Finding Targets for Aging Interventions


Kristen Fortney

Co-founder and CEO of BioAge

Kristen Fortney is the co-founder and CEO of BioAge, a clinical-stage biotechnology company developing a pipeline of treatments to extend healthy lifespan by targeting the molecular causes of aging. The company uses its discovery platform, which combines quantitative analysis of proprietary longitudinal human samples with detailed health records tracking individuals over the lifespan, to map out the key molecular pathways that impact healthy human longevity. By targeting these pathways with a large and mechanistically diverse portfolio of drugs, BioAge is unlocking opportunities to treat and prevent diseases of aging in entirely new ways. Kristen’s scientific background is in aging biology and bioinformatics. She received her PhD in Medical Biophysics from the University of Toronto, followed by postdoctoral training at Stanford University, where she was a fellow of the Ellison Medical Foundation & American Federation for Aging Research.

Episode transcript


What we are able to do is go into these samples and interrogate them with modern technologies, like proteomics, you can look at 7000 proteins now in a human blood sample, thousands of metabolites. Right. And just ask this big sort of data, first question, what’s changing with aging? Of course, but also what predicts the future? 


Aging. Like gravity, it pulls on each of us. Why do some of us age without illness? How do our bodies and minds experience aging at the cellular and molecular level? What’s the future of aging in our society? And maybe most importantly, what can we do about it today? My name is Gordon Lithgow and here at the Buck Institute in California, my colleagues and I are searching for and actually finding answers to these questions and many more. On this podcast, we discuss and discover the future of aging with some of the brightest scientific stars on the planet. We’re not getting any younger, yet!



Gordon: Hi everyone. Welcome to the show. Today I’m delighted to have Kristen Fortney on. And, I’ve known Kristen for quite a few years now. All the way back to her days at Stanford when she was a postdoc. Kristen was really quite, quite unique in coming out of that postdoc, in the sense that she immediately realized the potential for the aging research space and was also very entrepreneurial and wanted to go ahead and get in there and form a company. Kristen is the CEO and co-founder of Bioage. Kristen’s company uses human samples and health records to develop targets for interventions. Kristen has been very much in the eye of the scientific community as a shining example of how we can move from the basic science into a successful start up company and beyond. 


Gordon: Welcome, Kristen!  

Kristen:   Thanks, Gordon, for having me. It’s always great to chat with you. 

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Gordon:  You know, we know you as one of the superstars of the aging community in biotech. I mean, in all the, you know, scope of biology, botany and marine science and everything else, how did aging come to be the thing that fascinated you?  

Kristen: Yeah. I mean, I-I guess, so, personally, I’ve-I’ve never been, I guess, a science for science’s sake person. It’s more sort of like, “What can we do with these tools?” And so, um, biology and its impact ‑‑ and medicines, right, and the impact on healthcare were always very exciting to me. And aging, like, as you know, right, like, it underlies so many different diseases. It’s like, uh, a master key in some ways that can unlock a lot of different benefits in human populations, and it’s also very understudied, right? There’s a lot  of really exciting new work to be done there.

Gordon:   So BioAge Lab is really based on your computational biology experience. And at the outset I guess you had some strong ideas about how to find targets for interventions in aging. So maybe-maybe you can talk about that.

 Kristen: Yeah. So  zooming out a little bit, if you look at, like, the kind of data sets that have been really transformative for biotech in general in the last 20 years ‑‑ and it’s the right human data sets, right? So the large biobanks, like UK Biobank, like deCODE in Iceland, which Amgen bought a few years ago, um, and mapping out, you know, the different molecular pathways in large human cohorts, the different genetics in large human cohorts ‑‑  I think, you know, people  have shown that, if a target has what they call genetic evidence in a human population, it’s much more likely to be successful in the clinic, and it saves so much time and so much money. And part of the rationale and the impetus for BioAge is, like,  what’s the version of that human data for aging?  And if anything, I feel like it’s even more sorely needed in the aging field, because it’s such a new science, right?  And you have ‑‑ like I feel like a lot of human aging is still a mystery, right? So it’s already been valuable ‑‑ for these fields where we have a much deeper knowledge of the mechanisms and the science, like CBD or cancer biology. Um, so-so we-we went through the exercise of, like, what ‑‑ you know, it-it’s ‑‑ you  data sets for two different things, right?  Data sets that, one, can help give us conviction around those mechanisms that work in model organisms, because that-that will also translate in-into humans the sort of translational knowledge. And, two, um, target discovery, novel target discovery in humans, because a lot of ‑‑ you know, I believe that a lot of the pathways that matter to aging are still undiscovered, and that data sets like-like the right, you know, genetics and proteomics data sets can help uncover important new targets. And so our approach at BioAge was really to capture molecular changes over the lifetime. Like, this is one of the reasons why it’s so hard to study, uh, human aging in a lab, right? Because it’s a 50 year experiment, it’s not possible! You know, even if you want to do a mouse lifetime experiment, that’s the length of a PhD. You know, if you’re lucky ‑‑ ‑ it-it works. [Laughs] Um ‑‑

Gordon:           I know. It kills me ‑‑

Kristen: Right?

Gordon: ‑‑ the length of those experiments. Yeah.

Kristen: Right. [Laughs] Um, and so there are a small number of very forward-looking biobanks that started to collect sample from healthy, middle-aged people, you know, close to 50 years ago and then followed up those individuals throughout the rest of their lives with health records on of, you know, how long they lived, the diseases they got as they aged, and also, critically, like at our favorite biobank, um, health scan variables. Like, every few years they’re looking at walking speed and grip strength and cognitive function, over decades. And what we are able to do is go into these samples, these really precious samples that have been conserved for decades, and interrogate them with modern technologies, um, like proteomics- you can look at 7000 proteins now in a human blood sample. Uh, thousands of metabolites, right? And just ask this big sort of data-first question: what’s changing with aging, of course, but also, what predicts the future, right? Like, if you look at the molecular pathways in a middle-aged population, what differentiates those individuals who go on to live, like, 90-plus with really functional muscle from those who don’t, and use that as a starting point for, um, for all of our science. 

Gordon: Did it shock you that recent studies have shown that variation in human longevity is basically not genetic, or a very small portion of it is genetic? Was that ‑‑ was that a surprise? And then, you know, you just mentioned proteomics and metabolomics, do you have a preference for what data sets you think are going to be the most predictive?

Kristen:    It’s not a surprise that common genetic variation doesn’t explain much in normal human lifespans, right? You do see that explanatory percentage get higher as you look at more and more extremes. And keep in mind, too, that, if you’re going to do a genetics project, then  you don’t need the trait to be explained by, um, by, like, one or two genes in a very, uh, large population. Like, a great example is PCSK9, right? Like, this is, like, a blockbuster heart drug. And they found it by ‑‑ you know, they found this target by, uh, by human genetics. There was a family that had rock-bottom cholesterol levels, and they had basically PCSK9 knocked out. Like, is that gene that important population-wide? No. But is it a wonderful target for the rest of the population? Yes, right? So I do ‑‑ I-I ‑‑ you know, I’m defending the genetic approach here to discovery. Like, I still think that, if you look at longevity, exceptional longevity in certain special populations, there will be very interesting targets emerging from that, even though that’s actually not our focus at BioAge, because, in order to do that, you need to sequence lots and lots and lots and lots of people, right?

Gordon: Yeah. Yeah.

 Kristen: And so our-our approach is a bit different, which is what you touched on, which is, um, looking at these more ‑‑ these omics that vary over time, that vary over the lifetime, right? Like, your genome, whether you’re 8 or 80, it’s the same, mostly.  Um, but in contrast, your proteome changes very much as a function of age and changes, you know, in similar ways right across populations. So you can actually have a lot of power in a proteome, and so we really look at these more sort of common changes that unfold in human populations. And one thing that I especially like about these omics that change through time is that they integrate, um, genomes in the environment, right?  So, like, just to take  an example, like a ‑‑ like one path we were really excited about at BioAge is apelin signaling. And in our cohorts, you know, middle-aged people who have really active apelin levels, they’re living a lot longer. They have functional muscle a lot longer. Now, you know, maybe they were born with genetically high apelin, or maybe they just exercise a lot, you know? Or maybe they eat the right foods right? But whatever it is, right, the molecular intermediary is the apelin, right? And that’s ‑‑ and that’s the drug target. So some way I ‑‑ yeah, I-I agree that, like, uh, environment brings a lot to longevity, too, and I like ‑‑ I think that you can see that reflected at the molecular level.And you can, like, use that to help ID targets as well. Yeah.

Gordon: So  proteomics, which is really the analysis of-of all the different proteins in our cells and tissues and the states of those proteins and the level of those proteins, is very important technology right now, and I-I think many, many people are-are applying this to aging. Um, and then there’s metabolomics, which is the-the small molecules, the metabolites in our tissues and cells  and plasma and blood and so on. And you-you would imagine that the proteomics, because they’re the enzymes that do the work in the body, are generating the metabolites, and so I’m wondering if-if, in the end, the metabolites will be the thing that  we look at and we don’t need to do the proteomics anymore, because they predict the metabolites.

Kristen: Yeah, I think that that’s really interesting, right? Like, where we are right now is I think we’re limited by measurement technologies, right? So if you go into a human blood sample, for example, there are technologies that will look ‑‑ let you measure 7000 proteins, right? But for metabolomics, you can measure and name maybe only around 3000 metabolites. So-so, in the future, maybe, you know, we’ll have, like, a more, uh, you know, fundamental layer of understanding that we can use to model other ones, but, um ‑‑ and it’s going to be really interesting to see how that evolves, but currently our favorite modality is probably the proteome.  Um, and part of the reason for that is just that we have so much understanding around proteins, right?  So if you see a  protein signal that’s very predictive, then you’re not starting in a vacuum of knowledge, right? There’s actually a lot of information about this protein. It’s probably been mutated in a mouse and-and just ‑‑ you know, it’s been described what happens. Maybe even someone tried drugging it for something, and there’s this whole, like, rich literature you can access. I think there are going to be metabolite targets, methylome targets. I think those are harder targets to start with.


Gordon: Let me take a step back and go back to muscle again. This is obviously one of the major interests with, uh, BioAge Labs. And so describe what happens with muscles with age. I just walked up the stairs there and I felt ‑‑ I felt that my legs were a little bit shaky. And I thought, “My goodness, what’s that all about?” And I exercise! But still that was happening…

Kristen: Yeah. We-we focus on muscle, and it’s-it’s one of the ‑‑ one of the universals of aging, right? Like, we all lose muscle mass as we age. We all lose muscle function as we age. And this drives a lot of poor outcomes and a lot of suffering. Like, it’s the number one predictor for frailty and sarcopenia, and when you lose independence, that’s when you go into a nursing home. You know, that’s-that’s when outcomes become very poor. Um, we think it’s a ‑‑ it’s-it’s very important to treat muscle and help ‑‑ to help extend the health span.

Gordon: So  frailty obviously is a spectrum of different-different types of, uh, you know, aging conditions. Is that something that you can, uh, you know, derive patents around and get FDA approval for? Is frailty itself an indication?

 Kristen: That’s a great question. I think it should be. I mean, the muscle space is really interesting. I’m not sure, um, if the audience is familiar, but I can give a bit of context there. Like, 10, 15 years ago, um, large pharma did have, um, departments focused on muscle, right? And they were taking things forward, like myostatins, like-like SARMs, selective androgen receptor modulators. And the challenge was they weren’t looking even at frailty. They were looking at things like cancer cachexia, which is related, right? Um, where it’s muscle wasting. And the challenge was actually a regulatory challenge. So FDA   acknowledged these were real indications, you know, which they haven’t yet for frailty. [Laughs] Um, but, you know, the endpoints for these indications to get approval were things like ‑‑ were functional endpoints, which, you know, they kind of have to be for muscle, so far. There were things like the six-minute walk test. And there’s a number of-of challenges, like this is ‑‑ this is such a noisy thing to measure. Um, like, it’s a very, you know, center-to-center variable, uh, administrator-to-administrator variable, how you feel on one day versus another variable, right? So that they’re actually very challenging endpoints to hit, and that’s-that’s one of the important reasons that the field… that muscle departments were shuttered and programs were closed, right? And so I would love frailty to become an indication, and part of that, though, is having, like, better-better endpoints, right? Endpoints that are easier to hit ‑‑

Gordon: Yeah.

Kristen: ‑‑ in the ‑‑ kind of the context of a clinical trial to really see ‑‑ and we’re starting to see a bit of a muscle renaissance just in the last year. Um, I ‑‑ so I ‑‑ you know, one of these old myostatin drugs, the one that Novartis discarded some time ago, got brought into a company called Versanis, this is a great example, and they showed that it’s actually helped with healthier weight loss in an obesity context. I’m really excited about this because I think that, uh, pharma is turning to muscle again. So what’s actually really interesting ‑‑ I’m getting a bit into the weeds on indications now, but there are ‑‑ you know, there’s these blockbuster weight loss drugs that didn’t used to exist, right? Things that are in the news every week, like Wegovy and Mounjaro. Um, people lose a lot of muscle on those drugs as well. And what-what companies are starting to realize is that, if you pair one of these weight loss agents with a muscle drug, you have the potential for healthier weight loss, but you also-also have the potential for more weight loss, because muscle is metabolically expensive, so it’s kind of a to return to the earlier point, you know, um, the-the regulatory endpoint for these types of drugs is weight loss itself, right? So if you could take your muscle drug, plug it into an obesity drug, and now the bar is a different bar. It’s not this very challenging functional endpoint bar. It’s a weight loss bar. Um, suddenly, like, there’s a lot more development possibility. So there’s actually, I would say, a reawakening interest in muscle, which is, I think, good for the field. In fact there’s lots of aging mechanisms coming from there. Yeah. Bit of a pharma detour, but ‑‑

Gordon: No. No, no. That’s great, actually. What keeps you awake at night? Is that the day-to-day science, the drug development, or is it the ‑‑ this sort of regulatory framework and landscape that you need to navigate?

Kristen: I mean, it’s all plugged together.  These are all hard problems, right? Like, the science has to work and be meaningful. The drug has to be safe. There has to be a way forward, you know? Like, no one’s going to want to pay for you to develop your drug to take it into human populations to show that it works if you can’t sell it at the end of the day. So there has to be a very clear understanding of how that’s going to work and why there’s going to be interest.  And-and that’s ‑‑ and that’s sort of where we are now, right? Like, I-I-I would love to see frailty approved as an indication. I think, even if we just restrict ourselves to these functional endpoints, if you look at things like-like wearables, right, the Fitbits or Apple Watches, you might be able to get more robust functional metrics. So I think that that ‑‑ or I think there’s a lot of other routes that are, you know, being developed in parallel that might help unlock more possibilities here. Yeah.

Gordon:   Do  you have days where you-you clearly see? You’re looking at the data, and of course there’s a lot of noise, and aging data has a lot of noise. Is there particular days where you go, “There’s the signal. There’s the target”?

 Kristen: I mean, you know what this is like, right? [Laughs] So there’s sort of the cautious optimism when, like, one thing works, and then, like, you know, you try it another way or, like, a different-different type of experiment altogether, and, like ‑‑ and it works again, and it’s like, “Oh, that’s interesting.” [Laughs] And then there’s, like, the rare times when ‑‑ uh, you know, and that’s-that’s what it looks like when something does work, right? It works over and over again, reproducibly with large effect, across models, and then, and then, and then, you know? Then you’re set, right? Those are rare. Like, those are rare moments, right? A lot of things  look promising and, you know, don’t translate across different conditions, or the effect size isn’t meaningful enough. Um, but-but yeah, when you ‑‑ when you ‑‑ when you have ‑‑ I mean, you know,  we’re still early, right, but, uh, there are things that I think are very exciting.  

Gordon: Fantastic. Um, I ‑‑ you know, this is, uh, uh, uh, I guess this is a question for me. [Laughs] Um, when-when, um, you mentioned model organisms earlier and you mentioned mice briefly and things. How much does this factor into your-your calculations about drug development? I mean, it seems you-you need to have mouse data to get a patent in the first place. And we know that the mouse models are not-not optimal, by any means, in terms of studying functional aging. What’s your framework for that, and what’s your company’s framework for-for model organisms ‑‑ model organisms work?

Kristen: You know, we do a lot of discovery work in our human data sets, but then, yes, you have to ‑‑ like, even if you know ‑‑ even if you believe, like, you have, you know, Mendelian randomization, causal genetic evidence, there’s still the separate question of, if I take a sick person and modulate this pathway in the short term, will that suffice to really modify disease, right? So  there’s still, I think, a really important role for disease models, animal models. Um, the way that we focus on this at BioAge I that we do have, um, an aged colony.  And we like to focus on things that naturally go wrong with these animals, you know ‑‑ it ‑‑ with the idea that that’s going to be more translatable. Things that go wrong in these animals in the same way they go wrong in humans, right? So for example, like, mice ‑‑ old mice on their own will never die of heart disease. Old mice on their own will never develop Alzheimer’s. So those, you know, preclinical models we-we don’t really use, right? But the old mice, like us, they lose muscle mass. They don’t run as well in their wheels, right? That’s one of the reasons we like muscle aging as well. We believe that we have more access to translational models that are naturally aged, you know, which we believe a bit more, you know?  

Gordon: Um, you’re describing de‑risk. Could you just give a very general explanation of what that means?

Kristen: Yeah, for sure. So, in drug development, in biotech, basically, everything takes a very long time, and every step is more expensive than the prior one. [Laughs]

Gordon: Yeah.

Kristen: So if your ‑‑ if your target, you know, that you discovered in mice isn’t going to work in humans, it’s not going to be efficacious, you want to, like, you know, know that as soon as you can. You want to know that before spending, you know, $10 million on a phase II trial. So if you can de‑risk, you know, quote/unquote, that sort of means looking at a whole host of things that might make your-your program, you know, less likely to be true. Um, so there’s de‑risking from an efficacy perspective, but ‑‑ and de‑risking from a safety perspective, right? That just ‑‑ you want to have ‑‑ you want to sort of be able to have as many early looks as you can to sort of be sure that you’re on the right path. 


Gordon: So  let me just finish by asking you, you mentioned the ‑‑ of course, that the-the omics, the metabolomics and the proteomics, capture exposure to environment, and this is becoming a big thing, right, that really our entire life experience of the environment, everything we do, everything we eat, the air we’re exposed to, the environmental toxins we’re exposed to. The exposome is a vast, unstudied area and is also ‑‑ it’s almost completely impossible to think about how to study it! And maybe it doesn’t matter. You know, if you develop a drug and you show it’s effective in a certain group of people, and that-that’s fantastic. And that-that’s ‑‑ but   do you think about the need to, um, study diverse groups of people who have been exposed to different risks throughout their life and even maybe their parents’ life through epigenetic mechanisms?

 Kristen: I feel, I guess ‑‑ I guess we’re looking for, first, you know, those mechanisms that are going to be translated broadly, right? You know, And if you can think of us more as, like, you know,looking  in contrast to looking only in inbred black sex mice and comparing some young ones to some old ones. [Laughs] Even if you were to only go to, like, one human population, you’re still adding vastly more genetic and environmental variability. Um, we have, I guess, right now, sort of, uh, a few different ethnicities covered, you know, but it’s more like 10,000 people, not-not millions of people, right? So there is  probably a lot more to discover as you add on more diversity. Um, and I-I ‑‑ especially for particular paradigms, right? Like, there are some people who are incredibly stress-resistant. There are some people who, you know, eat a terribly unhealthy diet, but, you know, live really long and healthy, right? So I think there’s a lot of different types of discovery paradigms that could, uh, be fruitful. Yeah.

Gordon: And I presume you’re very conscious of gender differences well in drug development and, you know, what we can do there to improve that situation.

Kristen: That’s been a big one in aging biology, right? It’s frustrating. It would be nice if things worked really well on both, but so far there have been quite pronounced differences, yeah, in genders. Yeah. That-that’s an interesting one.

Gordon: Hmm. Um, well, I’ve got another final question. Where do you see BioAge in 10 years’ time, and where do you see the aging field in 10 years’ time?

Kristen: Uh, yeah. That-that is a very hard question, but, you know, I would like us to have, like, uh, an approved drug, you know, ideally a couple, right? I would like us to be testing other mechanisms, and the field as a whole you know, I think we’re in an interesting spot right now. As we were discussing earlier, there’s sort of more activity in terms of translation than there’s really ever been before. It’s, again, still early days, right? Like, you can draw a map of the clinical pipeline for aging, and, you know, if you look at things that are near IND or in human testing, there’s maybe 20 or so things. That’s a big number. And until you look at, like, the pipeline of a Novartis or a Lilly, where they’re ‑‑ they have, like, 120 different things in the clinic, right? [Laughs] And that’s just one company, so. There’s still a lot of room to grow, and I think there’s a lot of very exciting mechanisms that are, you know, in or near human testing, so I think the field is going to be changing rapidly, like, expanding rapidly.

Gordon: Is that a problem of…of academia not coming up with the interventions? Is that a problem of not enough aging companies yet?

Kristen:  All of the above. [Laughs] And, uh, you know, and really, like, funding for ideas, too, coming out of aging biology, right?  It’s still, uh, a new field to-to biotech. It’s still a new field for pharma. Once we see ‑‑ start to see some of the first successes in terms of molecules that make it over the line, I think we’re going to see a lot more spending in this area, right, which-which hopefully ‑‑ like, I-I believe there’s a lot more mechanisms to discover, but I also believe that, like, there are a lot of things that are ready to be translated that haven’t been yet, right?

Gordon:  In-in thinking about the future, what ‑‑ if we get outside of ourselves, outside of the aging bubble, um, what do you expect the layperson or, you know, anyone-anyone who’s experiencing aging and seeing horrific things happen within their families with Alzheimer’s and cancer and so on, what-what would you hope that they start to see or hear about this field?

Kristen:   Well, in terms of what they see ‑‑ you know, like right now, as you grow older and you think about what medicines are really available for preventing disease, instead of treating disease, and and there’s not many, right? Like, I would put statins in that category. Most people, after a certain age, start taking those. But I think that that’s-that’s really the ultimate potential of these aging medicines, right? Like, I-I would like to see that set of options widen, um, where they actually have that potential to delay disease, and at the same time, more awareness right now, right? Like, we discussed muscle aging, and that’s, in a way ‑‑ like, that-that-that’s horrible, but, you know, I-I-I want to keep my parents out of a nursing home. Like, that’s-that’s a scary outcome, too. That’s a terrible place to be. Um, and just recognizing that, you know, there are ways, there is science that can help. And, you know, there-there are ‑‑ we ‑‑ there should be more attention focused on this, so that I think the society should sort of shift focus that way. I think now, like, people are past a certain age, you know, and you go to the doctor, right, they’re like, “Oh, sorry. You’re-you’re old,” right? And-and I think we can  do better. 

 Gordon: Yeah. Kristen Fortney, it’s been an absolute delight. Thank you so much. You’re, uh, a real pioneer in this field in-in taking us towards translation, and you’re also a very generous communicator of-of what you do and what your company does, so thank you for taking this time with us today.

Kristen:    Thanks so much, Gordon. I really enjoyed it.


Thank you so much for listening. Please subscribe, share and give us a five star review on Apple, Spotify or wherever you get your podcasts. We’re Not Getting Any Younger, Yet! is produced by Vital Mind Media: the Buck Institute’s very own Robin Snyder as the executive producer, Wellington Bowler is right next to me here directing the recordings, Stella B is behind the scenes ready to debrief when we wrap, and the esteemed Sharif Ezzat weaves the show together for you. 

If you’re listening to this podcast, you know that there’s never been a more exciting time in the research on aging. Discoveries from our labs or moving into the clinic to help us all live better, longer. The Buck Institute depends on the support of people like you to carry on our breakthrough research. Please visit us at Buck Institute dot org to learn more and to donate.

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