Latest / BioSpace / Beyond Buzzwords in Longevity Investing
Transcript
- BioSpace: My name is Jennifer Smith Parker, Director of Insights at Biospace, and you're listening to Denatured. In this episode, I'll be speaking with Sergey Yakimov, Managing Partner, Alongevicy, and Artem Trotsiuk, Operating Partner, U.S., Alongevicy. We discuss how longevity has staying power in drug development if developers stop chasing aging as an abstract target and concentrate on mechanisms underlying specific age-related diseases. our time and hi, Sergey. Thank you so much for joining this episode of Denatured. If you can please introduce yourselves, that would be wonderful. Sure, absolutely. can kick this off. So I'm Sergey, one of the managing partners, one of the co-founders for Longevity 2.1, now Longevity 2.0 as well, as we have moved into our second fund, as well as several other ventures and incentives that we have built in this space, including, for example, Longevity Science Foundation or non-profits, funds early stage, agent research, and the like. Artyom? Hi folks, Artyom Trotsky, one of the partners of the fund. My domain expertise is pretty science heavy. joined the fund about three years ago and lead the deals team. right. So let's go ahead. So you've described longevity as a pragmatic longevity investor. So what does that actually mean when you're deciding whether to back a company and how different is that from a classic biotech fund that's looking at the same deal? Artyom, I'll actually, I'll actually, as you start on this, I feel like you have things to say. I was going to say you should kick that one off, but all right, sounds good. Not a problem. So I think that we were in longevity before longevity was a trend. That's like how I would describe it. And the way we view longevity is how can you improve someone's healthspan and lifespan as they get older? And how do we think about aging as a area of disease indication? Because aging is not classified as a disease. How do we... help someone live healthier longer with a good quality of life at the end. And that comes in the form of therapeutic and non-therapeutic interventions, tools, diagnostics, measurements, ways in which we can capture the breadth of what it means to be healthy and age well. And so that was the thesis of the fund when the fund was started. And when I joined, like we're really trying, we're building that out. as practical, pragmatic investing in science, longevity science, that it has to still go through the same hurdle, same FDA regulatory path as every other biotech company. I think, I think actually this is where I asked Thornton to start it off. I think he did it pretty well. Look, back in the days when longevity one was started, so longevity one is vintage 2021, right? We saw, it was this interesting moment in the industry where On the one hand, the longevity space and kind of the aging research and the notion that you should invest in aging research. did somewhat spin out of traditional farmer driven biotech. So you were already talking about two slightly different, maybe ideological trajectories, although kind of going after the same thing, but in a slightly different way. But ⁓ it was still very unfocused and we saw a lot of capital being wasted in investing in fighting aging. Right. So the very early. investments in the longevity space were, and a lot of times money down the drain. And that's because the research was inherently bad, but because it was research. It was very early. was, was fundamental science. It was not focused. It was not ready to speak the FDA language, let alone, you know, proceed to clinical trials with a, with a feasible disease indication. Right. So, so when we started indeed, I mean, we went after atrial diseases, ⁓ as Artum already said, right. We went after measurable endpoints and we kind of view the notion of arriving at a longevity drug, if you wish, not as this hypothetical concept of arriving at a longevity pill that someone consumes a little longer, healthier and rewards the biological age, but rather understanding what are the underlying mechanisms behind age-related diseases and hopefully also finding that there are mechanisms that are present in several age-related disease categories, right? So once you... Once you essentially figure out how to act on that mechanism, you will widen the patient population that you were affecting pretty severely. And this is where you improve health span. Right. And that's, that's ultimately longevity for us. We're also problematic in a way that if we stay clear of hype, we're not really into nutraceuticals. We're not really into anything you would see in the TikTok health advice feed. Not something that, you know, your average health. influencer would push, et cetera. Because ⁓ I'm not saying it's inherently bad. I some of these things are bizarre, right? Some of these things are borderline useless, yet safe. The issue is they're not data backed, right? And we're all about data. And I think that the team that Artum has built out has ⁓ scientific due diligence as a top priority, right? And this is how we designed the fund from the very beginning. this is where the pragmatic component comes from. And we get it. Placebo is a strong drug. The placebo effect is real. But then Well, how does that translate into actual product? How does that translate into revenue generation? So very much aligned with the pragmatic approach here. Both of you make such an important point. And I know, Sergey, when we had our initial conversation, you talked about how regulators, payers, inevitably still think about disease by disease terms, that type of a typical clinical trial paradigm that we have. But our longevity, the overarching view is talked about healthspan. So what does a realistic regulatory and commercialization path look like today for a startup that markets itself as longevity or going into the longevity space? It's trick question. It is a trick question because FDA is there to stay. I mean, several variables that you cannot really change, right? FDA is there to stay. Data-driven approach and endpoint-driven approach for preclinical I &D enabling and then clinical trials is there to stay. It is also there to ensure safety. for patients. It is also there to ensure that you are actually affecting something very specific that is measurable in a preclinical and then in a clinical setting. So there to enable phase four studies afterwards, post approval observation and the like. So all of these processes are there not necessarily to be disrupted because you need them. Essentially, at least for now, you need them. I'm not prepared to speculate what's going to be what is going to be like in 20 years time, but for now we need them. So that's kind of point number one. Number two, I think the realistic, not romanticized path for a longevity, quote unquote, company as of now is still going after a specific disease target. Being able to demonstrate a very specific piece of Asian biology or a mechanism of action that they are exploiting to ⁓ go after a specific disease indication. in preclinical, then IND enabling, then clinical. Although I do hate the debate of longevity, people saying, we're not traditional biotech, and then traditional biotech saying, like, what is even the difference between you and us? Fundamentally, if you are trying to go after novel biology, that comes primarily from the aging research, you are absolutely, we're like all hands for it. But the reality of it is the mechanism of you proving your thing works would be essentially similar to your traditional whatever. drug that Novartis is putting through clinical trials in oncology, for example, right, which will be considered traditional biotech. That'll be my take. Artof, what do you think? I agree to add to what Sergey talks about the payers, the eventual say a drug is approved, eventual payers want some outcomes data. So any concoct longevity company needs to think about how they're stacking their evidence strategies earlier on. Obesity was not an indication. GLPs made it an indication. So maybe in the future, health span or aging will be an end point that could be measured. But because it's so variable for every individual, what is defined as you age, what changes, ⁓ I can't attribute a timeline for that. whatever indication in the aging biology someone goes after, there's a mechanistic side. There's, and then the targeted scientific rigor that is, you're required to just prove that what you're saying is what, what the science that you're saying is actually going to work. And then. You got to prove to the regulators who have systems that are in place since way back when, to go through the check marks to show that you can, your, your, your claims are valid and unsafe for people to use things like midformance, analytics, all these aging related buzzwords or longevity buzzwords still need to go through outcomes, prove that that works real world, real world evidence. And it is very often a blessing and a curse at the same time, Because a lot of fundamental pieces in aging biology, tend to have much, much, much broader claims than your traditional kind of mechanisms of action from again, quote unquote, traditional biotech, right? If you take whatever, take senescent cells, which are arguably, you know, participating in a lot of aging-related and deterioration-related processes in the body, right? or telomere, any part of the telomere science out there. And that's a blessing because ultimately if you eventually prove that it works and it has a place under the sun, then you are claiming potentially systemic benefits for patients. The curse is understanding what is the area I'm gonna prove it in, right? Because just making things better is not an endpoint. So that's... This is where a lot of longevity companies were originally stuck. We see them now kind of getting out of that ditch and essentially understanding that FDA is just there to stay. So there is certainly an improvement if you stack it against, let's say, 2021, 2022. Yeah, you make an interesting point, too, going with GLPs. I remember that's something we discussed earlier on about how their first real longevity drug there. So I'm just curious from the GLP standpoint, just to talk about that a bit more, what has that taught you about how future longevity therapies will actually reach patients and fit into pharma's business model? It definitely sounds a bit going along what you said about the endpoints and that traditional aspect and very specific timelines and readouts. Yeah, so can get going off. Their mechanism, so they dialed in on a mechanism earlier on and kind of what is that receptor pathway outcome? if we think about it in the longevity drug space, we can't say like we're targeting aging because that's not a mechanism. So there was a little bit more thought about what the biology was. Now the indication agnostic feature, it could be that that is a way in which they were thinking about scaling the product. So I think Gozephic started. as a diabetes stroke and now it's for obesity, now cardiovascular, kidney, maybe Alzheimer's. And so that seems to me that because they see a market opportunity that the business model is trying to expand, especially since the patent cliff, think for the initial GLPs or the patent for the initial GLP is about to expire. thinking about other indications and by way of some modification that could lead to a new revenue stream. ⁓ So, ⁓ but so I'd start there. Interestingly with the GOPs, they've pulled in a lot of oxygen and capital towards this area of metabolic diseases. And so the question is, is that the right area specifically to be deploying all that capital or is still other and other methods by which we can treat cardiovascular, kidney or maybe Alzheimer's or any brain related things can be possibly been more beneficial, but because of the huge market adoption. And the volume of money associated, I there's many reasons why a lot of investors are excited about this. I the chairman of that real quick. So with your visa, think it's a perfect example of something that started off as a very specific disease indication drug. then along the way proved to be having more systemic or wider health benefits for a wider potential patient population or even kind of semi healthy, you know, population, right? People that are not necessarily diagnosed with something yet or about to be diagnosed. So that's one. Second, I always have to struggle with kind of what does the pharma understand and what does the pharma not understand type of discussion because the reality of it is I think big pharma is, I mean, They are smart enough. These are smart people. And in order to understand how they think, you need to understand the nature of their business. And the nature of the business of Big Pharma is distribution of drugs on a very, very, very large scale and access to markets and access to patient communities and access to healthcare providers. essentially all these sales channels that a small bio segment is developing something will never ever reach in its lifetime. Right. So, and this is why pharma is acquiring a lot of IP because by the nature of the organizations, it's sometimes too big, too clumsy to move fast. And this is why the innovation is better happening elsewhere, at least the early innovation. And then they can take it, take it from someone else's hands, right. And then kind of push it towards the finish line with a bigger budget. then the distribution, because the distribution is a huge part of a commercial success of any drug. So in order to enable this distribution engine to actually make you money, you need something very specific with a very specific disease indication to distribute. You need a specific good to be sold. That's it. That's all there is. So the example with GOP is just an example of what the longevity companies should do from our previous question, like five minutes ago. And that is prove themselves in something very specific and then claim a wider health benefit once you've proved yourself elsewhere. And this is how you expand. Because now you have the ground that you've built with these initial sales, with these initial kind of distribution channels. And this is how you get Big Pharma interested. Because then, as a huge distribution business, they understand what to do with it. Because there is a specific good to sell. So yeah, think GOP, you can call it the first longevity drug, can call it a drug that simply lowers a lot of it. It has a ton of side effects as well, in all fairness. Some studies recently have indicated the osteoporosis. The risks, example, you know, together with the previously known sarcopedia and all the asmic face and whatever risks. ⁓ But it does have wider health benefits, like cardiovascular risk reduction, etc. So it's just a good posture child that we have as of now. I'm not saying it's perfect. It's just a good case. Yeah, I think that makes a lot of sense. I love the idea of putting this as a posture trial with caveats, right? With what we talked about withers. side effects and other things. I'm hearing again and again how important it is to have data behind everything that you're doing and not just a theory, not just an idea about longevity here. So I'm curious when a founder pitches you in a longevity, let's say startup, so what are the top one or two towels, let's say in the first five minutes, that you say this could be fun backable and not just a great science project? All right, so this is for you to start with. So even before we take a call for them to pitch, they'll send us the pre-reading material. People sometimes underestimate the importance of having your pitch check dialed into the story you're trying to communicate. And after not going with the hype of what the current trend is and then sticking all those keyword hypes in there, very often we've seen thousands of companies across the last couple of years. And I could tell you the ones that stand out, the pitch check is the first part in which we kind of screen through to determine. If we're going to continue that conversation or not, they'll start with the theme area and that theme area, then we'll be able to, we will then say cardiovascular. I'll give it as a direct example. Someone's interested in cardiovascular and then they'll present their pitch on some new cardiovascular indication. We have the knowledge of seeing other, like we've seen other companies in the same space. And so we'll start thinking about how is it that their approach is the same and or different or unique. as compared to what has already currently been tried. Are they trying the same technology from 20 years ago and saying it's new and novel? Where actually it's not. Or have they been around for the last 10 years and it hasn't really progressed forward? So there's a lot of filtering and thinking that goes in, but to think of, to assess their indication before drilling in on the science. the initial screen also will review the data, whatever data they want to present. That does help inform. I think the data component comes more in... to conversation when we'll go into diligence. When we'll ask for a, I'd like to see some of your papers or publish or unpublish. Perhaps you have some reports that you were in internally. Perhaps you have other stakeholders. Perhaps you have some explanation on the mechanism of actions. Then we'll prod that a little bit further to test those hypotheses to say, Hey, we think that this does some, this could be a risk or this doesn't make sense or other people have tried this. mechanism from a different angle. How does your approach stack against those? Why is yours better? And at every single part, especially these science heavy companies require a certain amount of demonstration of feasibility. When they're super early in concept, there's a little bit more wiggle room because it is the conceptual framing. When you're further down into like a series A, going into series B, and if you don't have much to justify your hypotheses, even cell studies in vitro large animal models, then the question is whether or not what you're proposing is going to actually transition into being successful in phase one. But the thing that's super important with all these biologics is, there a drug product? There's oftentimes we see a lot of companies that come in and say, we can generate a bunch of hits. We can generate a bunch of targets. We can generate a bunch of molecules. That doesn't matter because then day you gotta have a drug product that comes from all this. I it was a talk where the head of AI for Eli Lilly was talking and saying, we a gazillion, we have a ton of AI models that in-house that we could turn on just like with a snap of a finger and just generate a bunch of hits or a bunch of targets. It doesn't really matter for us. You can generate us lists. We can use those. can do that ourselves as well. It does not matter. What matters for us is If there is something that you have on the data defensibility or can you speed up our processes? Can you get us to faster production timelines or can you get us to the point where we can get into clinic faster? What can you do to help us essentially get to the end point of making an extra dollar faster? I'll pause there, see if Surya has any additional comments there, but that's kind of how I would start bringing it. mean, absence of wishful thinking. Top one, top one, the only one. Seriously, no. It's a it's a like voluminous term, to be completely honest. Like it's a very voluminous factor. And what goes into it is what Artem was talking about essentially, right? But it's also the realistic perception of the team of what it's going to take to actually build whatever they're trying to build. think biotech is in a way, I mean, it's one of the most difficult. industries to invest in period. So you need to be an absolute optimist to invest in a really stage prior to Zerg. But then I think one of the few perks that we get, very few, is that ⁓ you rarely get absolutely random people as founders. So they're usually educated, field trained. individuals very often with previous exits or previous pharma background or you you essentially get people from the space building in the space. So it all comes down to how realistic are they about where they are, where they're going to be, their ability to estimate their timelines, their ability to estimate their regulatory hurdles, their ability to be realistic about business development, the way how the team thinks about business development to begin with, right? So... where if you see a team which says, well, now we're kind of, don't want to talk to the industry yet because we're going to talk with the industry in a year and it's going to be fast. That is something you would probably notice knowing that the industry takes a year, year and a half to do the deal with you very often. It doesn't move that fast. Things like that. Same applies, same wishful thinking factor applies to data. Are they trying to see something in the data that is not necessarily there? And I think, you know, a lot of what Artom and his team does is ⁓ essentially cross validating a lot of things that we see with either our scientific advisory board or the external network of KOLs we have. Because that it is a mandate of the fund not to invest in a deal unless we have obtained multiple positive opinions from these unbiased experts out there. So for me, it's the wishful thinking basket, which then expands quite a bit if you try to break it down to specific components. Well, thank you, Artem, and thank you so much, Sergey, for joining this episode of Denatured. Very insightful comments. 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