a16z Podcast - Healthspan, Lifespan, and the Biology of Aging

Episode Date: February 3, 2023

In this cross-over episode from Bio Eats World, Kristen Fortney, cofounder and CEO of BioAge, joins Vijay Pande, founding partner of a16z Bio + Health, and Olivia Webb, editorial lead, to discuss the biology of aging, how she started a company, and some fun things — like how long a hypothetical venture capitalist can expect to live. Resources:Greg Egan, whose writing inspired Kristen, has a list of his books on his website Stay Updated: Find us on Twitter: https://twitter.com/a16zFind us on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. For more details please see a16z.com/disclosures.

Hello, everyone, and welcome back to the A60Z podcast. We've recently had a ton of new listeners come in, so I first just wanted to say hello, and also welcome. If you're new to the show, I'm Steph, the host, and what we try to do here is cover the most important trends within technology alongside the people building it. And if you're just tuning in now, you've come at a great time. We've got some incredible guests and topics in the hopper, ranging from VR to hardware to how AI is reshaping everything from law to code. Plus, an upcoming episode with a very well. well-known founder, then I don't think you'll want to miss. But there is one episode that I'm particularly excited about, and it's about the state of the App Store. Look, Apple recently released

that they've paid App Store developers over $320 billion. Yes, that's B for Billion. And in this episode, we cover where things are, where they're going, but also how new founders can get involved. That includes a new age Beanie Baby app, a viral talking dog, an app from 2012 that finally broke the top 10, and a Chinese app that's been at number one for a majority of 2023. And let me tell you, that's not TikTok. All right, I'll leave the teasers there, but make sure to subscribe so you don't miss out on those new episodes dropping very soon. Moving on to today's podcast, we're sharing an awesome episode from our sister podcast, BioEats World, on the biology of aging. I know there can be a lot of judgments surrounding

the world of longevity, but it's hard to think of a more potentially impactful space on humanity. Living longer might mean having the time to write that book you've always wanted to, to found that company you've always wanted to build, or just spend more time with your loved ones. But also, imagine having another decade to contribute at your highest potential. Imagine what you could do. Imagine how that could reshape society.

And so naturally the question becomes, what if you knew what markers to look for in order to extend life? Well, in this episode, A16Z general partner, VJ Ponday, and co-founder and CEO of Bio-age, Kristen Fortney, discuss exactly that.

As a listener of this episode, there were several aha moments for me. But here's one that really gripped me. Kristen asked Vijay the following question. What if you could cure all cancers tomorrow? What would that do to the average lifespan? Now, I'm not going to give away the answer, but I want you to take a second and pause to think of your answer

before listening to the rest of the episode. No, really, go pause the episode and have a think. What would curing all cancers do to the average lifespan? All right, I hope you have your answer, and I also hope you enjoy this episode as much as I did. Look out for new episodes of the A16Z podcast coming this, Tuesday. Hello, and welcome to BioEats World, a podcast at the intersection of bio, health care, and tech.

I'm Olivia Webb, the editorial lead for Bio and Health at A16C. In today's episode, we talked with Kristen Fortney, the CEO and co-founder of BioAage Labs. You'll also hear from Vijay, General Partner, at A16Z Bio and Health. Together, we discussed how Kristen became interested in the biology of aging, how she started a company, the state of aging research today, and some more practical matters, like how long a hypothetical venture capitalist can expect to live. Let's get started.

So, Kristen, welcome to. of BioEats World. Thank you for joining us. Thanks, B.J. I thought we'd start off by talking a bit about your founder journey. The biology of aging and longevity is pretty unique space. And I think people would love to hear what got you here. I mean, that really dates back an incredibly long time. I've been really fascinated by science and science fiction and aging biology since I was a kid, really.

You know, probably reading tons of science fiction as a kid. Yep, yep. They too. I think that's important for a lot of founders that I talked to you, actually. Yeah. And actually, what was your favorite book as a kid? Oh, good question. I like a lot of Greg Egan stories, if you know him. They're really sort of like hard sci-fi.

I don't. Oh, you don't? Oh, you should check him out. We can link it in the show notes. I read lots of the classic stuff too. I'm pretty, I still read tons of the stuff. So, yeah. Yeah, so that got you interested in science.

And I think many of us had similar kind of backgrounds. So then what gets you on the path to doing it academically? You know, I was always reading about aging biology. I was always very excited about that in particular, because it seemed like it could have such tremendous potential for medicine, for health care, and it was still very new science. So I was always kind of like really reading from the outside. And as an undergraduate, I actually went into math and physics first, you know,

but I was always kind of reading about aging biology on the side. And then for my PhD, I decided that I wanted to get into the field myself. So I did a PhD in bioinformatics, but focused on aging biology, because that was sort of the quantitative skills that I knew, applied to the problems that I cared about. And at the time, I analyzed large data sets to build biomarkers and to repurpose drugs. And really, I was, like, brand new to modern biologies

of sort of really soaking all that up. Yeah. Well, especially, you're coming from a physics background. Was that a bit of a shift? Oh, definitely. It's a huge shift, right? Came in with lots of, like, unrealistic ideas, I think about how easy it was.

And then you sort of meet all the hard realities of, like, you know, biology is actually really hard, right? And we still know so little. There's still so much to learn. And then, you know, I started to become more, more fluent in aging biology and aging science and decided for my postdoc, I really wanted to join like an aging focused lab. There are still very few of those. So can you put us in time when both postdoc was roughly? Yeah, this is 2012.

And I came to an aging biology lab at Stanford. And what attracted me in particular was that they had samples from people who lived to be, like DNA samples, who lived to be over 100 or over 110, right? And that really excited me in particular because aging is so complicated, because aging is so difficult to intervene in, I thought that if we can learn what, you know, these people who are already aging successfully, what's different about them, that could be a really great way to figure out new drug targets. Genetics has been really important in other areas of disease biology with PCSK9, et cetera, right? So I wanted to crack at those data. And so I joined the lab, got into that. And, you know, over time, I'd been realizing that, like, what I really wanted to do was, like, develop therapies and, you know, impact lives, impact health, right? And realizing more and more that that's not, by and large, what happens within academia.

I mean, not for most people in academia. And so it was at that point where you really, did you ever consider staying in academia? Potentially, but, like, sort of got further and further from that. Like, I had a particular, well, thing I wanted to do, right? Like a particular project that seemed like it would be a great way. to find drug targets that was not an academic project, right? And that was what really led to the founding of bio age. And it really related to this idea,

and then that's kind of the idea that we're founded on, that there's going to be a lot that we can learn about how humans age by studying, you know, the 8 billion examples all around us, right? And we're going to learn a lot of pathways that can help people live healthier longer by, again, studying people who are already doing it. And that could unlock a lot of new biology, a lot of new target discovery, help us treat and delay disease.

and that was really the founding idea of bioage. Yeah, so it's roughly what time now we're talking 2014. This is 2015. Yeah, late 2014, early 2015. So you decide to start a company. What was that like for you? Because the first time anyone starts a company, it's a very new thing. What was it like sort of jumping in, and how did you even just get started?

Well, it's interesting, right? Because I did my PhD at the University of Toronto, and that's Canada's largest research university, but there's not a whole lot of, you know, young startups founded by students, founded by postdocs. And I don't know that that would have been like on my mental map at ice head. I remained in Toronto, right? And then I came to the Bay Area for my postdoc and Stanford and the Bay Area are very special environments. And you meet friends who are doing it. You realize that you can, you know, get to value creation for not too much money in the biotech world. And you learn more about how it's done and you have friends who are founders

and talk you through the process. The joke is that Stanford's an incubator with the football team. Yeah. Yeah, exactly, right? So I think that was really critical, just meeting some people who'd been through the journey before and understanding that it could be done and the precise mechanics of how it was done.

Like, that's so important to have that help early on that, you know, opened that door. Yeah, so you found the company, and how does the company come together? I mean, you get a co-founder. Yeah. And so Eric, when did you meet Eric, how does this actually come together?

Yeah, my co-founder, Eric, has been my friend. friends since high school. Oh, wow. Okay, I'd realize it. So we were both reading our sci-fi novels. I think we first met on the math team. Yeah, yeah. So it's been a very long relationship.

That's fantastic. Yeah, yeah. And he, you know, we both had actually shared an interest in aging biology. He'd gone down a career to get his MD. But we'd still always talk about agent biology, even collaborated on a paper together actually back when I was in grad school. So it was very natural for us to do something together. Yeah. So found the company, you get some initial funding.

Yes. And then you're off to the races. Yeah. Maybe we could fast forward a bit. How do you go from having the idea that, you know, aging biology could have an impact in disease to actually becoming a therapeutics company? The very first step for us was to establish that by looking at human biology, watching the process of aging unfold in the right human data sets, we could find compelling targets. As step one for us, the very first thing we did when we started the company, we located and found and negotiated with several very special biobanks. that started collecting samples from people, humans, when they were healthy and middle-aged, and these samples were collected as long as 50 years ago.

They had samples that were collected longitudinally throughout the lives of these people that were tied to health records with information on how long those people lived, the diseases they got as they aged, and also critically their health span. So, like, how their muscles aged over time, how their brain aged over time.

And this is what we really believed we needed this kind of data to understand aging because human aging doesn't happen overnight, you know, or doesn't happen. two weeks like a dozen the worms which we'd like to study in universities. I mean, otherwise, yeah, the company would have to be around for a couple hundred years to get some data, right? Exactly, exactly. Yeah. So the idea was that, you know, we could do what is basically a 50-year experiment, if we could get our hands on the right samples and analyze it in the

right way using modern technologies like proteomics, metabolomics. And why would they even have this data? Like, what were they thinking? That's a great question. It really like differs by biobank and sometimes it's really a case of like they started the biobank for one purpose and then like after they've been collecting sample and data for two decades like well now it's an aging study like some of them are actually like national level biobanks like with Estonia or Norway we work with those as well and it's more of a longer term collection process there yeah so these biobanks have blood or yes usually it is like serum and plasma because you know you're not going to get your hands on brain biopsies from healthy people so

You're more limited with the material there. Yeah, exactly. And the medical records. So you have some sense of how they're doing along the way. And the medical records. Yeah, that's really key. Okay. And so let's say you got that.

What do you do with that? Well, step one. So you have these really precious samples that 50 years old. They're incredibly rare. Like there's not a lot of biobanks like this out there. And then you want to know, like, what's in them, right? So you interrogate them with modern technologies, like the proteome, like the metabolom. And the idea is really just to make a really big list of all the different molecules in there.

And then you've got this huge data. out of molecules by people, by time, and there's a lot of very interesting questions you can ask of the data. One of the ones, for example, that we're most interested in is like what molecular markers, whether it's a single marker or a pathway, but what things can we see when you're middle aged that really predict the future of your aging, right? So what kind of pathways predict the difference between someone who goes goes on to live 90 plus in great health and their brain still works and their muscles are still highly functional

versus someone who only makes it to 270 or so. And that's really the starting point for everything that we do at BioAGE. We want to make a list of these molecular entities that are important for health span and lifespan and then drug them. Yeah, and just that whole process is really interesting because probably around the time of the Human Genome Project, it seems like biology shifted from pipeting and one-off experiments to database lookups and statistics.

And so you've got this enormous database with all this information, and now you can ask a series of questions. So I'm presuming you're asking what made these people that live longer, live longer. Precisely. Yeah. And so what did you find? Well, to take, you know, my favorite example, because it's the one where we just had a clinical readout, right? So we just had to, I'll get to that in a minute, but we just had a clinical data announcement.

But in one of our proteomics analyses, we discovered that there's a protein called apalin that circulates in your blood. And people, when they're middle-aged, if they have more apolin in their blood than other people, their age, that's highly predictive for both living longer, having better muscle when they were older and having better cognitive function when they were older in a linear way, right? So the more apline you had, that just seemed to correlate with better and better outcomes. And so that's how we initially got interested in this target. Interestingly, apilin was first described as what they call an exorchine. So it's actually something that your body produces more of on your own right after you exercise.

Very nice. Yeah. So it plates and the blood impacts on the muscle. So we got very excited about this. So people knew about it as an extra kind, but didn't know about its connection to aging. Yeah, longevity. Exactly. That's right.

Longevity and muscle function. Yeah. And so based on that, we tested out whether if we improved apolin signaling in older mice, if we could improve the function of their muscle. Let's back up a second because you were talking about human data all the way here. That's right. And now we're going to mice. Yeah, no.

I would love there to be like a day when you actually don't need mice anymore, right? You can go directly from human data to the clinic. And, you know, for certain hypotheses, I think maybe we're getting more and more there. You have all this human data, so like... That's right. Yeah. Yeah. Well, so this is one of the ways I think about it, right? Like, so you've got this sort of lifetime signal where more apilin is good for you. And that's great. That means that if you get enhanced apiline signaling for decades, that's good for you. But the separate question, which we're going to be asking in the clinic, is like, if you're already sick and we improve your apiline signaling, can we see a dramatic effect quickly that actually impacts on a disease?

and that's a very different question. It's sort of taking a system that's disrupted and trying to fix it by tweaking this one variable and seeing if that alone suffices to fix the condition. So I do think, I still believe that the right preclinical experiments can be tremendously derisking and value-creating as you move towards the clinic. Because, yeah, there are experiments that you would do with mice

that we wouldn't do with people. Yeah. And there'll be probably many areas of mouse biology that overlaps with human biology. Yeah, I'm sure we're going to miss things too, though, right? Like so much of what we do in aging biology is in vertebrates. A lot of it is in mice. And invertebrates, of course, are incredibly different from us.

We are not flies or worms or yeast. But even mice in the lab, they die pretty much exclusively from cancer, right? That is not true for humans. It's cancer, cardiovascular disease, right? I think we need to develop better models. But at least for those things that are conserved, I think this is a great approach. Well, and you'll have specificity. Maybe you'll miss some sensitivity for the things that are not in both.

Yeah, that's exactly how we think about it, right? We want to execute first on those targets with the most evidence that tick all the boxes. And yes, we might miss some that, you know, don't take all the boxes. But because there are so many targets emerging, we can still have a, you know, a big set we can move forward with with high confidence. Confidence that will work in humans. And that always seems to be such a big problem in biotech and that, you know, you've heard my old joke, like it's a great time to be a rich mouse. And so here you have some data that would suggest it would work in humans. Yeah, that's why we always like to start with you.

human data because you want to know that the pathway really matters there and compared to all the other pathways that are, you know, affecting the aging process, affecting the disease process. Yeah. Okay. So then you actually then put in humans. Then we put it in humans. We put it into various mouse models of muscle aging and saw a positive impact in several different models from sarcopenia to stem cell function to muscle atrophy. And we actually focused on the atrophy aspect for the clinic because that's where we saw the biggest effect size in the shortest window of time, which is exactly what you want to see in the clinic. So the particular mouse experiment that motivated our clinical design as we took some very old

mice and we put a cast of one of their arms. And after three weeks, you can remove the cast and weigh the muscle and it's undergone substantial atrophy. In fact, they lose close to half the weight of their muscle. And we saw substantial protection for those mice that were on the drug. And in fact, there was no significant difference in the muscle decline. so a really enormous effect size, and that really motivated how we built the clinical trial.

Did you give the drug prior to putting the cast on the mice? Yes, we did. It was prior. Yeah, so it was, exactly. So it was prior to the effect, yeah. And when we did our clinical trial, we based it on the same kind of scenario. So it's what's called a bed rest trial.

You know, sitting in bed is always bad for you. This is the part that I think most people would be shocked to hear. So 10 days of bed rest does what? 10 days of bed rest. Yeah, you lose about like 7% of your lean mass if you're past a certain age, right? And importantly, too, for a younger person to lose a similar amount of mass would take a couple of months of bed rest. So it's really dramatically accelerated by your age. But you do see substantial changes in the muscle. Usually these studies focus on the thigh. It's your biggest part, you know, the most stationary part of you. People are sitting in bed still eating, still watching TV. But their legs are very stationary and their thighs are large.

So you can look at the thigh muscle size, thigh muscle quality, thigh circumference. And we looked at all of those in the study and saw a significant difference, which we're really excited about as sort of the first proof of mechanism with a really clean story all the way from our human discovery platform through to some very nice, you know, in vivo mouse results and now to the clinic. And I guess you're off to the races as a clinical stage company. That's right. And next step would be phase two, phase three trials.

Yep, that's right. Yeah, up into next trials. Okay, so I want to switch gears a little bit, and especially where we are in this story now, why is aging such an important factor in disease? Or to what extent is an important factor disease? Like, why do you care about it? It's a tremendous risk factor, right? Like you can see, you can draw all these exponential curves of incidents

and also death due to all the major diseases, Alzheimer's, heart disease, diabetes. The list goes on and on. Yeah, so not a lot of 20-year Alzheimer's patients. Precisely, yeah, exactly. And at the same time, it's still like understudied as a contributor, right? Like a lot of the times when people study these diseases, they study them in young animal models that they intervene in. So they kind of looked like the disease state. But that is that is so very different.

Well, this is a really interesting thing that you have this colony of old mice. That's right. Yeah, yeah. And like it just, you've got to wait for them to get old. They're like three years old. Yeah, that's right. That's right. We have 7,000 mice.

And a young animal is so very different from an aged animal because, an aged animal is in this really frail state or it's predisposed to, like, even if it's not already sick, right? It's just much more likely in the next span of time to get sick than a younger animal. And we believe that by targeting those differences, the differences between old and young, we can, you know, treat, but also ultimately potentially delay age-related disease. Yeah. And so this seems to be a lot of diseases, right? I mean, it's, you said cancer, Alzheimer's. What sounds like what you're doing then is that you want to sort of understand biology of aging, get into market with certain diseases, but then these drugs could be used just more

broadly. That's right. That's right. And in some ways, you know, you can think of this as following like the statins playbook, right? Well, yeah, tell people about that. Yeah. What's that playbook? So statins today are a drug that you can think of them, they're prescribed as though

they were an aging drug, right? Like if you're over 40 and you have a couple of risk biomarkers, your doctor will give you a statin. They were actually first approved for an orphan disease, familial hypercalycelestrolemia, people who had genetically very high levels of cholesterol. And then they were found to be efficacious more broadly, and the label was expanded over time to be, you know, ultimately everyone, right? And I think those of us in the aging space where we're working on targets that have this amazing potential,

it's all about getting that first approval and then like widening to really get to all the patients as rapidly as you can. With statins, that took 20 years, you know, to go from that first approval to the sort of broad use and hopefully we can do better. Hopefully we as a field can learn to do better. But there is that potential that's been done before. It's not like, you know, a new way to develop drugs, yeah. So fingers crossed some of these drugs get across the finish line. Across the finish line in their first indications, these indications start to get broadened a bit. That's right.

And when do you think we start making this transition or how does this transition work from, oh, I have this drug for muscle atrophy to now we have ways to address longevity? Yeah, we've seen that start to happen already with some other drugs, right? a great example is perhaps metformin. So metformin is one of these first-line diabetes therapies. It's been used by millions of people over decades. And people did a retrospective analysis some time ago now and showed that diabetics on metformin were living longer

and getting less cancer than diabetics on other medicines or even then control people, right? Some caveats retrospective analysis, but really very exciting finding. And today it's actually fairly standard to get metformin off-label. You probably know people who are doing that. We have a lot of friends in common.

That's true. That's true for repomysin as well. And I mean, that said, that said, we as a field, I think, still need to, like, we don't know if it's going to make them live 10 years longer. That takes a long time to measure. But the field is coming up with better biomarkers. And honestly, we still need, like, real clinical trials of some of these as well. But it's interesting to put this in the context of companies or institutes that are going

straight after longevity. Yeah. What do you think that's going to look like? It almost feels like it's trying to make a tunnel by going from two ends. You can go from the specific indications and broaden them, or you could go after longevity more broadly. I mean, maybe it's worth talking, especially for the audience, something like the Amonaka factors. Yeah, it's like a cocktail of factors that can reset every cell to a younger state. And that's really exciting.

Resetting every cell to younger state. So what is that, like, what does that even mean? Well, people still argue about what that means. Yeah, yeah, yeah. And, you know, as your cells get older, there's a whole bunch of different things that go wrong with them, right? Your gene expression profiles drift. They accumulate gunk in them. Right.

They can go senescent, right? Yes, yes. And the idea is that this cocktail of factors can potentially rejuvenate them and rejuvenate each cell in your body. So what's perhaps unique about that approach is that it's like a, you know, a potential one-stop shop for everything, right? Like a master switch. Those factors, where are they in terms of given to animal models and so on? Yeah. So we're still in fairly early days. It looks promising from some of the short-term studies. We still have to definitively establish that it does increase animal lifespan. That's still, it's worth pointing out to, right? There can be risks as well associated with, you know, winding back the clock in these cells. If you do it too much, you might get something that looks like cancer. How does winding back lead to cancer? Well, think of it in this way, right?

Like senescence, for example, can be thought of as an adaptive process. Like, synessence is when a cell can no longer copy itself, make more of itself. And it becomes a very sick cell. And there's evidence in aging biology that actually eliminating senescent cells is really good for you. It's actually even specifically thought to be an anti-tumor mechanism. So you're starting to accumulate these DNA damage, and you don't want that proliferating, right? But then if you go and take one of these cells and rewind the clock and tell it and everything's normal now, go and multiply. That's a theoretical concern, I think,

but I'm actually pretty excited about the prospects there longer term. A lot of the early things that got people excited were those mouse studies were the... Parbiosis. Why don't you explain paramosis? Yeah, parabiosis is the very Frankenstein-sounding experiment showing that if you surgically attach a young mouse to an old mouse, that ends up being a good thing for the old mouse.

So blood circulates from the young to the old animal and back again. It's also terrible for the young animal. But the idea that that suggests is that there are either good factors in young blood or bad factors in old blood or some combination that can impact, you know, aging in multiple different systems. Yes, which is exciting. So in principle, that could be another process. Correct. Without Silicon Valley blood boys.

Or another way to find factors. You're going to have to bring science into this, aren't you? And so you find the factors, either the presence of the negative factors, or the absence of the positive factors and add the positive and try to remove the negative. Keep in mind in the mice, of course, they're all clonically identical, right?

There's going to be rejection issues when you have. They could, though. They could do the paribosis experiments with wild mice, right? Presumably. Oh, yeah, that's true. They could.

And they should. I mean, you could control against that. And, you know, there's some evidence, too, that if you just dilute old blood that can be beneficial, that was a more recent finding in the field that we expect to be. Yeah.

Just with salient or dilute in what way? Yeah, basically. And I read a convoy published that, I think, a couple years ago. And I think there's a couple of companies working now to bring that to the clinics. It's an easy thing to test. It's a very easy thing to test. Yeah, because this is sort of more the bad factor hypothesis, right? Yeah, yeah, yeah, yeah.

There's just some bad stuff in there. And if there's just less of it, then that's going to be beneficial. It's at least something that we'll know the answer to, I think, in a couple years. Yeah. So imagine you have this hypothetical case of, like, a 50-something Indian male. Purely hypothetical. It's really hypothetical. Let's say willing to sort of be on the leading edge, but not bleeding edge of this, you know, works out, like, eats well, and then we'll try some of these things as it comes.

How long would this person live for? Again, it's hypothetical. Yeah, yeah. Like right now, they probably, like, the median is, like, what, 8590? That's right. My general hunch about the field is that, you know, like at BioWage and everybody else working small molecules. These are sort of these easy levers that are going to add a few years of health span.

So I feel like that we're going to have a handlawn pretty soon. And I'd love to double click on health span versus lifespan. Yeah, for sure. I was just talking about age. But like, why don't you explain the difference? But yeah, the average, you know, lifespan in the U.S. is around 80 or so. The average health span is around 60. So lifespan is how long you live and health spend is how long you're healthy.

And then you start to get diseases of aging and you spend a quarter of your life accumulating those, right? And we in the field talk about increasing the health span, which means really the portion of your life that you remain healthy and free of disease. And we believe this is doable because some of the research I mentioned earlier where when you give a drug to a mouse, it lives longer, it gets its diseases later and actually spends a smaller proportion of its life being sick. And because also of the human examples, right, these people who live to be over age 100, them, their children, it's the same thing. It's increased health span, or they also call it, like, compressed morbidity. And that's what we would all like to have, yeah. Yeah, so in principle, even if the lifespan didn't increase, but the health span increased, that would

still be a huge. That would be huge, but honestly, they go together. Yeah, okay. But if you do delay the onset of disease and if you do improve health, you're going to extend lives too. Yeah. Yeah, one of the things that I always thought was really fascinating is that I was with a group of people and we were trying to think of, like, what's the most audacious thing we could

think about. Something so ridiculous would be embarrassed to tell people. And so I guess now I'm telling people. But I think, and so first is like, oh, let's try, it would be great if we could cure cancer. That'd be great, right? Or great if you cure Alzheimer's. But then like, okay, well, can we think for something more audacious? And the more audacious thing is like, cure all disease, right? And that just sounds ridiculous, right, on many levels. But for diseases that are sort of exacerbated by aging, if you can slow aging, maybe don't cure. disease, but maybe you greatly push back many, many diseases and maybe even diseases that we haven't figured out or differentiated as different types of dementias or whatever.

That's right. Yeah. Yeah. I mean, that seems like the ultimate future of this because it always feels like doctors are doing great job with heart disease. Yep. Now all these people are dying of Alzheimer's. Right, right.

The next bottleneck, right? And really the underlying cause for all of these is aging. There's actually a really good statistic related to this. People have said, like, what if you did cure all cancer? Yes. What would that do to average lifespan? again, it would add about three to four years, which is like underwhelming, right? Like, actually, I didn't even realize that.

Yeah, that's it. That's all you get because, again, most cancers are happening to older people. And just as you said, if it's not cancer or something else a couple years later, right? So it's really not making much of a dent at all. And in contrast, if we could, what we've discovered in mice translates to humans. Yeah. And you can slow aging to the extent we've already done over and over get an animal species. That's adding 10 to 20 years of healthy life.

Yeah. So that's the promise, right? and we're still in the early days, but that's what I'm very saying. So this hypothetical in the male might live to like 110 or maybe. Well, my feeling is that adding 10, like, I don't think that we're really optimized at all for aging. Okay, so we're very different from worms,

but I think there's a few things we can learn from worms. And one of them is that they've done this experiment where they've tried knocking every genome one at a time, and then how long does it live? How long does it live? Right? And the answer is that, like, actually, like, there's a whole bunch of things you can do to a worm

that make it live longer, you know? Like, it's not, it's not that hard. And like a lot longer, like 10 times longer, right? That's a bit more hard. That's harder. Okay, okay, okay. A bunch of things you can do have a fairly minor effect, but part of the lesson there is that, like,

there's a lot of different things that can work, right? There's nothing special. I don't think there's anything special about 80 years. I don't think we're really, like, maxed out there. And I do feel that we're going to get to the point fairly rapidly where we can add, say, 10 to 20 healthy years. As we're running out of time, I want to end a little on a philosophical note,

and then on a pick your brain on a personal note. So on a philosophical note, when I think about organisms and evolution, I don't think it's just about evolving any one of us, but evolving the ecosystem. And maybe we're supposed to die. You know, and like if we didn't die at all, that might not be so great for the ecosystem in a variety of ways.

Do you ever think about this philosophically? I mean, again, it's like, what's so special about 80 years, right? Like that just happens to be the age at which we die now. And, you know, the average life expectancy has changed, just in the last century, right? So, yeah, no, I don't think. That's a great point. So what was it like 100 years ago?

Well, it was like, I think, in the mid-40s, right? I mean, in large part due to sort of childhood mortality, but still, that's a big societal level shift, and we've borne it, right? Yeah. And Social Security being stuck at 65, I think the intention was that you weren't been, you wouldn't live that much past 65. Right. You know, and so that's just even in that period, it's a pretty dramatic change.

That's right. No, that's an important point, too, right? if we are extending healthy lifespans, that will be extending the work span as well, right? So that's a great point, yeah, and productivity span and possibly a different type of even person, someone with the wisdom of a 60-year-old and the sort of energy and body of a 30-year-old.

That's right. Is that plausible? I think that's possible in the longer term. And I think, you know, that's one of the things that excites me about aging too, right? Like, you know, what if you had, you know, just a couple decades to be in your prime, but like double that time.

Right? Longer time horizons, better planning. Like, there's good incentives there, too. It's an exciting, exciting future. It means I got a lot of work ahead of us, right? Personal part, if there's a team I, we can stay away from. But everyone always asks me, and so I'm curious to ask you, what supplements do you take? We should add this as a recurring feature to the podcast.

Yeah, yeah, actually, that's great. Yeah. So I drink lots of coffee. Coffee, yeah. Are you familiar with the retrospective analyses? Well, let's just start with coffee. Yeah, so what's up with coffee. So, I mean, it's funny that people talk about it as though it's not healthy because the evidence is strongly in the opposite direction.

And these are just retrospective analyses, right? But drinking more cups of coffee every day is very protective. So in many different retrospective analyses in large populations. When you say more, like more is better? Like infinite is better. Well, I think in these studies, they went as high as like five cups a day. But that's not very many cups. Well, you have to have enough people in your population that are doing it to sort of actually know the answer.

You're right, five is not that much. Yeah, I routinely do seven to ten. Right. measuring cups, cups. Yeah, sure. Yeah. But yeah, more is more protective for cardiovascular mortality and for all-cause mortality. And that's like a really nice association. And coffee is delicious. So, yeah. Okay. Okay. So that's already, you made a lot of people happy just right there. Any other supplements you want to talk about? I don't do supplements yet. I do intermittent fasting. So let's take each one in turn. So is there a reason why you don't do the supplements? Because, you know, K-O-L in the space of aging and, like, other KOLs take a ton of stuff, you know. That's fair. I mean, you know. So no metformin, no.

So metformin and rapamycin are both on my list of things to try, you know. And I haven't started yet, but I will soon. Yeah, that's right. Yeah, maybe you're too young, too. I don't worry about this. But then interim fasting. So what do you believe about that? Well, I do the lazy version of that, right?

Where a couple days a week, I have dinner. I typically skip breakfast, but not skipping lunch is kind of hard. Well, it'll be interesting to see what you end up doing. We'll do another podcast in a few years. As I age. As you age. Oh, yeah, one final question is that the biology of aging is relatively a new field. Yes.

And longevity is a new area. One thing is that always strikes me. Another question people ask me is, how come everyone in the aging field are so young? Yeah, no, it's true. Partly because maybe because it is a new field, right? So you need, it's a bit different from what's been done before. A lot of it too is people coming in from the science, right? And so they are younger.

You don't have people coming in who are like ex-Barma experts in aging because there aren't any, right? So maybe I'll end with this. So there's all these people in tech that are very excited about longevity and actually also interested in getting into life sciences of health care. Like what advice would you give them for transitioning? I think a really good way is just to go to conferences. I think it can be really helpful to, like, wander around a poster session and really engage with scientists on their science. It's so important to figure out, like, what, you know,

you read in the literature is real and what is not real at all and what is, like, you know, very on firm ground or shaking ground. And you really can't tell that from, you know, the paper abstract, you know. Right, right. Yeah, no, you get the real. Yeah, so learn to decode that language and what's trustworthy and what's not and what's promising and what's not and what's, sort of exciting but very far from translation.

I think you have to learn how to read papers and you have to learn to just meet the people and engage with people. And if you go to conferences, people are very friendly. And I think they're always excited to have more people in the field. Definitely, yeah. Thank you so much for being on BioEeds, World.

Yeah, thanks, BJ. Thank you for joining BioEats World. BioEats World is hosted and produced by me, Olivia Webb, with the help of the bio and health team at A16Z and edited by Phil Hegesa. BioWeeds World is part of the A16Z podcast network. If you have questions about the episode or want to suggest topics for a future episode, please email BioWeetsworld at A16Z.com.

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