives you really interesting insights that help you think about how to prioritize them and which are most likely to translate in humans. And then the really exciting thing is it then starts to generate ideas. We'll say, look, well, if target A and B work, that suggests that this pathway is actually quite effective. And have you thought about this other, you know, target Z, right, that we hadn't thought about.

40:03And now that's starting to fill out even some additional candidates. And it's also starting to help us on the SR &E design. And so we're pretty excited, even as a small company, how this could help us accelerate, increase the likelihood of technical success and open our eyes to even some additional targets that we wouldn't have thought of otherwise.

40:30Alex Aravanis, M.D., Ph.D.: Yeah, I'm glad you brought that up. There's, you know, NVIDIA, I think in the last or at least this last six months or so has launched a new, you know, kind of life science focused agentic technology. I saw a presentation that they did just in the last few days. Anthropic, you know, there's been some news going around about them, you know, hiring someone in to evaluate deals and partnerships and things that they might want to get involved in in the life sciences. My question for you, Alex, is, you know, are you having to go out and evaluate, you know, new AI like every several months to make sure that, you know, you've got like the latest and greatest at the company?

41:18Alex Aravanis, M.D., Ph.D.: How do you, you know, how do you, I guess, decide what AI to use and then continuously, you know, improve that over time given the rate of change? Yeah, there's a tremendous amount going on and we're not a huge company. I'd say we have some folks who are really experienced with AI and machine learning tools. So we have a really good sense for what could be enabling and what's maybe perhaps just incremental or just a rebranding of something. So I don't think that everything that comes out is that distinguished, but there are some tools and there are some big leaps. And so we try to make kind of targeted investments when we really think there's something new with potential worth evaluating.

42:08And then, you know, we want to use it on a program that will move the needle for us, right? There's stuff that's kind of academic that's interesting that maybe we fall in the literature. But when it comes down to, gee, we have a really interesting target, but it's, say, challenging to find an effective sRNA against it. Well, that's a real problem that if we can solve it or accelerate it or not have to brute force it really has big benefit to us. So that's like a great problem.

42:40Or we've got four targets that seem to all have very promising data. is there any reason we should prioritize one versus the other? Right. So those types of applications are, you know, really meaningful to us. And we try to match it with the tools as they emerge that that we think are the most the most impressive.

43:03Alex Aravanis, M.D., Ph.D.: Yeah. I mean, has a lot I think of Grail and Illumina as as pretty high tech companies. But I'm curious, you know, were you when you were, you know, co-founding Grail and working on Galleria? Was there an AI component to that or was it completely, you know, not there yet? Were you guys using, you know, earlier versions? I assume, you know, you've watched this technology progress, you know, at least, you know, thinking about the life sciences with a kind of a clearer lens than at least I have or many people have. No, we actually made a big use of it at Grail. Back then we called it machine learning and there's a distinction between AI and machine learning.

43:49But yeah, we were using deep neural networks to look for complex association between changes in the methylation patterns in tumor DNA to distinguish real cancers versus, you know, background signals. And that worked incredibly well. Without those kinds of computational approaches, we wouldn't have been able to do that. And there's just when you have, you know, in some of our studies, we were using tens of thousands of samples with millions of CPG sites. There's just no way any human being can curate those or find subtle relationships the way that a machine learning tool or neural network can. So, no, it was incredibly enabling.

44:35And I think it's probably one of the first big applications in diagnostics of AI slash machine learning. So I'm big believers in it, in the technology, because I've seen it play out. At Illumina, we launched some of the first tools called Primate AI and Splice AI. And these allowed you to look at regions of the genome and make predictions about whether or not SNPs, so single nucleotide changes, were likely to be disease-causing or not. And sometimes these are novel, meaning it's a rare change and there's no lookup table or literature on it. And these tools could make really accurate predictions of whether or not this is just benign or, hey, this could actually be the single mutation that's responsible for this child's developmental disorder.

45:32So those are some really early pioneering examples of how these tools could use these large data sets and genomics is great for this purpose and, you know, make much more powerful use of the data than we ever could before.

45:48Alex Aravanis, M.D., Ph.D.: Right. Excellent. Well, I really appreciate you coming on the show, Alex. Thanks for thanks for taking the time. Yeah, my pleasure, Ben. Thank you. we've been speaking with Alex Erivanas MD PhD CEO at moonwalk biosciences I'm Ben Comer and you've just listened to the business of biotech find it find us and subscribe anywhere you listen to podcasts and be sure to check out our weekly video casts of these conversations every Monday under the business of biotech tab at life science leader.com we'll see you next week and thanks as always for listening

46:30We'll be right back.