The Longevity Medicine Paradox - Adam Carewe, MD (General Medicine)

00:00 We are the guinea pig generation. The reality is as a medical field, as the best physician in the world, we just
00:06 don't know. Do you think patients just don't know that we don't know? Most people understand what that is on the surface, but and I honestly just
00:13 think that as physicians, we probably don't say that enough. It's challenging. The problem is we have all this access
00:19 to all these different tests and the imaging is only getting better and better. And so I think we're in this
00:25 weird kind of bubble right now where we have this amazing kind of technology for testing. We don't have a way to truly
00:32 interpret it yet because we don't have like the data for it. You know, I just had this itch to go into the startup
00:37 world myself. Didn't have the courage to do my own startup but wanted to join and so I joined the company general
00:44 medicine. If I could go back 10 years I would have probably told that person to Hi Adam, thanks so much for joining us
00:51 today. Happy to be here Rashad. looking forward to the convo. So am I. Let's give our audience a bit
00:56 of an intro. Could you tell us what do you do in your professional life today and how did you end up here?
01:02 Yeah, happy to. Uh I'm a physician, I guess, first and foremost. Um but didn't kind of land on that path, I'd say, the
01:10 traditional way. I started college thinking I would be a math teacher. You know, we were just briefly chatting
01:15 about kind of math background and prowess. And I was also just pretty good at math and it was just kind of natural
01:21 and I liked teaching people and helping my classmates and so so I picked that as
01:27 like my initial major. But I played basketball in college too. So I was really into training and performance and
01:33 making myself as best as I could be personally as an athlete. And um I ended
01:39 up pivoting to the exercise sciences for my undergrad degree. So, you know, which
01:44 was I don't know, it was sort of like a premed light type of major. I took an intro class and I like I realized, man,
01:51 there's a lot of different aspects you can go into this. And, you know, selfishly in college, I was like, man, this is going to be helpful for me like
01:57 to know how to exercise and how to train and um learn about the body and how it
02:03 adapts and that sort of thing. And so, I got really into that, really into strength and conditioning performance um
02:10 as well. you know, I was always like because as an athlete I was always kind of was I was good obviously good enough
02:16 to play in college um but I wasn't great you know so it was like I had to really work hard to to be that kind of
02:22 differential and I finished college and thinking I would go into exercise sciences but I wasn't sure which avenue
02:28 cuz you can kind of go consumer or more clinical type of roles and so I kind of just decided to try both of them you
02:35 know I worked in some gyms I u I worked for some companies that had their own kind of fitness
02:40 kind of program internally. Did that out of college and then but I decided to go to grad school and in grad school I
02:48 dipped my toe in the my first clinical kind of role which was working in cardiac rehabilitation and so cardiac
02:55 rehab um I was like man this is fun. And I got to do stuff in the hospital and bedside teaching education and then got
03:01 to work with patients, you know, in the outpatient um facility, crafting their exercise programs and nutrition and
03:09 education. So, I kind of always followed that like kind of teaching kind of arc. I thought I would be a teacher
03:14 originally in college, you know, for high school and maybe coach. I had a mentor there and she was one that
03:19 suggested, you know, have you ever considered medicine? And I was like, no, I haven't. Didn't have any doctors in my
03:24 family. So it really wasn't ever really on the radar, but I thought it was interesting and a good way to to kind of
03:30 go forward with, you know, the way my life had been. And so that took me to medicine. And I think like, you know, I
03:37 was in college in the late '9s, so right when, you know, the internet was really
03:42 blooming, you know, and Napster was around for, you know, free MP3 downloading. um obviously highly illegal
03:49 but um everyone was doing it you know and I just got really into the technology stuff that was coming up. So
03:55 that whole arc was kind of like woven in throughout and always thought technology
04:00 and medicine was something that I was super interested in and so I always gravitated to those types of things and
04:08 you know I think in residency that's probably when I first started really getting involved um when our hospital
04:15 system was transitioning to Epic as a EMR going from paper to Epic and um so I
04:21 was one of the resident representatives on that transition and that just kind was the catalyst that led me down a path
04:27 of like really wanting to optimize the systems that physicians and other care
04:32 teams use. It just made my own life so much easier and better and more efficient and I loved being able to help
04:40 others do that. So that is kind of what led down the path of informatics formally and and so yeah so I just I did
04:48 that internally at Kaiser for many many years ultimately becoming the CMIO for
04:53 the Colorado region of KP and um and really enjoyed it but you know I just
04:59 had this itch to go into the startup world myself didn't have the courage to do my own startup but wanted to join
05:05 one. So um in August of 2024 I um I left KP and I joined the company general
05:13 medicine which was really early and incubating at that time but um started with them part-time and um have
05:20 continued to work with them through today. That is an amazing journey and I have a million questions and let's maybe go in
05:26 chronological order. Sure. The one thing I really and my math journey stopped after first year of
05:31 undergrad. Uh the one thing I really enjoyed about maths is you can test everything. you can prove everything and that's part of learning math and and and
05:38 and doing math that doesn't exist in the real world often what I found when I was doing my premed courses eventually the
05:45 answer is we don't know for I found most of the things come from physiology to biology to
05:52 chemistry like often it's like we just don't know why this happens you know good example maybe that lasix has no
05:58 mortality benefit but obviously it works so no one's going to not use it for heart failure um is is that something
06:04 you strugg struggle with with having the very defined world view in math at least at the university first year level and
06:11 I'm sure it gets more vague as we go further along versus kind of being in the real world and and real working
06:17 scenarios where most things are unknown. There's a lot more probabilities as opposed to determinism happening. And
06:23 how do you kind of tie that into how we naturally want a deterministic model of the world
06:31 but the world exists in a probabilistic model? Yeah, that's a great question. You know, I don't think I ever made the
06:36 connection between me liking math and like what you just said, but that it actually makes a lot of sense. I've
06:42 always been someone who when I'm learning something new, I can typically grasp it pretty quickly. And I think for
06:47 math, it was that was particularly evident. And you know, so like we could learn a new concept in say high school
06:53 and calculus and you know, it's like once it clicked and it clicked pretty quickly, I would be like, "Okay, I know how to do this. Like I understand the
06:60 rules, I understand the formula, etc." I think what I quickly learned and what helped me like excel in even in math at
07:07 an early age was I could then like translate that to other people pretty easily that was I think something that
07:13 was just like a natural kind of gift that I had you know I think that piece is probably the piece that I think
07:19 transferred so like much more to medicine because as you know you're always like learning stuff you're taking
07:25 in kind of like you said real real concrete possibly even deterministic things And then there's like that gray
07:33 area where there's the uncertainty, the you know, and so I mean I tend to write about this type of topic a bit too, but
07:39 it's you know for me like in medicine I think the way I see it is I want to optimize the crap out of the
07:47 deterministic stuff like make that like just so foolproof like super easy for
07:52 patients, super easy for clinicians. make that part as like automated and
07:58 amazing as possible because then I think then it leaves like more of that kind of gray area to actually focus on. I don't
08:05 know. That's the way I would kind of answer you know your question. I kind of took it my own way a little bit but I
08:10 think that's um that's kind of like been my approach and that's the part where I see you know us being able to actually
08:17 be able to care for more people with less human resource is to do that. We got to automate the automatic stuff and
08:23 the easy, you know, call easy in quotes. But the, you know, the deterministic,
08:29 the algorithmic, those types of things, we got to make those um really simple and uh easy so we could take care of
08:36 more people. That's been that was that would be my connection, I think, to kind of the math roots to to where I am
08:41 today. A lot of VCs in particular, but people in general, have predicted the AI physician happening in our lifetime and
08:48 recently within the next 5 years. I think the future is easy to predict. It's very hard to predict when it will
08:54 happen. We'll have flying cars. I don't know when, but at some point in the future, we will. When do you think the
09:01 AI physician is happening? I know there's a very early bill in the Senate pushing this as well. Um, when do you
09:06 think that's going to happen? Yeah, I mean I think I generally say the similar thing that you just said that I'm pretty
09:12 confident it's going to happen and I think whatever time I'd say somebody con with a more conservative estimate says
09:19 my general gut is that it'll be quicker than that but I still do think it's going to take some time. Is that
09:26 nebulous enough of an answer? Um I mean I I think it'll honestly be iterative and kind of progressive in a in a
09:33 certain way. I mean, I see more of the kind of more innovative startups
09:39 probably pushing the envelope and kind of pushing what different AI tools can
09:44 do uh for care and it'll be a much longer adoption curve for the
09:50 traditional kind of legacy health systems, you know, that just have a lot of reasons why it they can't change
09:56 really quickly. But, you know, I think like anything, there'll probably be a
10:01 disruptor or significant disruptors that I think will catalyze this and will kind
10:07 of force it to spread. And I truly feel it's going to be something that truly
10:12 patients like gravitate towards and they demand it, right? I mean, I think that's the way it happens in all aspects of of
10:19 our society. Um, is ultimately it's the customers that really will drive it. And
10:24 so that's why I try and, you know, kind of beat the dead horse of like I really
10:29 feel strongly that physicians and and other clinicians need to really be
10:34 leading and pushing this forward and really testing and and trying things and
10:40 not being so guarded because I think if if we protect the old ways, I think you just you're going to get usurped at some
10:46 point. It seems like Chad GPD and maybe open evidence are are sort of leading the forefront here from a consumer DDC
10:53 perspective where you know there there seems to be there will be a solution now where consumers and patients can upload
10:60 their records into chat GBT complete records and maybe Epic is building this as well with Cosmos and other tools
11:06 where you can ask queries from your records. What are your general thoughts on that? There's an obvious fear that
11:13 everyone will ask, do I have fibromyalgia, ADHD? And not to say that, you know, those conditions are very
11:19 real. I treat a lot of patients with it. But the social media push towards if you have these symptoms, you
11:25 have this that sentence is is can be a very dangerous sentence. That's a little bit of knowledge can be a dangerous thing.
11:32 Um, no physician diagnoses something from four symptoms, right? I think you
11:37 just need more information there, right? Um, correct. Yeah. like uh do do you think it's it's
11:42 is this good or bad? I I think if the the LLMs are tuned a little bit
11:48 differently, not just tuned for validation, not just tuned to tell me I'm the smartest human being ever to
11:54 walk on this planet, which I know I'm not, then I can see this actually being good. But the problem is then people
11:59 won't use it. So, um, we're kind of in a catch 22 is that this could be really good, but then it it won't get usage and
12:06 and that the the quote unquote bad versions of this, the validated versions of this will probably get more usage.
12:13 What are your thoughts here? Yeah, I mean I think we're in this weird position right now where the tools, you
12:18 know, like the consumer grade, I mean, just take Chad GPT or Claude or Gemini, I mean, all of them are they're
12:24 extremely good. And like you said, like they're pretty darn good with clinical
12:30 things. Like I think the challenge right now, yeah, is like I think if you just
12:35 use a generic model and just kind of upload your stuff, present your information and ask it a simple
12:42 question. I don't think it's going to generate something that is consistently
12:48 accurate cuz they really are kind of aimed to please, right? It's that's the way these models like really function. I
12:54 think OpenAI just recently published a thing where they they said that's the reason why these things actually hallucinate cuz it's it's actually
13:01 designed to do that. It's designed to kind of give a convincing uh answer to
13:08 something that may not actually be true. But I think you know there are ways to to kind of make guard rails around these
13:15 things too even in the open kind of uh models that are out there for consumers.
13:20 I think the challenge is is like either the consumer has to be savvy enough to to put around their own kind of
13:26 prompting guard rails around these types of things and use it in that way or they
13:32 have to like constantly be fact-checking you know everything with another source which is obviously you don't know what
13:37 to fact check when you when you have all that. I mean, I still think though from like the standpoint of patients being
13:44 able to kind of noodle on their kind of concerns, their health information,
13:49 their data, their different studies and things and labs that have been done. Um, and to potentially like poke and look
13:56 for other potential explanations I still think is overly positive. I encourage
14:01 patients to do that. I think the part where that you just have to be careful and stop is if it does say something you
14:07 really do need to get that validated by someone who knows you know or knows where to look up that information
14:14 accurately. So I think like where things are right now where I think these models are extremely good is on the clinical
14:20 side. So someone who has a clinical mind or you know say like a lawyer like someone who has law experience and knows
14:27 how to infer which things are wrong and not like if you have that expertise and
14:32 you have the right guard rails and prompting around these tools they can be extremely extremely accurate and
14:39 powerful for what you're trying to to use them with. So it's going to be wild. I think we've hit some crazy leaps and
14:45 bounds with the LLMs that are out there. And maybe we're hitting a little bit of like I wouldn't call it a plateau, but
14:52 it's maybe a little a little bit of a flattening of the ascent. But I still think there's going to continue to be
14:59 significant gains over the next few years that handled in the right way are going to be really powerful for both
15:05 clinicians and consumers. From what little I know about athletic performance and kinesiology, and it is very, very
15:12 little. It seems like we don't differentiate as much between physical and mental health as we do in medicine.
15:18 Something I'm thinking about a little bit more recently. We seem to just look at them through completely separate
15:24 lenses where it's part of the same human body. I don't know why we have this arbitrary distinction of mental health
15:31 versus physical health. We're looking for an organic cause of mental health, right? instead of just saying this is
15:37 health. And I think we would be much better off as a field, as a society if
15:43 we just got rid of the label of mental health. Um cuz it's almost as if
15:49 something is broken with you or in you. Um whereas physical health, you know, no one says if you have diabetes,
15:55 something's bro, you're broken, right? Whereas if you have depression, like people might say you're broken. Why do
16:01 you think that is? And and I kind of see this in the longevity space as well. It's all about physical health. Um you
16:08 know, how do we get rid of this distinction? Can we get rid of the distinction? Why do you think it exists?
16:14 Um and I have a follow-up question I'll ask um after. Yeah. No, I think I think humans love to compartmentalize things. And
16:20 traditionally in medicine, I mean, it's it's always been very compartmentalized. You know, over our careers, we've even
16:27 just seen how much of an overlap there is, you know, across disease states. I think that just comes from historical
16:33 context of why it is established that way. But you know, like you were alluding to and what you were
16:38 mentioning, physical problems can lead to quote mental problems in yourself and
16:43 mental problems can obviously lead to physical problems. So they're clearly tied together. I mean, I think what I a
16:50 lot of times break down with patients because I think too patients when they if they come in with a um a symptom, say
16:57 they come in with like abdominal pain and everything's been kind of ruled out from from a you know, an actual
17:03 digestive functional or a you know, physical problem and you know, you
17:09 ultimately arrive at something you know, like you know, IBS or something that's just you know, this and you start
17:16 explaining it to them and the The way I always break it down is that, you know, our brain and our gut are like actually
17:22 directly connected by the same nervous system. And because if you just jump
17:27 right to saying, "Hey, I think this is is IBS and you know, we should try X, Y,
17:32 and Z that you know, and then they go, wait a minute, those things you just mentioned, those are like those are medicines that are used to treat
17:39 depression and anxiety. Like how is that going to help my gut?" I mean, I think that's just like a perfect example in
17:44 medicine of where there truly is that connection. But, you know, I mean, personal story for me, I mean, when I
17:49 I've had periods of my life where I've had some pretty significant orthopedic injuries, you know, from from athletics
17:55 happened first in college. I I broke my foot and had to have a screw put in there that put me out a year. I was
18:01 definitely depressed during that year. I mean, I clearly had some depression, but it was clearly related to, you know, a
18:08 physical ailment. It happened to me again, you know, later in my adult year. Um, you know, probably my 30s. I tore my
18:15 patellar tendon and you know that really put me down and like even got me to the point where I was like man I can't play
18:21 basketball anymore and so there's been like these waves of of things that have come and I think it those two things
18:27 really are connected and I'll flip it a little bit to like I hate it in healthcare where things are
18:32 compartmentalized too right I mean we need specialties and specialists for different expertise but like I
18:39 absolutely hate it when a specialist would be like oh no we can't talk about that because that's not my specialty. I
18:45 think that's BS. Like every specialty has an overlap with something else, right? It's the human body. And then the
18:51 terms we use in healthcare are also compartmentalized. Like why do we call it teleaalth or digital health or
18:57 inerson health? Like it's it's really all the same. I mean the goal of it all is is exactly the same. So I don't know.
19:04 I think it's just humans. We all we'd like to compartmentalize things and put things into a bucket, you know. I think
19:11 I think the whole system is just has been set up that way, you know, from history until now. But I think there's a
19:17 little bit of a shift. So much of the foundation is still rock solid in that area. We know what we need for longevity and
19:24 for athletic performance to an extent. We know we need to sleep 7 to 9 hours. We need to reduce our stress levels. We
19:31 need to let go of thoughts that are harmful. We need to eat better foods,
19:36 ideally a more plant-based diet. We need to lift weights. we need to do cardio. None of these things require any
19:42 technology yet it's technology and AI that's unlocking the longevity space. It
19:49 it's tests we don't need. It's more biomarkers we don't need um to an extent.
19:54 You know there is there is some role for imaging for more detection of preventive
19:60 health in general. I'm not saying preventive health shouldn't exist. But do I really really need a biioarker for
20:05 sleep um or for lifting weights? Right. Um, do do you think we're in a at a
20:12 point where we are testing too much and not optimizing for what's needed or do
20:18 you think given the way our human brains are designed for convenience and reward and scarcity and you know the principles
20:25 of marketing, we need to do it this way? Yeah. I mean, I don't think it's like an eitheror. Um, it's one of those things
20:32 that, you know, kind of like you just said, I can be on I can be on both sides of the fence, you know, like, you know,
20:38 I mean, I think and and I I think there's a there's a tug and a pull between traditional quality based
20:44 healthcare and what consumers actually want and need, too. So, I think there
20:50 has to be a balance between these things, you know, and that's um you know, so like I've had plenty of
20:57 conversations with, you know, my neighbors who who know I'm a physician and they'll just be like, you know, why
21:02 won't I go into the doctor? Like, why won't they just let me why won't they just order everything, you know, to make sure everything's not right wrong,
21:08 right? Or, you know, we have several companies that are doing kind of whole body imaging, you know, to try and look
21:13 and see if there's potentially anything. And you know on one hand I totally understand that like right I mean you
21:19 you want to know like it's like this element of unknown but I think like you know if you go into the actual like
21:26 statistical probability of these tests being positive and you get into all the details of that like you quickly realize
21:33 that it's it's not really good to just blanketly do all of those. I think what
21:39 we have to do is we have to find a way that these that these tests can actually
21:44 be much more sensitive and much more specific which is obviously the holy grail of any test right you have those
21:51 both at 100% you're like pretty much money you can use it as a screening test and confirmatory test and I think like I
21:59 think that's like where we just have to really push with these you know so-called biomarker tests which I say I
22:06 hate that term because really all It's it's the same things we always have. They've just tagged on a catchy name.
22:11 But and then I think the other thing obviously everyone wants to live a fruitful life and everyone wants to live
22:18 a long life, right? I mean unless something horrible happens to you that you're miserable. I think this whole rush for kind of longevity.
22:25 I wish it wasn't called longevity cuz that infers that people just want to live longer. And I really think like
22:32 what people really want is they want to live the way they are right now as a younger person for a longer time, you
22:38 know, and there's all sorts of obviously terms and things that are used for that. But I think it's like if all of this is
22:44 truly just allowing people to live a longer fruitful life and be able to do the things that they want to do for the
22:49 longest period of time, then I think that's good. But I think this whole like I don't know the whole industry around
22:55 hacking different things and trying to find certain things that are going to degrade aging and uh be able to prolong
23:02 different cell life. I don't know. I just think that's we're like splitting hairs at that point cuz like what you
23:08 led with all those core tenants are really the things that if you do those you're pretty much going to live a good
23:15 healthy life. And I always tell patients, especially my older patients, you know, or that are patients that are
23:21 approaching an an older age, like it's even just more important that you do those basics when you get older, right?
23:27 Like you got to preserve that strength. I mean, cuz if you fall down or you slip and you're on the ground and you can't
23:34 like get yourself up, I mean, that's a problem, right? Like a little kid, I mean, they fall all the time, hit their
23:40 face, they bounce right back up. but just getting on and off the toilet or slipping in the shower and like not
23:46 being able to get yourself back up. I mean, those are the things that can really do people in. So, I don't know,
23:51 that was like a serendipitous answer to your original question, but I think all the stuff that's happening right now is very well intended, but I think a lot of
23:59 people are jumping on the bandwagon of this term longevity to like promote stuff that we've kind of like already
24:05 known or can already do. I haven't really seen a ton of net net new things,
24:10 but I think some of those are probably on the the fringe of of really coming
24:15 together. Yeah, I think going a little bit deeper, you know, I had a patient who wanted a screening X-ray for no reason and ended
24:22 up with a lung resection, but you know, these cases are rare. It almost guarantee if we give you every single
24:29 test we know, it will result in some invasive treatment for no reason. And
24:34 the the gap between what we know in medicine and medical knowledge and the appetite for knowing and optimizing our
24:41 health is very wide. We know so little about what to do with the tests we
24:46 order. Uh and even that the normal ranges are based on specific populations that maybe don't apply to other
24:53 populations and they're based on gender and age and race and and medical conditions. So I I I think there we are
25:00 the guinea pig generation. Uh, and I think collecting more data is good. We don't know what to do with it. And I
25:06 think patients should know that before signing up for these things. This is an amazing business opportunity. You feed
25:12 people more uncertainty every time you order more tests cuz we don't know what to do with them. The reality is as a
25:18 medical field, as the best physician in the world, you know, whatever the top
25:24 doctors from wherever you think are the top doctors from, they don't. We just don't know, right? Like I don't know if
25:29 your sodium is 134. What does that mean? I know if it's under 130 that, you know, maybe we should optimize it a little bit
25:35 cuz lead to bone der demilarization and you have a hyper. If your sodium is too high, sure, I should look for maybe
25:42 something called um diabetes and cipotus and like maybe like this. But we don't
25:48 know. There's no optimal sodium, right? Like a 137 versus 136. There's no
25:53 difference. And I don't know if that's an answer people just aren't willing to accept or is it like, "No, you know
25:58 something. You're not telling me." Whereas I'm like why would I hide it? Why do you think that it's like do you think people just like patients just
26:05 don't know that we don't know? How do you kind of deal with the question? Why? Well, why wouldn't you order every
26:12 single test? Like why I want to know my compliment pathway, right? I I want to know everything, right? Like just order
26:19 all the genetic tests, you know, and all the tumor markers every single visit cuz if I get cancer now, I want to know
26:25 now. I want to follow CA199 hourly. And some of the audience is not medical that I'm
26:30 measuring mentioning C99 is a tumor marker for pancreatic cancer that we use in ovarian cancer and we use to monitor
26:37 cancer but not to detect it cuz that's not what the test is designed for and we just don't know what to do if it's a
26:43 little bit high because a pancreatic not an easy procedure. But anyways like what is your kind of um answer there? Yeah, I
26:51 mean my approach to it is generally like just this true like shared decision-making approach where I'll try
26:57 and break it down to the patient of like, you know, this test or these tests are for X, Y, and Z, but I usually will
27:03 get a pulse of like how much this person wants to dive in cuz I can go into a whole deep dive of what sensitivity and
27:10 specificity are. And I think people, most people understand what that is on the surface, but you know, when you
27:15 specifically dive it in, dive into testing, I think that's when people really can kind of realize it. And then,
27:22 you know, I'll flip and I'll start talking about positive predictive value and negative predictive value and like these types of things and and that all
27:28 tests like vary and some of them, you know, like say like those tumor markers that you're mentioning, I mean, those
27:33 things can be really kind of horrible at some of those um but then also can be really good for some use cases. And so I
27:41 think a lot of people think labs are very like black and white. And you know, I think you asked the question
27:47 specifically, why do patients have like maybe that skepticism around physicians
27:52 and and kind of the interpretation of these things when in reality a lot of these things we don't know what they
27:58 mean, right? I mean, it's and I honestly just think that as physicians, we probably don't say that enough. I think
28:04 patients expect us to just know everything, but like, you know, I think family docs, you know, biasly probably
28:10 do this a little bit better, but I think we're we're generally better at like saying, "Hey, I really don't know what's
28:16 going on with you. I agree. Your symptoms, you know, are disturbing and we've checked X, Y, and Z, and they've
28:22 all been okay." But I think where this gets into trouble is when there are some
28:27 practitioners out there that that will start to say, "Oh, there's this optimized level of this and that." And
28:34 you know, I've encountered this as a doctor. Patients will bring me these reports and you know, it's like a standard Quest lab, but like it has this
28:40 custom kind of interpretation of it. And you know, patients like, "Oh, they're telling me I'm not optimizing this and
28:47 that and that." I'm like, "Well, I don't know what to do about that." You know, like drink more water. Like if you're,
28:53 you know, creatinine isn't dead in the center of, you know, the creatinine range or less water. I don't know. It's
28:59 like, yeah, it's challenging. The problem is we have all this access to all these different tests and the imaging is only
29:07 getting better and better. And so I think we're in this weird kind of bubble right now where we have this amazing
29:13 kind of technology for testing. But like what you kept saying, we don't have a way to truly interpret it yet because we
29:19 don't have like the data for it. You know, like I'll take whole body MRI as an example. I'm like pretty bullish that
29:26 that's going to be something in the future like that's going to be pretty transforming to healthcare. I think
29:32 right now most physicians are super skeptical of it because of the way we were trained and the way things are,
29:38 right? I mean cuz you don't want to just find all these incidental things that you're chasing down and people are
29:43 having biopsies of and all this followup, you know, like that's especially if it turns out to be nothing. Now you just put someone
29:48 through a bunch of risk. But I think if like the imaging in these tests can continue to get better and better and
29:55 the technology that interprets them, including the physicians, gets better and better, we will reach this point
30:02 where like it's a really, you know, like I said originally, where it's extremely sensitive, but it's also very specific
30:09 and being able to characterize, you know, specific findings and not just be
30:15 that kind of typical radiology read that like hedges on something like h it looks
30:20 sort of concerning but not you know definitive you know I think we need to get to a place where we can definitively
30:26 you know characterize things better because I think that will ultimately lead to better outcomes um and and
30:32 better prevention pulling on the whole body MRI thread and I do recommend it to some select patients who I think are a good
30:38 candidate with family history of cancer or patients I know will be comfortable handling in incidental from talking to a
30:46 radiologist and a oncologist And what they kind of their frame of reference is
30:52 a whole body MRI will never diagnose cancer because we cannot see the the pathology slides, right? Like we cannot
30:59 see in it's just a it's magnetic waves, right? Like it it's we cannot see inside
31:04 the detail because the technology is limited. The the MRI technology itself,
31:10 the way it works is limited. It's like you cannot see through a wall. No matter what the resolution, no matter how many
31:15 pictures you take, you you're never going to be able to see through a wall because the you're using light and light
31:21 does not travel through walls, right? It's a that's kind of their analogy is MRI will
31:26 never diagnose cancer. The only way to train a model is to take a biopsy of every single incident to then train a
31:33 model to have enough data to say this is cancer, this isn't cancer. What are your thoughts there? Do you think we're doing
31:40 cancer screening a disservice by leaning so heavily into MRI and because they have this mythical connotation somehow
31:47 that's developed that it shows all but you know it's still the picture you don't see the actual tissue or the
31:53 actual cells and cancer is for those listening cancer is very fast dividing
31:59 cells so and and we see them under a microscope on pathology slides we we
32:04 can't see cells in an MRI No matter how much you want to I don't know what
32:11 whatever you want to do with the MRI just like we can't see through the wall. No matter what you want to do with the light um or you can't see inside a ball
32:18 with light. Um yeah. So like what are your thoughts there? Like should we be building a
32:24 technology that allows us to see at a cellular level based on an and
32:30 non-invasive test? I think that's what we should be building, not wasting our time with MRIs. like they they have such
32:36 a big commercial uh tailwind that it's it's all it's easy enough to say well hold better MRIs a lot of people get
32:42 them we'll make a lot of money kind of thing. Yeah. No, it's a good question. I think we're going to have to wait and see how the technology evolves. I mean I think I
32:49 think in the MRI realm I think just what's improved significantly in the last few years is there the um obviously
32:57 the quality of the machines continues to improve. But I think the other piece that's really changed and improved is
33:04 the quality and the configuration around the protocols of like how the image is
33:10 rendered, you know, like on the actual screen. And so I mean, are we going to
33:16 reach a point where like you can no longer improve what the image looks like and you got to look for some sort of new
33:21 technology like you just mentioned? Could there be some other sort of thing that could actually get to the level of
33:26 like a pathology kind of evaluation through yeah some sort of light or image
33:32 or something you know I mean I think that's there's definitely a possibility that that could come about. Not aware of
33:38 anything in R&D area around that now but I'm sure people are trying to look for those. I I just think, you know, with
33:45 what we have today, I think will be interesting to show over time is if
33:51 doing any of this stuff actually changes some sort of outcome. You know, I think that's going to be the the most telling
33:58 thing. Will there actually be positive outcome data from these types of things?
34:03 And and I think that's still to be told. And I think, you know, the emerging companies that are doing this, you at
34:10 least started doing this, I think that's why they're collecting this data. I think they're hoping to to be able to
34:15 show that sort of thing. Um cuz yeah, as of right now, none of that stuff is none
34:20 of it's going to be covered by insurance yet until there's some sort of real substantial proof, you know, that it's
34:27 it's going to change the outcome. I think we'll probably get there at some point. I just don't know what time frame
34:33 that's going to be. And so for right now I think these types of things are going to live in the kind of the cashbased
34:39 business you know or companies will offer it as a perk you know as being a part of the company to get these not
34:47 current evidence-based you know um testing and exams done. I think time
34:52 will show eventually it'll show either yes or no and that could be kind of
34:57 either the bloom or the the doom for you know these types of things. I love the framing of focusing on the outcome. It's
35:04 easy to get get lost in the technology and the details, but what matters is outcomes. Yeah. So, a time will tell.
35:11 What do you think went wrong or went right with the Brian Johnson experiment where he kind of launched this, grew it,
35:16 and then it seems like he said, "Maybe I've had enough or it's not working." Do you think that's kind of a case study
35:21 in, you know, just sleep better, exercise more, lift weights, so you're struggling a bit. Doesn't matter how
35:26 many reps you're doing or how much weight you're lifting. As long as you're pushing yourself, that's what you want. And then tracking these things isn't the
35:34 path to optimization. Pushing yourself, sleeping better, being less cuz you know
35:39 when you're less stressed. I don't need anything to tell me if I'm not stressed. What are your thoughts on the Brian Johnson phenomena and then just the the
35:46 tracking all these uh things in general? Yeah. Yeah. Yeah, I mean I think the tracking piece is like, you know, it's one of
35:52 those things that I think is helpful for some and it can be very kind of anxietyprovoking to to others and
35:60 there's like a spectrum in between, you know. I think like so recently I've probably for the last six six or seven
36:06 weeks um I've been using, you know, one of the the Stell um CGMs, you know, just
36:12 to track what my sugar does. I don't have diabetes. I don't have pre-diabetes, but you know, I think
36:20 what's been pretty eye openening to me is just it's all the stuff that you kind of know, right? Like the more sugar you
36:26 eat, like the higher your the steeper your spikes will be. And then on the flip side, you know that I mean I guess
36:33 my background in exercise, I I I know what happens from a like a biochemistry perspective for exercise with blood
36:39 glucose and and that sort of thing, but to actually see like what happens, you
36:44 know, when you just, you know, when you do like any sort of exercise, whether it's in the morning, the the afternoon
36:50 or or in the evening and when it's around food, like it has you can visually see, you know, the the changes
36:57 that that that does. So, I think like for some people having that data is is really helpful. You know, I've had
37:03 plenty of people where I think they're just trying to get so much data and they're like it they be you become obsessive about it. And so, I think if
37:10 you can use it in the way that it will help you to to make behavior changes, I
37:15 think I'm all for it, but I think that has to be framed up. And I think when patients ask me, you know, oh, hey,
37:22 should I get this sleep tracker and do this and that? I I usually have the conversation with them, well, like, what are you hoping to get out of it? you
37:28 know, and and how do you plan to use the information to help yourself? And as
37:33 long as they have like a a good kind of thought process around what they're going to do, um I'm usually supportive
37:40 of it. But if I can tell they're like a super anxious type and that they're just this is probably just going to make them
37:46 super super nervous all the time, you know, I'll probably try I'll try and steer them away from it if possible. But
37:53 so yeah, I think it's like kind of like I think it has to be adaptable to the type of person that they are, you know,
37:59 if or when this is going to be helpful or not. Earlier you said that you you are um
38:05 excited about technology in healthcare and optimizing systems. If you could magically optimize or change one system
38:12 in healthcare, what would it be? So I mean the thing that's been on my mind for a very long time is you know I think
38:18 a lot of I think if you ask that question to a lot of people they'll say like pry ros or the in basket or whatever. I mean because I think a
38:24 clinician that's like what we're so and I agree technology can fix all of those things pretty well. But I would zoom out
38:30 even further. And what I really want is like I want patients to have the ability
38:36 to really kind of um accurately kind of noodle on their concerns and really
38:43 allow them to like frame it up. So the time spent face to face or whatever it
38:50 is with with the actual kind of physician or clinician is like extremely efficient. And so I guess the way I
38:57 would like break it down is I think we need still need better ways kind of
39:03 pre-enccounter how for patients to really formulate what's their concern is and what's going on. Um I think we have
39:10 pretty good stuff right now to be able to help within the encounter and like synthesizing and capturing. We need even
39:16 better tools downstream, you know, like the post and across like between visits. I think right now like patients have
39:23 real real concerns about themselves or their health and what we've done is we've made it so they only get to spend
39:30 10 minutes with the actual like expert for this like one for this problem and I
39:35 just think that is like it's not right. I mean it's like they don't remember anything that's said during those 10 minutes. It's like I don't know that
39:42 that was a kind of a long-winded way to your question, but I really do think we just need to we need to optimize that
39:49 the whole process of from concern to the patient feeling like they're getting
39:55 some sort of resolution or next steps. I think that is still fundamentally like
40:00 the same as it was when I was a child. Hasn't changed. So, I want technology to be able to fix that stuff.
40:06 Yeah. as clinicians, we we often kind of forget the patient perspective of things. We're so
40:12 entangled in in our uh inbox and and prior ro as you said that it's it's
40:17 difficult to kind of see their experience and we just want to kind of get to the bottom of the medical query
40:23 and solve it. Yeah. So I can definitely see I'm not sure the business model or the business
40:30 case there, but I think there's there's clearly a need there. Now, last question, Adam. If you could go back 10
40:36 years in time and talk to yourself, what what would you tell him? Well, I think like just what I went through last year, you know, where I
40:41 finally made this kind of proverbial leap to something that I wanted to do for a long time. If I could go back 10
40:47 years, I would have probably told that person to to follow that, you know, desire and instinct. I had a lot of
40:54 people telling me over the years like, you know, you should start working in the startup space or you should I can see you doing X, Y, and Z. and and I
41:01 just kept going, "Yeah, I do too." But I never took the leap. So, I would honestly just go back and and um tell
41:07 myself to to take the leap earlier. Congratulations on taking the leap and I'm happy to meet a a fellow physician
41:15 entrepreneur and a physician in the startup. No, you bet. Thank you. I appreciate it, Rashad. Great conversation.