The Health Curve

Quantified Longevity: Biohacking To Extend Healthspan | Ryan Cabeen PhD, x-CTO at Blueprint (Longevity Series)

• Dr. Jason Arora • Season 1

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Can we measure our way to a longer, healthier life? 

In this episode of The Health Curve, I sit down with Ryan Cabeen, PhD — former CTO at Blueprint and biomedical AI researcher — to unpack the world of quantified longevity: data, wearables, biomarkers, and what actually moves the needle for health and lifespan.

We talk about the rise of the quantified self movement, how consumer tech has transformed what we can track (sleep, steps, heart rate, biomarkers and more), and where the science is solid vs still experimental. Ryan explains the difference between top-down “live better now” strategies (sleep, diet, movement, stress) and bottom-up molecular longevity approaches (gene therapy, cellular reprogramming, stem cells, rapamycin, GLP-1s).

We also get into the ethics and realities of longevity clinics, “over-measurement,” animal studies that haven’t yet translated to humans, and emerging tools like digital twins that could one day simulate our future health. Finally, Ryan shares what he thinks people are really seeking when they chase longevity.

If you’re curious about longevity, biohacking, Blueprint, or quantified self, but want a grounded, evidence-aware conversation, this one’s for you.

👉 If you find this helpful, please subscribe to The Health Curve, and share it with someone who’s curious about longevity or health optimization. 

SPEAKER_00:

Ryan, thank you so much for joining me today. It's great to have you here.

SPEAKER_01:

Likewise, really glad to be on the show and yeah, uh nice to chat with you, Jason.

SPEAKER_00:

Can you tell us a little bit about your background?

SPEAKER_01:

Yeah, gladly. So let's see, I've been doing biomedical research and technology development for maybe 15 years now. I've worked at universities, medical research institutes, startups, you name it, but kind of throughout all of it, I've been developing software, building teams, doing research, mostly related to health, very often related to the brain. Yeah, I've done the full academic track. I got a PhD in computer science from Brown. I worked at USC as a postdoc and faculty and worked with the CZI through their imaging scientists program. I love academic research, but I also realized, man, there's a whole lot of cool stuff going on in industry and discovered a lot of startups doing AI for digital pathology, diagnostics of cancer, fun stuff like that. I worked on and I most recently worked at Blueprint, kind of in the space of longevity and building up technology for that kind of space and working on things like health optimization, self-measurement, and all that good stuff. And these days I'm working, I have a consultancy, working with a number of different startups, doing cool things related to neuroimaging, uh, aging, you name it, anything in that space. So yeah, fantastic.

SPEAKER_00:

Yeah, it's a really amazing background. And we of course met through the longevity work at Caltech, which is really fascinating. They have a fantastic program over there. So I wanted to talk about Blueprint a bit and this quantified longevity movement that has emerged in recent years. So this is essentially people running what we would call n equals one experiments. So experiments on themselves, which with strict routines, wearables, advanced diagnostics, using supplements, experimenting with different things that might slow their aging down. And there is, of course, a lot of data involved there. Blueprint was one highly visible example of this tech-enabled approach, essentially. And of course, you were the chief, the chief technology officer there, but it's really a snapshot of a much bigger movement. I've been experimenting with stuff my entire life to optimize my routines, my health, etc. So I don't feel like this is something just for folks who have always called this longevity. But can you tell us a bit about this quantified longevity movement and some of the work you did at Blueprint, which was a deep dive into this? Yeah, gladly.

SPEAKER_01:

This is a really exciting topic. You know, it's one of these kind of frontiers, I think we have as a society is figuring all this stuff out. And like any frontier, there's a lot of different things happening. It's a little chaotic, so it's part of the fun, I think. And that there's all these different approaches to it, right? But I think you're right, like this kind of current of quantified self has been around for a while, like self-optimization. I remember growing up, my family, my grandmother even would be taking supplements and trying all sorts of funny dietary things. I mean, I think there's always been an undercurrent of this in society, but it's definitely hit a cultural moment right now where people are aware of it, people are kind of conversational about it. It's not like something you have to be kind of dedicated to. So there's been like people who are really kind of deep into it, kind of you could call them biohackers, who are willing to try very adventurous things, just people who are just trying to live a little bit healthier. I think one of the things that maybe has catalyzed it is just the ability to measure ourselves. They weren't wearables like we can get from an Apple Watch or Whoop or whatnot until recently. And just being able to track things like your sleep and your steps allows you to just discover, like, hey, there's something going on that I wasn't aware of, right? We as humans, we think we understand ourselves, but very often when you go and look and measure, you discover things that really are not just bubbling up to our awareness. So I think that's an experience a lot of people have. And I think if you look back even like three or four years ago, if you use the word longevity or health optimization, people really wouldn't be familiar with what you're talking about, but it's mainstream now. I think the blueprint is a nice example of a company that has kind of brought it to awareness, just kind of made it a household name. So but I think there's a lot of people doing this, and it's a full spectrum of people who are like scientists developing kind of a molecular understanding of aging and interventions to people who are kind of thinking more about health in terms of just lifestyle interventions and things like that. So I think it's part of fun is like all these different people are kind of together and in competition in some ways and trying to discover all this.

SPEAKER_00:

Yeah, and as we've alluded to, people have been doing this for a very long time. And our ability to measure has really improved in recent years. Now, that can be stuff like hardware, it can be stuff like biomarkers, et cetera. Can you tell us a bit about the different things that we're measuring today and how quickly that has evolved?

SPEAKER_01:

Yeah, so this is kind of different from how people often think about their health. The kind of usual thing you do is like you go to your doctor once a year for an annual checkup, and maybe they do some blood work, maybe they do some tests that occur at different ages. And that's all great and good. But basically the idea is that because of technology that's available, we can kind of do that more rapidly. We can get more feedback into the loop. We can take a bunch of sensors in our life. It could be things that we wear on our wrists, it can be maybe more frequent blood testing. You can do blood testing at home now. There's kits where you can collect it yourself, mail it in, all that good stuff. There's sleep mattresses that can measure your heart rate and your movement throughout the night. All these things are kind of sources of data that you can pull together. I think the challenge is that we're at a point where, like anything else, there's kind of too much data. We have to make sense of it. We have to understand it. So I think a lot of the work right now is A, developing these new sensing technologies and then giving people tools to actually make sense of them and make decisions based on them. You don't want to spend all day looking at the raw data, right? You need to some have some way to summarize it and translate that into insights.

SPEAKER_00:

So yeah, you said something really interesting there around what's happening in healthcare and what's happening outside of healthcare. So my career in recent years, I span both these spaces. So there is the stuff for consumers, which is really you go as far as you want to go and as much as you can afford, and as much as you have the luxury and the time to pursue, to investigate and experiment with. And then healthcare is obviously lagging behind in that there's only so much the healthcare system can do. It needs to do better, it needs to measure more, track more, et cetera, but it's constrained for various reasons that we won't go into today. In terms of what we're getting right about this quantified self-approach, what is going well there? What advances have we made in recent years where all this additional data is actually giving us useful, let's call it clinically relevant or scientifically relevant information that people can act on versus, hey, we have a ton of this data that's interesting, but we can't really interpret it and we can't really do anything with it. Where exactly is the line at the moment?

SPEAKER_01:

Yeah, I think it's a great question. I I think one of the things that these technologies are good for is building healthy habits. You can reinforce things at a scale that's a bit more useful for making things automatic. Like you don't want to think about how many steps you get per day, but you kind of want to build routines that give you more steps and kind of meet some goals. And you can look at like epidemiological studies of how many steps you need per day and set some goals for yourself and realize, like, oh man, there's some days of the week that I just don't leave the house. You just have to kind of discover that, and measuring yourself is good for that. You're not going to find that going to a clinic once a year with a doctor. And I think one of these things is also kind of competition. People have discovered that, like, when you can measure something, people being people, they love to compare each other, right? They want to see, like, am I doing better than my buddy or my neighbor or something like that. And you know, some competition can be too aggressive, but it can also be very productive, I think. And that's one kind of interesting offshoot I've noticed is that there's kind of this athletic component to measuring yourself and that you can make these comparisons. And you can keep on stuff like make leaderboards, and it could be, you know, just seeing like which of your friend group walks the most in a day. And then if you feel like, man, I'm the person at the bottom of the leaderboard, I don't want to be there, I'll go out and take some steps. So these weird incentives that come up, I think that I wouldn't have expected, you know, in terms of wearable devices. People weren't talking about this 10 years ago when the research was kind of emerging. And that can go off into different territories. It could be simple stuff like sleep and steps, it could be patterns in your epigenome and markers of kind of your biological age. So people do the full gamut of things, I think. So I think there's multiple ways that basically we get advantages out of these. Maybe competition is not the right signal, but you know, just kind of having self-insight and self-awareness is good for some people. So I wouldn't say it's one thing, it's kind of all these things together.

SPEAKER_00:

So we can measure things in our day-to-day lives. We did an episode previously where we talked about this pyramid where the biggest levers for health span and for longevity improvement are the basics around sleep, diet, movement, stress, preventative care, that sort of stuff. Stuff that we already have a lot of access to. And if people get that right, they're gonna do a lot for their longevity. What's your view on that? Given you had this window and you have this window into some of the more experimental stuff. Yeah, I think that's a great point.

SPEAKER_01:

And sometimes people think like, well, if I'm not doing everything, why should I do anything at all? Right. And I think that's a real danger, right? One way I think of it is the Pareto principle, right? This idea that for most things in life, you can get 80% of the gains from 20% of the cost that you invest in something, right? And I think that's true for health optimization and longevity too. You can go to these longevity clinics, spend an insane amount of money, and get this wonderful package. But there is this kind of core set of things you can improve about your life that really gets you most of the gains, I think. So when you start talking about these obscure stem cell therapies and whatnot, that's kind of trying to fill out that last five, 10% of the gains. But if you just think about like sleep and diet and exercise, I think those are the big movers, right? You can get most of the gains there. And they're not as easy as people think. It's one of those things where any one day you can get them right, but getting them right every day consistently is actually a big challenge. If you look at the data, that's what we saw. Is that regularity is is a challenge in itself, not just kind of picking any one goal per day. But I keep it even simpler, I think a pyramid's good. I think if we can boil it down, this 80-20 split is my daily kind of daily mental model I use.

SPEAKER_00:

If we think about some of the more exciting and interesting and experimental things, some can be as simple as the full-body MRI. I have my opinion on that, which we can talk about. There's cellular reprogramming, there's gene editing, that we talk about stem cell treatment, all these sorts of things. Can you tell us a bit about what's out there right now? What is being investigated, researched, what's early stage, what's unproven in humans? Like what does the landscape look like right now for anti-aging and longevity treatment in this context?

SPEAKER_01:

Yeah, I think that's a great question. And it kind of reveals that there's kind of like two different worlds, in my opinion, for all these interventions. There's kind of you know the interventions that attack the phenotype of aging, right? It's like your vision degrades, your hair goes gray, all these things. But then there's also like the kind of molecular things that are happening, which we actually have a lot of science looking at those. Yeah. So there's this idea of the phenotype of aging, these things that we're kind of familiar with on a day-to-day basis. We see them in our family and ourselves, cardiovascular disease, our cognition declines, muscle loss, skin aging, things like that. But then there's these kind of more molecular things that are going on, which you really have to do a lot of science to figure out. People call these hallmarks of aging. There's things that really get into nitty-gritty of like, what is your genome doing? Is it unstable? What's happened to your telomeres, epigenetic changes, all these things. And so there's interventions that can kind of attack both of those domains. I like to think of it as like top-down versus bottom-up. Top-down is trying to address things at that kind of macroscopic level, whereas the bottom-up is kind of looking at these molecular and microscopic changes. And you you pointed out that there are stem cell therapies, there's gene therapies. All these things can actually attack some of those root causes. I think those are very exciting. Those are also very challenging for a number of reasons, right? I mean, you're basically using technology that you really need to assess the safety of. We don't know what the downstream effects are. So I think those have a higher burden of kind of proof and experimentation to demonstrate safety. There's some very adventurous people who are willing to kind of use themselves as guinea pigs, which is controversial. I personally respect it, you know, as long as they're rigorous and open about all of it. But I think also like if we want to deploy these widely, we have to be more cautious. But um a lot of interesting work there, I think. Those are kind of like if we really want to prolong life, those are the things we need to target. Like if we want to live to be 150, we really have to get at the root causes. But if we want to live well, if we want to have a better health span, I think attacking things top down is great. And there's a lot of very safe interventions. Like for the most part, you can tell people to exercise and eat better, and there's really no risk there. Everyone has their own kind of dietary needs, of course, but for the most part, it's a very safe thing to deploy widely. So I think I like to break them down into those kind of two groups that they're this macroscopic versus microscopic ways of thinking of it.

SPEAKER_00:

What is the difference between anti-aging and chronic disease prevention? Where's the line?

SPEAKER_01:

Yeah, I think it depends on who you talk to. I think a lot of people are into longevity to kind of take their healthy state and make it healthier and more enjoyable. And for some people, maybe better looking, even so there's that whole world. But for a lot of people, like they they are facing some chronic health disease. And for that, I do think it's important to have doctors in the mix and clinicians and a lot of solid science to back things up. So I personally do see like a big difference between work that's related to diagnostics and treatment of disease versus kind of health optimization. One's more in the medical space, one's more in the wellness, kind of fitness, athletic space. And where one crosses over to the other is a good question. I I wish I could articulate that better, but I don't want to speak out of my expertise, to be honest.

SPEAKER_00:

As you mentioned, there are lots of longevity clinics that are springing up everywhere. I think at the moment there's an estimate of around a thousand in the US alone. There are high-end executive workups that can cost five, ten, fifteen, a hundred thousand every year. One core piece that we see in a lot of these approaches is to measure a lot of biomarkers. Now, when I saw this, I thought, that's great, but do we have the clinical evidence to know what to do about a lot of these biomarker results? Like how useful is this over measurement if there's not much we can do? That doesn't mean we shouldn't measure, but my fear is that this is being missled as this is a longevity service rather than this is experimental longevity measurement for which we don't necessarily have solutions yet. What's your take on that?

SPEAKER_01:

Yeah, I think that's a great point. One of the challenges I think that these clinics face is how do they communicate to their clients or patients? You want to communicate things simply and understandably, but you also want to be very cautious about communicating the subtleties of science and the findings, the caveats, which uh I've worked in science long enough to know that there's always caveats and always an asterisk at any finding. So we have to be careful communicating that, I think. So I think any person who's running one of those clinics, that's part of their skill set should be just how do you communicate science in a realistic but understandable way, which is not easy. And that said, you know, you can also communicate in a way that there's some uncertainty, right? That there's an acceptable amount of missing information, that we have some evidence, some weak evidence that this is useful, the harms are pretty low. Why don't you try it? But we can't promise you results. So I think a lot of people approach this as kind of a self-experimentation model. So you can, on one hand, take the findings of some study and then kind of rely on that as ground truth. I think that's a bit riskier because you're not using the same context as that study. Maybe you're part of a different demographic or something that could change things. But if you think of it as like self-experimentation, if you can measure something that's changeable, there's something there, I think. So if you can try out something and then see a response two weeks later, that's something that is adding some information. You know, I wouldn't say it's generalizable knowledge that necessarily helps someone else, but it might help you. So we discover that, oh, removing this thing from my diet helped me sleep. You don't need a large randomized control trial to tell you that that was helpful, right? Personally, I, for example, reduced my caffeine intake quite a bit. I love coffee. I would drink three or four cups, especially in grad school. And I also had very bad sleep at that time. And I discovered maybe about a year ago that I'm incredibly sensitive to it, even though I have been drinking a lot, I've been enjoying it. So I've cut it down quite a bit, made that observation. I think there's evidence out there like that, but I think we all have individual differences too. So this idea of trying something, measuring yourself, looking very closely, being skeptical as well, I think can pay off. And so I think of those kind of two types of information. There's kind of what you get from these big studies, and then also kind of what you get from your own end of one uh work.

SPEAKER_00:

We'll get back to this conversation in just a moment. But if you're finding this episode helpful, here's a quick ask. Take a second to follow or subscribe to the Healthcare podcast wherever you're listening. And if someone else in your life would benefit from this episode, or any of the others you've heard, please send it that way. Alright, let's get back to it. Let's move on to some of the evidence out there for longevity extension in animals. So, in animal studies, aging interventions can look quite dramatic. I think there's quite a bit of evidence in my studies, for example. But translation to humans seems to be quite difficult. Can you tell us a bit about that? Like, what have we seen in animal models around life extension, health span extension? Where are we struggling to translate those findings in humans?

SPEAKER_01:

Yeah, I think this is one of the biggest challenges with aging research, right? Is that there's a lot of great findings in animals. We see very exciting outcomes, right? Like increasing lifespan by 10, 15%, which most people would kind of run to try their think about themselves. But for whatever reason, we see that they don't always translate when applied to humans. And this isn't just a longevity research problem. I think this is kind of a wider problem in science and biology, right? In terms of like some of these findings, I mean, there's specific things that, you know, have been researched quite heavily, and there are pretty robust findings in non-humans, uh like rapamycin, for example, is something that has been found in different species, not just mice, yeast, worms, flies, mice as well. There's some human studies going on. There's some people who have kind of jumped in as and one experiments to try it as well. So I think that's one word. There's some promise. I think the challenge is always side effects. Maybe there's side effects in non-humans that we just aren't aware of because we're not measuring them and we don't discover that there's side effects until we get to humans, or or really there's something different about human biology that makes new side effects that couldn't be anticipated. So I think that's always the challenge there. There's others, there's things like uh Resveratol, something that you can find in grapes and wine and berries. So that's one where there is evidence of this increasing lifespan and non-humans, and we do tend to already consume these things. So it seems pretty safe for humans to test. One of the challenges, of course, though, is a lot of these animal models were chosen because they've got shorter lifespans. They can actually get that feedback loop of experimentation and seeing like, well, what was the lifespan change? Whereas humans have a pretty long life. If you really want to test some of these interventions, you have to wait decades to find out what's the change that's happening. So there's a gap there just in terms of getting that feedback. I'd say like that combined with side effects, the main challenge is. The other issue with some of these animal models is that they're not directly comparable in anatomy. They're also not directly comparable in their kind of genetic background. So very often a mouse will be kind of genetically modified for experimentation to serve as a model of some disease. And sometimes that genetic modification is something that we just discover statistically is related to that disease, but we don't necessarily know if it's a causal factor. And in many cases it might be, and it's a good model, but in those cases where it might not be. Things like um Alzheimer's disease, there's genetic models of that, which I think are being done in earnest and they're worth pursuing. But there's also just challenges of the question of causality and if addressing the downstream effects of that genetic modification will actually translate to cures in humans. That's yet to be seen, I think. So yeah, I think we're doing that work. We don't want to think of just animal models as answering these questions. We also have to think about how they play in humans, in terms of side effects, in terms of whether things translate in terms of anatomy. Yeah, I think there's one thing about aging is that all animals do age. You really don't need a genetic model of aging in animals. So you can kind of just take wildlife and vice and kind of run experiments with them that way. So I think in terms of making animal models useful, that's kind of one thing that if we had to prioritize, I would just starting first with kind of the wild types and then kind of exploring genetic models after that.

SPEAKER_00:

And one of the challenges with all of this is how do we measure the natural world in totality, right? And there's a whole field around real-world data and in the context of the quantified self or not. I don't want to get too much into jargon here, given our audience, but of course, we are developing better scientific methods, such as things like platform trials and digital twins, where we can simulate what an intervention might do or how a disease may progress using computer models. Can you tell us a bit about that and the overlap with this space, given that we have to understand how things are going to change over a decade, as you say, not short time periods?

SPEAKER_01:

Yeah, that's a really interesting topic these days is this idea of digital twins and trying to build models of individual people that we can essentially run computational experiments on. There's a lot you can learn from working with people in real life. If we can measure enough about them, build some sort of causal statistical model of someone from that data. The digital twin idea is trying to see if that computational version of yourself useful in a scientific sense. Can you do things like ask if I change my diet in this way? What will be the downstream effect on maybe this disease outcome or this quality of life measure? Yeah. And I think these are really exciting things to work on. I think a lot of it is being enabled by this wide array of measurements we can take. There's a question of kind of how much do we measure? You know, you can measure, like you said, pretty much everything these days. So there's a trade-off of how do you find the right data, how do you build the right models. I think there's a lot of progress being made in the kind of machine learning AI side to do the modeling of the causal nature of how things react to certain interventions. So I think we're making progress in a couple ways to make this more useful. Like one is that expanded set of measurements, one is this improved ability to model and make predictions. But that said, at the end of the day, they're also not real people. And any model has some things that are missing, right? I mean, all models are wrong, some are useful, is kind of the classic saying there. So the important thing is that like there might be things we don't include on our models of digital twins that are actually the important things. So I think that's the biggest risk with all those approaches, right? So you can't rely entirely on them. But in terms of like being useful, I think, yeah, we have to find kind of nice ways to apply them.

SPEAKER_00:

How relevant is the longevity space to improving the health span and lifespan of all people? We talk about democratizing this approach. Just in the US alone, life expectancy can vary by over 20 years between different American neighborhoods. And of course, globally, that widens significantly. We've talked a lot about how a lot of the things that we need to do or that people can do are actually very simple. They're not complex science. They're just environmental barriers to those things. They're cost barriers. How relevant is it when people say, how can we democratize access to longevity services? Is that sort of a bit of a misnomer in itself in that it's it's not necessary at this stage? There's the 80% of things, the social determinants of health, essentially, that we need to focus on for most people in the world. And the rest is really experimental science at this stage. It's not really a moral or a social obligation.

SPEAKER_01:

I think that's such a great question. And it kind of touches on an idea that I see is kind of a misnomer that a lot of people have is they they look at life expectancy over time in the US and different countries, and you see it's going up and up, and maybe you extrapolate and think, well, it's going up at this rate, and we'll be living to be 150, 200 things continue. But if you really break things down, I think everything is distributions. You should think about like, you know, what are the individuals that are being improved by all these changes, right? And a lot of it is happening at the low end. So people who would be dying younger are are living fuller lives up to age 80 or something, not that everyone is getting older per se on average. So I mean, globally, I think infant mortality is a thing that's very amazingly being addressed, and that pulls averages way up. You look at just causes of death, heart attacks, and stroke are very common. And if you can address that with health and exercise, healthy eating and exercise, those are things that can really actually push averages up without the maximum lifespan of a person going up. And I think a lot of those things to your point about democratizing them are actually very accessible. Like we want to give people knowledge, give people tools to do all this, uh, create systems that allow them to live healthier. So I think all that is is on the table. It's there for the grabbing. I think the culture is kind of changing. People are thinking about their health in a different way. There's less alcohol being drunk, there's exercise being more part of daily life. Shockingly, I mean, like jogging is kind of like a new thing. I think in the 1970s is when it first started. There were people doing it before that, of course, but it was more niche. So I think this idea of just making health and measuring yourself is becoming part of a daily mentality that people have. But even within the US, though, unfortunately, like health outcomes are not uniform. If you look at a map of lifespan, there's parts of the US that are just dramatically different from other parts. So I mean, that tells you that there's something that that is actionable, I think, and changeable. I mean, we all live in the same country. We should have access to the same healthcare and food and things like that. So I think that if you want to argue for democratization, there's definitely something to be done there.

SPEAKER_00:

You said something really interesting there around jogging. And I just wonder, I've seen this somewhere in some sort of popular culture thing. But you know, if someone from the past was to time travel to our time and see people running for fun, they may think that the world has gone mad. So I mean, how much of this is just we have not been proactive enough in thinking about how we should live as a society, as individuals. We focused on incremental progress in many other ways, but we haven't thought about human progress and human health through this lens. Like this is just we're making people sit at desks more, we're overfeeding people, we're designing these urban environments or transport systems or whatever such that it people just don't move much. And we we haven't been proactive enough about this stuff. So we're having to overcorrect doing things that the natural world already encourages us to do. What's your perspective on that?

SPEAKER_01:

Yeah, I think that's a great point that, like the time traveler point, that if you plop someone down, they'd think like, well, what is that person running from? And they're not running from anything, they're just running for health, right? I think maybe meditation is maybe one of those other things. I mean, people have been doing it for thousands of years, but I think it's more common now. And you might see someone just sitting in a park with their eyes closed or not sleeping. That could confuse someone from maybe 40 years ago in the US, for example. And I think that touches on this point of like what's socially acceptable to people. Like a lot of people just kind of want to fit in with people around them and they don't want to be that person kind of running alone in the park. But you know, I think these days there is a bit more acceptability of different approaches to health. You don't feel like you have to do the same health regimen of everyone around you. So I think this kind of individuality is a very good thing that's happening these days and allows people to experiment and try things that are outside the norm and see what works and eventually share them with others and get that knowledge transmitted and all that. So I think in a society, I think, yeah, we're going a good direction in terms of being open to all those things. The flip side is that people can also kind of come up with their own kind of reasons for why they're doing these things. So we want to make sure everything is science-backed and all that. So I think that's the tension is we want to give people individuality and choice to explore, but also kind of keep things evidence-based.

SPEAKER_00:

Awesome. What's the most exciting thing you see in longevity research at the moment? What has the most potential in your view?

SPEAKER_01:

Yeah. So I think there's a surprising connection between AI and machine learning and longevity in that they're both these kind of very data-driven approaches to thinking, right? And this is kind of obvious to us now. We're kind of surrounded by this way of thinking, but for for many decades, this wasn't how we did health and it wasn't how we did AI. Most of thinking about health, it's been very much going to doctors and getting kind of general feedback, not getting it very frequent, not reacting too much to your daily measurement. AI has actually been kind of the same way in that it was more of like a rule-based approach, more of an expert systems approach historically. So that was kind of the early days of AI in like the early part of the century. So I think there's a lot of interesting directions that people are discovering for longevity one, is these GLP1 agonists are just an incredibly useful tool just for achieving a lot of the things that people want to achieve with longevity interventions. So you can control your diet, control food noise if you want to do caloric restriction. GLPs are kind of on the locker for that. There's also all sorts of things that seem to be anecdotally coming out of their use, which I think is interesting. People are finding it easier to stop drinking, stop smoking, just anything involving habit formation and reward circuits. I think there's some interesting signal there that these are turning out to be quite useful for a large number of people. I think in terms of like therapies that are interesting because they're impactful and accessible. I think sauna and hyperbaric oxygen therapy are two kind of interesting ones that they're pretty safe and available. And it seems like they do have very promising each other outcomes for a lot of people. So you can find probably in most neighborhoods, in most cities, you know, ways to do this. Either your gym might have it, or you might find a clinic that has a hyperbaric chamber that you can go to. I think the challenge is, of course, that you these things are. have parameters you can pick how long do you go there, what temperature do you ice certain things, for example. So just making sure that you have some evidence-based protocol around them, I think, is challenging. It's also kind of like a social component. Sauna is kind of interesting, I think, in that a lot of people are finding it's a place to go and socialize. And maybe instead of going to the bar, you might go to the sauna to hang out with people. So that's kind of a fun outcome. And then the last one I think for me is I'm a dog owner and I've been thinking about pets a lot lately. And I think pets in longevity are a very promising direction, a, because we care a lot about our pets and we want to do everything to keep them around. And also I think people are willing to try things out. There's a lot of missing gaps. We don't have good ways to measure our pets. We don't have as good wearables there's a few out there, but it's not a solved problem in the way that it is for humans. And yeah a lot of the challenges we have with sleep and exercise and diet. So I think personally that's one I'm thinking a lot about is how to merge those two things.

SPEAKER_00:

That's interesting. I have one last question for you today, Ryan. You've worked in the longevity space for a good few years very deeply. What do you think people are really seeking with these interventions?

SPEAKER_01:

That's a really great question. And I think it touches on a lot of very personal things for people. I think a lot of it is autonomy, that people want to have control over their own health and destiny. I think that resonates with a lot of people some people they want to be fitter happier more productive and all that. And some people really do want to live forever. Some people are serious about that mission. So I think it depends on who you talk to but I I think if I had to boil down at the core it'd be this idea of self-control and self-determination, which I think is a real part of it is being able to make choices and improve yourself and have the you know reigns on your life.

SPEAKER_00:

Ryan thank you so much for joining me today. It's been a really fascinating discussion. Oh it's been a pleasure thank you Jason