156: Investing in the Business of Aging

In this episode, Dr. Karl Pfleger joins us to discuss the evolving landscape of longevity research and investment.

He emphasizes the shift from disease-specific approaches to understanding aging as a multifaceted process that underpins many chronic diseases.

Dr. Pfleger outlines his investment strategies in the aging biotech sector, highlighting the importance of addressing various sub-pathologies of aging.

He also discusses the concept of longevity escape velocity, the challenges of proving longevity therapies, and the role of aging clocks in research. 

Learn more about Dr. Karl Pfleger:

https://x.com/karlpfleger?lang=en

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Download Dr. Buck Joffrey's FREE ebook, Living Longer for Busy People: https://ru01tne2.pages.infusionsoft.net/?affiliate=0

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Transcript

Disclaimer: This transcript was generated by AI and may not be 100% accurate. If you notice any errors or corrections, please email us at phil@longevityroadmap.com.

     Atherosclerosis, the plaques that build up the number one killer of humans, it's, it kills more people in cancer and all the current standard of care in clinical medicine right now, things like cholesterol lowering is all just disease slowing.

Welcome everybody. This is Longevity Roadmap. I'm Buck Joffrey today. Uh, interesting conversation. We're gonna take a little bit of a different perspective. Usually, as you know, we're interviewing people who are down in the trenches, people who are doing research on. Some of the fundamentals of longevity, but all of this stuff has to get paid for.

And, um, more and more of that is coming from the private sector. Because of that, I wanted to get that perspective. I'm joined by a Dr. Karl Pfleger, who's a, a very thoughtful guy in the space of an investor. Um, and this is a, I think, a really important, um, podcast because. Again, we tend to dive really into the weeds, but I think it's important to understand where the money's going, because wherever the money is going is probably, uh, where you're going to see, uh, some material translation of the basic science into, you know, actual, actionable, uh, things.

Exciting conversation. Lots of, uh, I think you'll come out, come from this conversation with, uh. With some hopeful feelings about the future. Anyway, check it out. We'll have that interview right after these messages. Hey, longevity enthusiast. It's time to take it to the next level. I've been fine tuning my longevity regimen for years, and I look better and feel better than I did a decade ago.

In fact, my blood work is even better than it was back then, and it's all because of my data-driven regimen. And it's inspired me to create a course and community just for you. It's called the Longevity Roadmap, and I urge you to check it out. If you're tired of your belly fat, tired of being tired, or just wanna optimize yourself for the next 50 years, visit longevity roadmap.com.

That's longevity roadmap.com. Welcome back to the show. Everyone today my guest on Longevity Roadmap is Dr. Karl Pfleger, uh, one of the most thoughtful investors in the longevity space. Uh, he is a, uh, Stanford PhD in machine learning, spent years at Google, then shifted it, his focus entirely to aging science.

Uh, he's. Not just writing checks. He's also the creator of aging biotech info, which has become the go-to map of companies, conferences, and resources driving the field forward. Uh, his goal is to accelerate progress by showing how smart capital can shape the future of longevity. Karl, thanks for joining us.

It's a pleasure. Thanks for having me. So, as we were talking a little bit offline, either this is a little departure from what you, we usually do on the show because, uh, you know, we really deep usually dive deep into cutting edge, uh, basic science of longevity. Try to like, you know, uh, separate the nonsense from the real stuff.

And, and you're doing that sort of on a, uh, at a scale with that puts your money behind it, right? So, um, you have the option to stay in mainstream biotech, um. You chose to focus specifically on longevity from an investor's perspective, you know, what makes us feel different enough to build an entire thesis around it?

Well, traditionally, the whole idea of biopharma, the whole healthcare industry is to detangle the biology of specific diseases and. And, and develop, you know, therapeutics and or diagnostics for them. And, you know, that's great. And the world has worked on, worked that way for quite a while. Um, and there is a lot of disease specific biology and occasionally the, those efforts that are disease specific do.

Go back far enough to, to find some things, some biology that's actually relevant to other diseases, uh, as well. But the aging longevity field, the underlying hypothesis, the RO science hypothesis, uh, which is really not so much a hypothesis anymore. More of a, a paradigm. Now it's pretty clear. Um. Is that there's shared underlying biology that's upstream, earlier temporarily than all the disease, specific biology for all the chronic age related diseases.

And it's a whole different paradigm that's really gonna upend the entire healthcare industry since the majority of. By vastly, uh, you know, by vast amounts, the majority of death is caused by the chronic age-related diseases, the majority of suffering ORs caused by the chronic age-related diseases. 90, 85% of people in the US who die, die as a result of age-related chronic diseases.

90% of developed worlds altogether, 70% globally, over 40 million people a year. Over a hundred thousand people a day. And you know, suffering wise, it's just as bad. Um. So it's kind of absurd that, that most of the whole medical field and pharma industry does this stuff on a disease specific basis when really like, this is the, this is the thing to concentrate on.

So, um, I mean, I think from a, from an investment point of view, it's gonna be very, very lucrative. But from a. Philanthropic point of view or, or philanthropic capitalism point of view. It's also very compelling. Um, you know, the, the, just the purely capitalistic argument is that normally farm biotech startups have this sort of the same, they have the same trade off as any startup.

It's a very, very small, it's like a lottery ticket or is a very small chance of success for a, a bag of gold if you, if you succeed. And that's sort of the normal startup investing thing. And it's always, of course, the, for investors, the difficulty is weighing the. This small chance versus this big pot of gold.

It's like a, it's like a high numerator, high denominator thing, you know? Does it come out above one or below one? Who knows? Uh, it's, it's typical, but with the idea of going after aging biology, you theoretically have multiple pots of gold because if it works for the one indication, you know, your chance of success is about the same as any other biotech.

But then if it works. You can label expand or physicians can start prescribing off-label and you can potentially treat five, 10 different diseases. And so, you know, every different therapeutic is potentially pipeline in a pill. You know, obviously I, you know, I agree with you on the, uh, the idea of an upstream mechanism or mechanisms, uh, that, uh, ultimately are responsible for the vast majority of, of, of age-related disease.

But even that. Somewhat, I mean, there's a lot of different areas within that upstream area, right? Whether you're talking about, uh, immunology, whether you're talking about mitochondrial health, whether you're talking about, uh, you know, mTOR pathways and serin or whatever. When you look at that, how do you, how, how do you, uh, look at those moving parts and kind of, you know, decide, uh, you know, what's investible right now?

So let me unpack your question from two different angles, because there's an important point I wanna make that's a more, that's a broader point, right? So, so you allude to the fact that aging isn't one thing. It's, it's actually a bunch of different molecular processes that slowly accumulate o over time as we age.

Um, mi, mitochondria, you know, and there's, there's competing breakdowns of these, the hallmarks of aging, the senses, areas. You know, maybe none of them are exactly perfect, but everybody generally agrees there's like five to 15 kind of somewhat distinguishable, different sub pathologies. Um, so, so you asked about sort of how I pick those, but let me also make the broader comment that there's general agreement about that.

But it's amazing how often in the field people forget that it's not just this one monolithic thing. And sometimes people, this is, this is a, a horse that I get on a lot this particular year. There's a lot of people who. Think of the longevity field as only about extending lifespan and that the only thing that counts as a longevity therapeutic is something that can extend lifespan by itself.

But there are very few, there are a few approaches to slowing down metabolism. Calorie restriction, mTOR inhibition, some other, other cr mimetics that can affect all of these, these, these different aging sub pathologies makes, make them all run slightly slower. But there's also a lot of disease, you know, uh, sub pathology specific ways to address these.

There are specific mitochondrial things or things that just affect proteostasis or things that just kill senescent cells, which may not be expected to extend longevity by themselves. It won't be until we can array. At least one therapeutic, if not more than one, for every part of the body, for each one of these sub pathology.

So it becomes this combinatorial problem. Not enough people in the field acknowledge the potential wide and conquer approach to the field, and I think that's important. So then back to your question about how do I specifically sort of prioritize these? You know, I think each one of these, like that's the thing, you have to actually fix all of these sub pathologies to really fix aging.

So the key is to. Have at least one therapeutic approach that you think has got a decent chance of succeeding in each one. So, you know, I tend to approach my investing in the aging longevity biotech area from a philanthropy capitalistic kind of mentality. I'm, I'm doing it for the world as well as for, you know, just making sure money comes back to keep sustaining the effort and fund philanthropy.

Um, and so I try to arrange my portfolio where I take. Try to have at least a shot on goal or two at each of the important areas. And so I think that a lot of the areas are ripe. I mean, obviously epigenetic reprogramming has, um, attracted huge amounts of attention. It's actually attracted so much money. I actually don't feel like I need my money too much there, but I have several there.

I was making, I made several bets in that area long before Altos came along and New Limit came along. Um. But companies like Shift, bio and turn. Um, and then, uh, I'm, I think senescent sell are super important and, um, and k you know, killing them is, is very viable. And there's, I've got three companies in my portfolio in that area, and I think there's the idea that senescent sell are good, is overdone and not, you know, scent cells are good, but only transiently.

It's not clear that there's any benefit to long-lived senescent cells. And so lytics are still a perfectly viable idea. Stem cells are another one of my favorite areas. I think there's a lot of really good, um, data coming out there. And we finally are having, it's not all a wild west of offshore, um, you know, clinics that are unapproved and we've actually got, you know, approvals through the FDA and other regulatory national bodies.

Um, and then there's lots of interesting work in the stem cell area on the signaling molecules that come off the stem cells instead of actually the stem cells themselves as a delivery, uh, in injectable, uh, therapeutic themselves. Um, so et cetera. So, you know, you go down the list and you know, every different type of damage.

You know, one way that people think about the field is, does this category of therapeutic extend lifespan right now, given the baseline that we start with the average. You know, member of the US public. Another way to think about it is if we solve every other problem, which would this other, would this particular problem limit lifespans?

You know, it's sort of the, you know, whether it extends lifespans now or not, it's the, if we wanted to fully rejuvenate everybody back to the biology of their twenties, you know, young adulthood, this repeat biology, right? And we wanted to be able to do that repeatedly so that nobody ever suffered any of the effects of adult biological aging.

Nobody who ever had the biology of current 50 plus, 60 plus year olds. You know, the question is, you know, would some particular molecular cell pathology eventually cause that kind of degeneration and age-related pathology if we didn't fix it? You know, so that's one sort of way to sort of, you know, so something might be.

Slow enough accumulating that it only affects 110 plus year olds, in which case it's not really a problem right now. But if we do want to sort of think about the long term you can think is that, do we need eventually a solution to that problem? And, you know, those maybe have lower priority at the moment, but they're worth thinking about how we would then solve 'em.

Um, curious how you view, I guess, when you, when you're investing in this field, I would imagine you would have some sort of. Theory or thesis on how we get around this problem over the next couple of decades. Right. And, um, you know, my, uh, uh, I guess, uh, my, a friend, uh, Aubrey de Gray, as you probably know Aubrey's talked about longevity, escape velocity.

Um, the, is the concept of longevity escape velocity, the one that you use kind of as your framework. Sure. Uh, I mean, I, I fully believe in longevity escape. I think it's pretty inevitable, right? We're, we're all just molecules, humanity's getting better and better at manipulating molecules. You know, I don't believe there's anything that's not, you know, not just a molecular state that is needed to fix everything.

Uh, so eventually it'll happen. It's anybody's guess exactly how fast that happens. But obviously we can prioritize. So, for example, two of my portfolio companies are the only two companies in existence, as far as I know, that are, that have disease modifying, reversal of atherosclerosis, right? So atherosclerosis, the plaques that build up the number one killer of humans, it kills more people in cancer and all the current standard of care in clinical medicine right now.

Things like cholesterol lowering is all just. Disease slowing, right? It doesn't fix the plaque. So two companies in the field, both of which grew out of Aubrey's. You know what to, to one of the companies like Clarity is, is people from the Sends research foundation who founded it and the UP Company Repair Bio is Reason who was one of Aubrey and sends his biggest cheerleaders.

Those two companies both have therapeutics in the works that can reverse atherosclerotic plaque and Cycl clarity is already in phase one trials in Australia and repairs in preclinical, but they've got lots of, uh, late stage preclinical data and it looks really good. And so I, I expect them to start clinical trials soon.

Um, and so, you know, obviously fixing that pushes the, the LEBA little bit and then, you know, I, I mean, I try to do. I try to invest primarily in all these things that are gonna have these big effects initially, while sort of paying attention to those other things that are gonna be needed, and also paying a little bit of attention to what's already getting a lot of money and what's not getting enough money.

And so, for example, for a long time and even still now, um. Problems with the extracellular matrix. The ECM have not gotten enough research and nobody really knows how to drug it and how to break cross links. And so I have two companies in my portfolio that are working on that. The one that's farther along is, is probably Rebel, uh, pharmaceuticals.

And they have, uh, some great enzyme engineering, uh, in order to break cross links that. Some of which, you know, basically don't have any normal way for human DNA to create an enzyme to, to break those. And so, I mean, I think there will eventually be progress there, but we need more, we need more shots on goal.

The problem is that the shots on goal are almost in infinite, you know, like it, if you look at, you know, just in doing this podcast, um, you know, I, I, I constantly hear about a new angle, right? And who knows, who knows if it's a a real thing or not. Just as an example, uh, I spoke to, uh, the, the discover of, of the telomerase gene a week or two ago.

And I didn't really think that Tera was lengthening. His thesis was really something to pay much attention to anymore. There's just been too much. I don't know, there's just, there's, there's just too much noise there. But afterwards, after I talked to him, I was pretty convinced that there was something there.

You know, it just kind of, sort of a never ending, uh, you know, now what, and I can look at it. I can just. This has gone through this sort of classic hype cycle where there was a period of time where everybody thought it was the key to aging and it was the only thing that was, that mattered and blah blah and, and you know, and that crashed down, but it probably crashed down too far to people thinking isn't important.

And now we're finally coming back up to this sort of, okay, yeah, actually. There's something there. And you know, I, I think absolutely we're gonna need a way to extend telomeres. And I have one company in my portfolio that does that with mRNA and it's, I think it's gonna be great. And there's lots of good data on telomerase and things like IP F so yeah, it's, it's very, it seems very clear it interacts with senescent cell senescence.

Um, but you know, even if you have some way to kill senescent cells, you're gonna need a way to extend omes in order to keep stem cells active. Right. Eventually. Right. And then you have, you know, discussions of, uh, regeneration of the thymus gland, right? Like, and then you end up, you, you, there's just like an infinite number of things where, I shouldn't say infinite 'cause I'm sure it's not infinite, but it, it, to me it seems that way.

But, um, that you, you just look at it and you're like, well, yeah, but that's almost like, you know, programmatic death, right? If we run out of this, you know, certain number of immune cells over time. You know, how are you gonna live? Are you, you know, like, so it just kind of keeps going. But it's, it's an interesting area.

I just think, uh, um, to look at. But, um, let me ask you this. So comment, go ahead, but comment, your comment about, um, how do you deal with this? New things keep coming along, goes exactly back to your previous question about LEV, right? We know there are some sub pathologies that are clearly impacting lifespans now because they're creating high risk of multiple age-related diseases.

So we know we need to fix those, so we should just get on with doing that. And when we do, people will be living a little bit longer, and then we'll see which of these other pathologies that we didn't maybe have on our radar have high up priority and, and then need a 10. That's the whole LE idea. And I think, you know, clearly, so, so you know, for example, atherosclerosis, like I mentioned, um, I, I mean I think there is good data that thymic evolution is probably bad for you.

There's still some debate about that. Um, but et cetera, seno, senescent cells clearly play a role. You know, Kirkland's got a slide with 20 plus diseases, so there's things we know we need to fix. We don't have to get the laundry list exactly. Perfect. Now we just need to have the top priority ones. Get multiple enough shots on goal that some of them succeed clinically.

You know, one of the biggest challenges in proving a therapy works in humans is that, you know, waiting 30 years, 40 years. So what kinds of methods are you using to, I guess, um, shortcut that issue? Is there a blood tests or anything like that that you, you're relying on yourself for some of these outcomes and using it as a, you know, as a surrogate?

For, for lifespan. I, I look at that and I'm like, boy, that'd be a real challenge if you wanna invest in something like this. So, yeah, I mean, this is a big issue in the field that I think the field often doesn't. Some people in the field have discussions that don't appropriately acknowledge. The challenge of the, the human long lifespans and getting the, the data right.

Um, and it's, it's, it's frustrating how often you see, like Eric Topel just had a, a post where on vitamins, and he wrote this paragraph that said, experts have told me that there are no long-term randomized controlled trials in humans with high enough N that prove that any vitamin extends human lifespan.

Of course there aren't, you can't have long term written life control trials in human at the duration of their life, man. Especially with high end, like, that's just completely impractical. So here's the thing that, that I, I wrote up a thing and it's on my social media. People find me on Twitter or LinkedIn.

There's a version of this post on, on both of them, right? The best we can do, right? Here's the three things that we want from data. Ideally, we want. Long-term data. Well, we care about long-term health here. We want long-term relative to lifespan data, and then we, that should be, that should trump short-term endpoints, right?

Ideally short term relative to lifespan influence. So we want long-term data. We want randomized data, um, instead of observational data. Ideally we wanna prefer it, and we want data in humans. So three things in humans over. Animal models, model species. Right? So, so long term randomized in humans. Well, this is a choose two of the three.

The thing is you can't, all three is IMS is not impossible, but we just, we're not gonna have it for decades. Even if we started it now and it's, and it's economically impractical, so we can't have all three. But this is one of those situations where any two of those three we have in many areas we have lots of data on.

Right? So we have. We have randomized controlled data on non-human, long-term relative to lifespan. You, you just choose either one of those three and you can leave it out. And we have good examples of data, so the best we could do is for any given area that we care about, whether it's, you know, some lifestyle in modification we're thinking about, or some new therapeutic.

We try to triangulate as much data as we can from each of the three areas that leaves one of those three desirable things out. And then if, ideally, if all three of the things point in the same direction, that gives us some good. Um, so if we're on social media, for example, I looked at protein, low protein versus high protein, and I, I booked that.

But even for new therapeutics, right? So you start out with. The, the, the model species. So you have mice or you have some other model species and you look at how the data works for that particular area of biology and therapeutic approach. And then try to gather whatever data you might have in humans.

Maybe there are some relevant biomarkers that you can mine for, for epidemiological data, et cetera. Um, and so, you know, and then you proceed through clinical trials, which don't take 30 years. They only take. Five to 10 years depending. And then, you know, you start getting people using it and hopefully that's great and you monitor 'em afterward.

Um, in the meantime, the search is on for biomarkers to try and short circuit this process. And we're, you know, we have aging clocks and we have other biomarker. You know, the aging clocks aren't really ready to be full surrogate endpoint for a longevity lifespan trial yet. But they are getting better and they're already good enough to be better than using chronological age for some of the purposes in which chronologically age is already used clinically.

So I think progress is happening there. I'm curious, um, just a discussion on the aging clocks, because I mean, it's been, um, that's an area that I think a lot of, uh, longevity. People, longevity hackers or whatever you wanna call 'em, are really relying on, but in my most cases, they're neither, um, you know, they're neither, uh, uh, specific or accurate.

Um, and so is there some clocks that you think are for some reason, you know, worth relying on a little bit more? There's a lot of misinformation about aging clocks. Um, so in general, they are better for populations. Which is good for studies than they are for individual use, right? So there's, 'cause there's a noise and so they're not as good for, I'm gonna take one data point using one clock, and then I'm gonna change something about my life and then I'm gonna take another data point.

Like there's too much variability there. Um, but that doesn't mean that you can't run a trial with 500 people or a thousand people in each the treatment and control group. That, that evens out a lot of the noise. So that's, so that's one. Um, there are a number of improvements that have been made to aging clocks over the last five years.

A number of problems have been identified with the clocks with. Fixes to those problems and not all those fixes have been incorporated into all of the clocks. So it's fashionable these days to like try and test as many clocks as you can and like look at a consensus. I don't think that's a very good, very good approach.

What we want are new clocks that take into account all of the things that, all of the showstopper problems that have been identified. So here's three that have, that have happened recently. Several years ago, Morgan Levine's lab, then at Yale, she's now at Altos, um, identified the test retest variability because a lot of the clocks would, would look at hundreds and hundreds or, or a thousand plus CPG sites, the methylation clocks, and then they would boil 'em down, like in, you know, they would do this, um, feature selection process and they would boil 'em down to only a few CPG sites.

But there's enough noise in the CPG site measurement that what would happen then is you could take the same. Blood tests or, or, or sample tests, uh, whether it was saliva or whatever and, you know, and run it twice through your machine and you would get widely different answers. And the, they, they came up with a fix for this, the sort of principle components thing, and you test more CPG sites, it evens out.

And then, you know, basically you fix that problem. And the problem is not all the clocks actually have that fix. The best ones do, but not all. That was several years ago. And then more recently in Eric Burden's lab at the buck. Uh, Alan Tusc, one of his grad students. Um, you know, there are different cell types running around in the blood.

There are very, especially very different, um, a bunch of different immune cell types. And some of those, it turns out, have, according to these CPG site clocks have, are, are sort of inherently younger than some of the other cell types in the immune system. And sometimes when you get an illness or so that something else changes, the ratio of those different immune cell types changes.

And so you can get this situation, which is sort of, you can call it in statistically they call it Simpsons paradox, but, um, where you get, where you call it mixed changes in general, where maybe all the cells in the blood. Don't change in their age. A relative proportion of the young ones or the old ones changes.

And as a result, the average looks like it changes. And so you can, you can fix that out by dividing the cells by their different types. And so they came up with these phrases, intrinsic age and extrinsic age, and you know, very few of the clocks available today direct to consumer for the biohackers actually have that broken out.

You can do it and it's coming and I'm sure all of them will end up breaking that out eventually, but, but right now that's sort of like, you know, that means all the sort of first and second generation clocks aren't trustworthy with respect to immune cell type niche changes if you just happen to have a cold recently or whatever.

Um, and then the third thing that happened recently is Vian VTIs Lab helped detangle that some of the CPG sites, some of the changes in the epigenome are. Compensatory or, or downstream of some causal chain, but others are actually on the causal chain themselves. Like that change happens in that as a result of that change, you are older or you know, some, some pathology is driven and so they detangled the causal ones versus the non causal ones and came up with clocks that.

Only are based on the causal ones, for example. So when all of those things are incorporated into the new clocks altogether, and when we've gone several years without some new showstopper idea showing what was wrong with the current clocks, then that's the time where I believe the clocks will be, will be good.

But it's important to know the clocks are all really good, like chronological age is a pretty good. So let's take a step back. Chronological age is super important for predicting. Chronic age related risk, right? If you look at the top risk factors for heart disease and cancer and a whole bunch of other things, it's like, it's like all the things people think about, like, like cholesterol and smoking and then like, you know, aging.

You know what your chronological age just dominates. It's like so much more important of a, of a biomarker of your risk. And yet the aging clocks, the good aging clocks, are already at the point where they can out predict chronological age. In terms of predicting the risk of age-related disease or predicting mortality.

So we're already at the point where maybe clinical medicine should actually be using these aging clocks alongside, or instead of chronological age for some of the reasons, some of the ways that we use that, for example, you know, diagnostic screening criteria for colonoscopies or, or who should get a booster shot, who's at higher risk for various conditions with that, that have vaccines with boosters.

You know, there's all these thresholds on chronological age. Probably we would reduce risk if we actually took into account even just the current bets. Yeah. Aging clients. Yeah. Yeah, definitely. Um, what gets you really, really excited? Gimme like a couple of topics that when you hear about them right now and where you're sitting from, you're like, wow, I love that.

Uh, that is gonna be big and you can refine your question. If this isn't, doesn't answer your question, but the thing that gets me very most excited right now is that, you know. The wider public does not realize how important the aging and longevity field is. They don't, the, the public doesn't realize it, and government funding doesn't recognize it.

Right. You know, 85% plus of humans who die in the US die as a result of age related pathology. But the NIH budget devoted to aging biology is less than 1%. So there's a huge mismatch there. And. The public is going to get behind this at some point when they realize that it's the only way to save social security and Medicare from bankruptcy and solve the demographic that the demographic is out that we're on the way to of the silver tsunami.

Um, that hasn't happened yet. It's a big question. What is the thing that is going to. Convince the majority of the public and probably it's going to be many things, but one of the things that gets me most excited is that the field is reaching a really exciting point. The next five to 10 years are gonna be super exciting.

So roughly speaking, if you look at, there were, you know, centuries of science where we looked at disease specific biology, and then the last few decades is where the sort of biology of aging in academia has really come. Its, you know, made big breakthroughs, but that didn't start generating biotech startups that were really trying to translate these new discoveries into things that millions of people could use until about the mid 2010s.

Well, it on average takes about 10 years to get through clinical trials to approval from a new biotech founding. So mid 2010s, well, it's right, it's 2025 right now. What does that mean? Oh, look, it's been about 10 years since the very earliest in some of the earliest ones. What's actually happening? Well, for some reason this narrative is underappreciated in the field, even amongst the top scientists, even in terms of discussions that happened at the Tom conferences.

But if you look at the, you know, as my website, aging biotech.info does and its company's table, right? If you look at the hundreds of biotechs that are, that are really looking at these core aging sub pathologies and, and trying to bring things to market with them. There's hundreds of them. There's three or 400, but there's not that many that are actually in late stage clinical trials yet.

But there are some, because some of them started in the late 2010s. So it turns out, if you look at just the approvals and the phase three clinical trials of drugs that really embody the geoscience hypothesis. There's a lot going on and this is the vanguard of the field, right? There are a couple areas where drugs have actually gotten through to FDA approval.

There are are another 15 or so in phase three, and with a greater than 50% success rate in phase three. That means that in the next several years, we're gonna have another half dozen at least approvals, and then there's 30 plus phase twos coming behind those. So we're actually at the vanguard of a whole bunch of things actually getting to market that.

Are fundamentally different from majority of pharmaceutical approvals in that they address biology that's not specific to a single disease, which means we're gonna start years after the approvals, we're gonna start getting label expansions where they get approved for multiple other diseases and or the physicians are gonna realize the biology it might apply to their patients who have slightly different diseases and are gonna start prescribing 'em off label.

When that happens, and that's, that's sometime in the next five to 10 years. When that happens, it's a whole new world. Like everyone's gonna pay attention and realize that this field is the, is the next big thing. You can kind of almost see that a little bit with GLP ones right now. That's right. So the idea is, so GLP ones are even worse than what's coming because, I mean, it's not clear yet, but so far all the data on GLP one drugs.

Only in people who are overweight or obese. And it's clear that being overweight or obese speeds aging. So it's possible that all the benefit from GLP one drugs is just to undo that speed up of aging. It's also possible that they really do affect mitochondria in some way. That will even affect people who stay lean their whole lives.

But there's no data supporting that yet. And so the new things that are coming along, some of them. Are gonna work even for people who weren't overweight or obese ever and didn't have that particular accelerated aging pathology. And so, so I think that there's a lot of things coming along that have more evidence that they're gonna affect a hundred percent of the population and not just the, the overweight portion.

Karl, thank you so much, uh, for the conversation. It's been, uh, really fascinating. Again, the, the site is aging biotech.info, sort of the go-to map of companies, conferences and resources driving this, uh, field forward. Thank you for everything you do. It was a pleasure. Thanks for having me on. Thanks for listening.

A quick reminder that while I am in fact a surgeon, nothing I say should be construed as medical advice. Now, make sure to include your physician in any medical decisions you make, and also, if you're enjoying the show, please make sure to show your support with the like, share, or subscribe.