Rethinking Longevity from Diagnostics to Longitudinal Care with Radence

Speaker 1:
Welcome to TD Cowen Insights, a space that brings leading thinkers together to share insights and ideas shaping the world around us. Join us as we converse with the top minds who are influencing our global sectors.
Dan Brennan:
Welcome to TD Cowen Insights. I'm Dan Brennan.
Over the last several years, we've seen a dramatic rise in consumer interests around longevity, preventative medicine, advanced diagnostics, and personalized healthcare, but separating scientific reality from marketing hype can sometimes be challenging. To help us navigate that landscape, I'm pleased to be joined by Dr. Julie Chen, who's a chief medical officer at Radence. Julie is a physician scientist whose career has spanned clinical research, genomics, precision medicine, and longevity-focused healthcare, including leadership positions at Human Longevity, now Radence.
Today, we'll explore how longevity medicine is evolving, what's truly actionable in early disease detection, how Radence approaches prevention across cancer, cardiovascular disease, neurodegeneration and metabolic health, and where Julie believes medicine may be headed over the next decade. So with that introduction, Julie, welcome to the podcast.
Dr. Julie Chen:
Hi, Dan. So nice to be here. Thank you for having me.
Dan Brennan:
Terrific. So maybe starting high level here, longevity's gone from what I would consider maybe a cottage industry, which has started to gain a lot of attention with the sequencing of the genome nearly 30 years ago, but I feel it's really started to move into the mainstream today with consumers being far more proactive, seeking to take their health status and outlook into their own hands. To kick things off, Julie, what does the term longevity mean to you and to Radence?
Dr. Julie Chen:
Yeah, so longevity is something that's frequently used and has very different meanings depending on who's saying it, what companies. And I think ultimately what people, the listeners, should be thinking about is how does this truly impact health span? And it's not so much about adding years at the very end of life, it's about protecting healthy years and keeping people functional, cognitively intact, and independent for as long as their biology allows. So practically, longevity means practicing medicine along someone's trajectory rather than waiting for the moment of diagnosis.
So at Radence, it's really about a genomic precision medicine, where we personalize the diagnostics in a way that we can risk stratify someone, but not just from the data, but really taking the data and looking at which specific risks to each individual are important, and then where do we intervene and where do we monitor? So it's really about also taking the data and knowing what to do with it.
Dan Brennan:
Terrific. And we'll certainly dig into Radence throughout the podcast, but maybe before we go there, so if we zoom out and think about the different types and categories of technology, blood-based testing, MRIs, portable EKGs, there's many others, and different service models that are seeking to address this longevity market, how do you think about per se the market structure today for companies in longevity, and how and why is it evolving?
Dr. Julie Chen:
Yeah, so the market organized itself around, I would say, predominantly a lot of these diagnostic modalities. It's a company here does blood, an imaging platform there, but that's what was fundable and, I think, easy to sell to consumers for people to understand potentially initially. But what's really going to move the needle on health span and longevity is about how the technology can be used together and to look at it from the perspective of how it can then provide the data for the best clinical judgment so that on any given person we know where the predictive and preventive factors are that can truly help someone optimize their health trajectory.
Dan Brennan:
Terrific. Okay. So maybe now that we've kicked it off a little bit, would love to give me and the audience an introduction to Radence, where you fit in the longevity market, and the problem that you're trying to solve that traditional healthcare largely doesn't.
Dr. Julie Chen:
Yeah, so Radence is a longitudinal genomic precision medicine practice. It's not just a diagnostics testing company, and it's important to really think about a full integration vertical stack for how we can really move someone's health optimization. And the way to do that is to build a deep multidimensional baseline for each member, follow how it changes over time, and stay accountable for the whole path. From identifying a finding to interpreting it, getting the right specialist involved and making sure something actually happens, traditional healthcare isn't really structured and built to do that when it's organized around annual visits and episodic testing. So we want to move it away from just looking at existing disease, but also into a more preventive and predictive modeling of identifying the factors that really impact health span.
Dan Brennan:
Terrific. So that's a good jumping-off point in terms of how Radence is organized around catching these diseases early before they become symptomatic. So where do you see the biggest opportunity today to have the biggest impact? What disease states? And how is Radence particularly positioned in those disease states?
Dr. Julie Chen:
So cancer, cardiovascular disease, metabolic disease, and neurodegeneration drive the majority of long-term risk. And we've extended our program to cover also vascular and aneurysm risk, autoimmune and GI, as it can have a multiplicative impact on the other four silent killers of the heart disease, metabolic cancer, and neurodegeneration. And what positions us isn't the owning of any given one test, it's having a defined protocol for each domain, and then the serial trajectory longitudinal measurements so we can see change rather than snapshots and a vetted specialty network so a finding turns into actual care rather than just a data dump of PDF files.
Dan Brennan:
So Julie, Radence has evaluated many emerging technologies, and you've done so, I'm sure, throughout your whole career. What framework do you use in deciding when a new diagnostic technology is crossed from something that's promising science into something that you can confidently use in patient care?
Dr. Julie Chen:
Yeah, so I usually ask three questions to really create this concept of scientific standard of care. The question is, does it measure something real? Is it reproducible in an asymptomatic population for early screening? Those are the first. And then does the result change what a clinician would do, and is that change more likely to help than the downstream workup could be harmful? So when that concept of being able to make a change and the fact that there is true benefit in the optimization of overall health span trajectory, that's when we know that the technology is able to be utilized because the evidence, the scientific evidence behind it is showing us that these factors are already there.
Dan Brennan:
Is that very quantitative? FDA, Medicare, USPSTF are accustomed to different organizations looking at whether safety or benefits to harm or things like that, but you talk about, and we'll get into a little bit throughout the remainder of the podcast, some of these technologies, but is it a very statistically bottoms-up quantitative or is there a lot of soft or subjective assessments that you do in order to assess the benefit versus the potential harm?
Dr. Julie Chen:
Well, we always look at the on science. Some of the cutting-edge may be slightly off label, but it's all FDA-approved to the level of the utilization of the tool itself. But how it's being utilized in a more multimodal health span long-term trajectory fashion may be slightly atypical compared to traditional medicine.
So for example, if you think about some of the therapies that are being utilized even for Alzheimer's or heart disease, the timing at which we would, let's say, implement cholesterol medication maybe sooner and more aggressively in certain people, because we have more data establishing that they truly are higher risk in earlier disease, versus a lot of traditional care may wait until it's truly symptomatic. So it's more about the fact that it's still very much on science based on FDA approvals, the testing has CAP/CLIA coverage, all of those things are still there, but the utilization timeline might change because of the fact that we are catching populations at a asymptomatic, what we call preclinical stage. But that's the point where we need to start treating because that's where we need to implement the medicine that really can alter the trajectory in a positive way.
Dan Brennan:
Okay. Maybe before I dig into a few specific services technologies in detail, just zooming out a little bit, when you think about where you think maybe longevity medicine could be getting ahead of the evidence today, I'd be interested to get your take there. And then conversely, similarly, on the flip side, where do you think maybe it's underappreciated today in terms of despite having strong evidence?
Dr. Julie Chen:
Yeah, so I think there's a lot of things that are of interest for people out there right now who are very interested in the longevity sector, things like biological age clocks, peptides, supplements, massive spans of data. They're talking about gigabytes. But to me, the evidence still needs to be more defined for us to be truly evidence-based. A lot of it is still at the level of either animal studies or correlative data.
So what I actually think is being underappreciated, maybe not as aggressively addressed, even though the evidence is very strongly already there, are just simply just being more aggressive in addressing cardiovascular disease. So LDL should be pushed much lower and sooner than a lot of care has been because they're saying that the person's asymptomatic. Or if, let's say, someone has lipoprotein (a), which is 80% to 90% more genomically associated, it makes their plaques stickier or more prothrombotic, those people, even if their LDL seems not that bad, they need to be aggressively treated.
So I think the things like blood pressure, sleep apnea, muscle strength, and balance, those are things that need to be taken a lot more aggressively earlier on because they truly have been demonstrated in evidence to have moved the needle, and so that needs to be taken into consideration.
Dan Brennan:
Interesting. Super interesting. Maybe just jumping into a few of the other maybe more prominent technologies for Wall Street. So for the last six months, I think on MCED, there's been probably more debate following the NHS-Galleri study out of GRAIL, which misses primary endpoint. So it's created more questions, I think, and we have the FDA coming up here. Has your view of the role of MCED evolved over that period? And how do you think about the clinical utility of multi-cancer early detection tests today?
Dr. Julie Chen:
I think the multi-cancer early detection testing is very important in the sense of where medicine and diagnostics will go in the future. I think what the listeners need to really think about is that this test in and of itself, six in 10 tests, they'll miss six in 10 cancers. So there's the actual ability sensitivity to detect cancers is not high enough that it should be used as a solo tool.
So I've seen this quite a bit in some concierge practices where they're using the GRAIL Galleri test as an individual test, but what people need to understand is that this test in and of itself cannot be used as a standalone. They showed in studies that if you use this test in conjunction with other screening tools, especially regular screening tools, higher-level screening tools, it will increase the detection by almost sixfold. And so you really need to be using that as a adjunctive tool rather than a solo tool.
And so to keep all this in mind also, and this is why Radence really looks at it from a multimodal, multi-tool perspective in looking at any given disease, is the MCED GRAIL test is about 60% positive predictive value, but that also then means four out of 10 of these positives when they go in and look, there's no disease yet or there, period. So again, at Radence, what we do is we use these serum biomarker testing for the MCED along with our own proprietary of whole-body MRI imaging so that they can cross-reference each other, and then as well as additional other testing and biomarkers to ensure that we get a very solid look. The good news is that if we're used as an adjunctive tool, the MCED tool is able to pick up a good amount of earlier-stage cancers and is a lot more effective when used in conjunction with other tools.
Dan Brennan:
That's interesting. So I did want to pick your brain for a moment just on full-body MRI. I've not gotten one yet, but looking forward to doing so. And I think the interest there is certainly growing, I think, and I'm sure you could see that in your practice. Just where is that most useful, say, versus the blood-based screening? Sounds like together they're really helpful. Is MRI on its own, I know in certain areas, very useful? Just give us a little color about how Radence is using full-body MRI.
Dr. Julie Chen:
Yeah, so the major push here is to... I'm not a believer in doing the whole-body MRI by itself. The reason is because, like any other tool, none of the tools are perfect, and so the MRI imaging should always be done in conjunction with blood markers and other screening tools. And so that's where ultimately you can pick up the nuances of early disease and know that they're actually important and worth well, and then monitoring that above and beyond in that moment longitudinally.
So a lot of people aren't aware that not all MRI protocols are created the same. And so even if you use a 1.5 Tesla versus a 3 Tesla MRI, the quality of what you're able to see is very different. And then also from one MRI program to another, the way that they slice and look at the images of any given organ can very much alter what you end up seeing or what you end up being blind to and you can't see.
So when doing this, people should really be looking for MRI protocols with very small or no gaps in between sequences and slices. The slices have to be large enough to be able to not have too much noise, but small enough and thin enough so that it doesn't miss the smaller lesions. So all of these things come into play. And I liken the analogy to an MRI machine is almost like a palette of color, but how you paint it together is ultimately how accurate the pictures come out. And so it's really about the tools and the proprietary protocols that go into it.
Now having said that, the blood serum markers, all of that gives additional color as to whether something is significant or not. So for example, let's say we did a brain MRI and it looked like the brain is smaller than the average person for that person's age, gender size, skull size. But the thing is that we don't have any prior imaging. What will really help are things like the proteomics that are now out looking at Alzheimer's and dementia risk factors. Also, other markers of is this person a significant drinker? Are the vitamin levels off? So all of these factors all come into play.
So all of the listeners really need to keep an eye on the fact that none of these modalities should be done as a silo. They really should be done in a multimodal, multiple tool way so that you can get the most accurate look. And it is important to see what your body's foundational baseline is because of the fact that as the body changes, if you never saw what your baseline was before, and let's say you find a finding later on, whether it's on blood marker or imaging or both, there's a possibility you won't know if it's truly a problem or not. But if you had a baseline, you now know the rate of change is what ultimately gets you the data sooner for you to act on faster.
Dan Brennan:
Terrific. Well, I was going to ask a question here on longitudinal tracking. You've touched upon it many times throughout the discussion thus far. So maybe you can give just an overall view today, and I'm sure longitudinally it provides a lot of insight, but are there certain areas in particular so far that you've found the longitudinal nature of what Radence does has been able to really uncover important findings that are missed by a traditional healthcare model built around annual checkups?
Dr. Julie Chen:
Actually, in all of the major categories we've seen it. And this is why I'm such a passionate proponent of this model of medicine, which is really a health intelligence-driven longitudinal tracking of trajectory with accurate data, not the volume of data, but accurate personalized data for every individual.
And so for example, I'll start with each of the categories, cardiovascular, we found people where their LDL, which is traditionally the main thing that doctors look for, the LDL actually looked pretty good, was in the normal range, but we saw significant plaque in the carotids. But because this person wasn't old enough, they didn't actually bother looking yet. So that was really important for us to put this person on more aggressive lipid therapy before they ended up having more vascular disease that was unknown until later stage.
For metabolic disease, we see all of the time people with elevated fatty liver or visceral fat, which is the fat around the organs, and those things frequently are abnormal earlier than fasting glucose or elevated hemoglobin A1C because of the fact that your body is already seeing a lot of excess fatty acids or inflammatory cytokines, inflammatory chemicals. And so that actually has overall impact, not just on metabolic disease, but cardiovascular, neurodegen, and cancer. A lot of these are reversible or stabilizable, so that's something that's actionable.
And then when it comes to cancer, we've had people where they had what they call IPMN, which are almost this more concerning lesion in the pancreas that isn't quite cancer yet, but depending on the location of the lesion, can be more likely to convert to cancer. But knowing that it's there means that we're able to keep an eye on it closely so that if it were to change to a morphology that's more concerning, you can get right into that and deal with it rather than waiting for pancreatic cancer Stage 4, which a lot of times is what we see in medicine because the symptoms are so vague until someone is Stage 4. But if you identify the IPMN early, you just track it and you see the changes early on so you can act before true damage is done.
And then talking about neurodegeneration, we've had multiple people where we've seen that their beginnings of the proteins of the brain elevate for the amyloid plaque buildups and/or when you look at the brain volume and the overall formal memory testing that gets done, which is usually done by a neuropsychologist over the course of four to five hours, not just the 10, 15 minute ones in the office, you're then able to identify the beginnings of change.
I think one thing that's very important about neurodegeneration that the listeners need to understand is that traditionally, a lot of the definition of whether they treat with a new monoclonal antibody therapies or not is they have to see cognitive functional decline. But if you don't have a baseline of yourself of what your cognitive baseline is like, then later on they trend it compared to the average population. So it's not precision, it's more population-based medicine.
But let's say you take someone who's very high functioning, very intelligent. By the time they look maybe more similar to other general population data, they will have lost more function before they deem this to be truly actionable or concerning. Versus if, let's say, that person had done their own baseline before, and it doesn't have to be a perfect baseline, it just has two data points they can compare it to, and if, let's say, in one to two years it's now declined, they can then say objectively that, "Hey, even though this person still looks pretty good compared to the general public, it's clearly a declination based on their own function." And so based on that, they'll be able to start treating a bit sooner. And that's very important because some of these new drugs that are out for neurodegeneration has a very narrow window of therapy, meaning you can't be too far into the disease, because if you do, the side effects are too high.
Dan Brennan:
Wow, that's really a ton of information. Really useful.
Maybe on the business model side, Julie, so Radence, you've got this terrific partnership with RA, you get to analyze some of the most advanced technologies, you have leading doctors, so it's really holistic longitudinal care at the leading edge. What do you think about for the masses for precision medicine and longevity? When you look out over the next five or 10 years, how does a lot of this stuff become attainable to the masses, or is it attainable today? Because Radence offers a terrific service, but it's certainly going to appeal to a certain ZIP Code for wealth. I'm just trying to think, is longevity as we've discussed it today going to be something that the masses could really tap into? And how does that evolve?
Dr. Julie Chen:
Yes, the way medicine is and where technology is nowadays, the concept of preventive, predictive, early intervention medicine has to be the future of medicine. I mean, staying in sick care is really not a option that people really should be thinking about, but rather how can we make medicine better? Especially with all the AI tools that are out there right now that can synthesize thousands of signals and data points. And so when we think about why the longevity sector right now costs this amount of money versus in the future, it's because a lot of early technology is always more expensive.
And so even if you put it to the kind of analogy to all the safety features in a car, all of the major safety features in all of the cars nowadays originally started in high-end cars so they can prove the concept and then be able to bring it to the wider population. So if you think about medicine that way, that's the same thing, is that a lot of the early cutting-edge technologies is expensive right now, so a lot of the populations that are able to access right now are still going to pay it forward, though, for there to be proven data to then be able to implement into the wider population in the future.
Having said that, right now for those people where maybe they cannot do these higher-level programs in its entirety and maybe they could do a little bit of testing here and there with some of the commercial programs and/or with their own doctors, they could try to piecemeal some of this together and try to do it longitudinally. Same thing in traditional medicine. They'll do a set of labs and they'll do it again in three to six months. That, to some degree, is longitudinal tracking. It's just not very comprehensive. So they're doing some of that, and they have to be self-advocates for getting that done in the fragmented healthcare system that it is right now.
But the goal in the long run is to have a system like Radence, where you have an advocate who's there to actually care coordinate for you and with you so that we can ensure that whatever testing and findings that we find from the testing actually is then acted on, and then also the advocate knows which ones we can just monitor. And so that data assimilation into what's truly important is the true value, I believe, in Radence and what we're doing for members, and hopefully for the future.
And the way that people should be looking at it right now, though, is that a lot of these commercialized, out-there programs that are onesies and twosies, again, still fragmental in that they really need to understand that this cannot be in and of itself the only thing you do. And the thing that really worries me sometimes is people doing these programs that are, one, a little fraction or silo of the care and then they have a false sense of security that they're good right now. But what it is is it should be looked at as an adjunctive unless you're doing a very comprehensive approach.
Dan Brennan:
Terrific. And maybe wrapping up the podcast here, maybe on AI, which is just pervasive, not just in healthcare, but obviously in the world and the stock market, for sure. And certainly in medicine, it's starting to detect nearly every part of medicine. So where is AI generally creating clinical value today inside Radence? And how do you see the use of AI evolving, whether it be in the next few years or over the next five or 10 years?
Dr. Julie Chen:
Yeah, so AI is a real value for synthesis and interpretation of data and its ability to take thousands of signals and have a predictive impact on any given person's personalized risk factors. And so when you're pulling thousands of data points across multiple years and domains into a coherent picture, surfacing what changed and letting our clinicians spend their time on interpretation and clinical judgment instead of assembly, that's where the true value is. But someone still has to own the answer and have that clinical judgment and what happens next, and that's a clinician.
So one thing to keep in mind is that we have to be humble and know that technology isn't, at this point, able to make that clinical judgment. So the time spent on clinical judgment and the true parts of programs like Radence, where we touch the member and impacts that member relationship, that's the moat, and that really needs to stay where it is in the human form while technology helps medicine be able to aggregate and interpret thousands and massive volumes of data so that it can truly predict the trend and trajectory for any given person.
Dan Brennan:
Well, Julie, I think with that, we'll wrap up the podcast. It's been a really fascinating conversation with you, so thank you for joining us and sharing all your insights. And I'm sure this is going to be as it's been discussed throughout a continuum here, so we'd love to be able to touch back in with you over the next six to 12 months and see how things are progressing and hopefully where things are moving along faster. So thanks again for being here, and I hope everyone on the podcast enjoyed it.
Dr. Julie Chen:
Thank you, Dan. It was a pleasure, and definitely would love to follow up.
Dan Brennan:
Great.
Speaker 1:
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