Medsider: Learn from Medtech and Healthtech Founders and CEOs - Building Around Technology and Market Tailwinds: Interview with Adaptyx Biosciences CEO Vijit Sabnis

Episode Date: July 27, 2026

In this episode of Medsider Radio, we sat down with Vijit Sabnis, co-founder and CEO of Adaptyx Biosciences.Adaptyx is a Stanford spinout developing wearable technology for continuous molecular monitoring.Over the past 20 years, Vijit has worked at the intersection of deep technology as an inventor, founder, and investor. Before Adaptyx, he was a Partner at Khosla Ventures and co-founded Solar Junction to commercialize high-efficiency solar cell technology. He holds a Ph.D. in Electrical Engineering from Stanford.In this interview, Vijit discusses how to recognize when a scientific idea is worth building a company around, how to build startup-style learning cycles when spinning technology out of academia, and designing products that are easy for clinicians and consumers to adopt. Before we dive into the discussion, I wanted to mention a few things:First, if you’re into learning from medical device founders and CEOs and want to know when new interviews are live, head over to Medsider.com and sign up for our free newsletter.And if you’re ready to level up your medtech game, you should check out Medsider Courses — 8-week masterclasses covering topics like fundraising, M&A and exit planning, design and development, clinical and regulatory strategy, and commercialization.These courses, featuring hard-earned lessons from elite medtech CEOs, can be purchased individually or come free with our All-Access Pass.If you'd rather read than listen, here's a link to the full interview with Vijit Sabnis, which includes a link to ScottBot — an AI version of host Scott Nelson trained on every Medsider interview and playbook. Feel free to ask ScottBot any questions you'd like!KEY MOMENTS FROM THE INTERVIEW(03:17) - Vijit's path from Stanford, solar energy, and venture capital to building Adaptyx (07:25) - How Adaptyx is trying to do for hormones what continuous glucose monitors did for diabetes (13:50) - The signals Vijit looked for before founding Adaptyx (25:35) - How Adaptyx turned academic research into startup-speed learning cycles (32:15) - Why cortisol became the company’s first clinical application (36:26) - How Adaptyx is designing new molecular data to fit existing clinical workflows (42:12) - Why new consumer health platforms opened new paths to commercialization (47:24) - Fundraising in an era of shorter attention spans

And we developed a conviction that all of that research that was done in academia, we could processize it, we could automate it, we could build a software layer on top with intelligence, we could build new screening tools that could all be done automated. And I asked Alex, hey, could we squeeze that year down to like weeks? Could we like do that? And he's like, I think we could go do that. And I'm like, well, if we can do that, Now we have startup-style learning cycles, right? Now you can go try to develop something new, see what you get, fix it, and just keep doing that, and scale that massively in parallel.

So that would be singular unlocking conviction to go build adaptives. Welcome to MedSider, where you can learn from the brightest founders and CEOs in medical devices and health technology. Join tens of thousands of ambitious doers as we unpack the insights, tactics, and secrets behind the most successful life science startups in the world. Now here's your host, Scott Nelson. Hey everyone, in this episode of MedSider, we sat down with VJIT Sabness, co-founder and CEO of Adaptix Biosciences. Adaptix is a Stanford spin-out developing wearable technology for continuous molecular monitoring. Over the past 20 years, Vigit has worked at the intersection of deep technology as an inventor, founder, and investor. Before Adaptics, he was partner at KOSLA Ventures and co-founded Solar Junction to commercialize high-efficiency solar cell technology.

He holds a PhD in electrical engineering from Stanford. Here are a few topics we explored in this conversation. First, the signals to look for before building a company around one particular idea. Second, what prevents promising academic research from becoming a real startup? Third, how do you choose the first indication for a platform technology with several potential applications? And last, how do you build adoption into a product before? it's ready for commercialization. Before we dive into the full episode, if you're a MedTech founder or CEO preparing to raise capital, you should check out the MedSiter fundraising cohort. This four-week

live workshop combines small group sessions with real-time feedback to help you sharpen your investor story, build a targeted investor pipeline, and run a focused fundraising sprint instead of a never-ending slog. Over the month, you'll walk away with an investor-ready narrative and deck, outreach scripts that actually get responses, a refreshed LinkedIn profile, a simple content plan that keeps you on investors radar and a repeatable system for running your raise. You can join the waitlist at medsider.com forward slash fundraising cohort. Again, that's medsider.com forward slash fundraising cohort. All right, let's get to the interview.

All right, Vijit, welcome to MedSider Radio. Appreciate you coming on. Thanks so much for having me. It's awesome. I've been listening to your podcast for quite a while, and I'm really honored to be a guest today. I'm honored to have you, and it's always fun to have someone on, right, that's been following kind of the interviews over the evening. years. So I recorded a very short bio at the outset of this interview, but for those that aren't

familiar as familiar as I am now, doing a little bit of research in front of this conversation, give us like the one to two minute overview of your story leading up to kind of mid-20206 here. You know, my background is I did my PhD at Stanford a long, long time ago. I was there in the late 90s and early 2000s. It was a super fun time at Stanford. The internet was being built out. and I did my PhD in optoelectronics and optical telecommunications. And so I ended up starting off my career in that, joining another Stanford spinoff here in Palo Alto, that was working in that space,

completely different than what I'm doing today. And that was a fun three-and-a-half-year journey to really understand new technology development, you know, inside of a startup. And then after that, I had the opportunity to spin out a technology, technology from Stanford into a solar energy company called Solar Junction way back in 2007. And we took essentially a PowerPoint idea with very little behind it. And back then it was a different era in terms of these kinds of companies getting funded.

But solar was hot back then. And so we ended up building the company. And over time, raising about $65 million in venture capital, taking that concept into the highest efficiency solar cells the world had ever seen at that time, which was quite a ride. And, you know, tackling all the commercial headwinds that the solar energy industry had back then and managing to get an exit to a group in Saudi Arabia in 2014. So quite a ride in building a team and managing through also a regulated industry and navigating that entire process there. And then I had a wonderful opportunity to become a venture capital investor starting in

2015. And it was a complete career pivot for me where I ended up spending, you know, about a third to half of my time looking at medical device and health technologies, really at the aim of taking my electrical engineering background, looking at sensors, looking at imaging, looking at new modalities of generating lots and lots of data. And back then, we had the conviction that big data was going to help us sort out all these signals that we were getting and that they were going to be really valuable. And obviously today with AI, we kind of take that for granted and absolutely loved what I was doing there.

But while I had that job, I was always jealous of the amazing entrepreneurs that I was meeting and that we had the chance to fund and follow. and I just had this burning itch to go build another company on my own. And I was very, very passionate about continuous monitoring and had the opportunity to connect with Professor Tom So at Stanford, who's built this amazing technology over the last 18 years. And over the period of a few years of incubating this, some ups and downs along the way, including COVID,

that started just when we got started on this, we were able to launch it down. optics back in the fall of 2022 and have made some really exciting progress since then. It would be fun to kind of dig into this in a little bit more detail. But anyone with an optics background always like my signals kind of go up or at least I see it as like really eye signals that I'm dealing with someone's who, uh, whose furnace is burning hotter than mine. Right. I'm a biology guy by background. And so even with with Juve and in a fast wave, I like kind of somewhat fell into this world of like optics and the fast wave. It's a little bit more

laser-specific, but it's like I'm always amazed at the level of brilliance, right, in the, you know, with PhDs that are coming out of optics programs. So anyway, kudos to you, but yeah, yeah, super, super fun story. And I obviously will spend most of our time talking about adaptics, but I'm hoping, hopefully you can share a little bit more learnings, right, that you've gleaned, kind of sitting on both sides of the table. But with that said, I'm looking at the website right now, adaptix.com.com.com.com.com.com. Adaptics.com.com. For someone that's never heard of this, right, before, if we're at a July 4th family gathering

and I'm maybe a cousin that you haven't seen in 10 years, right? Like, what's the, how are you explaining this? You know, the easiest way to think about what we're doing is, and I think all of us intuitively know this, our body, they're changing all the time. We are dynamic creatures. Neither of us feels exactly the same way today as we did yesterday. And one of the burning unmet needs is the ability

to understand continuously, to be able to gather a curve about important markers in our body. And we have that today, you know, for a handful of metrics. For example, the continuous glucose monitor over the last couple of decades has revolutionized the management of diabetes. But we don't have much more beyond glucose. We have oxygen sensing, which we can do with smart watches and in clinical grade versions of that. Today we can now also measure ketone bodies and lactate. But think about the hundreds or even thousands of other molecules that are dynamically changing and affecting our health, both clinical health, as well as our everyday consumer health. That's our mission at Adapics is to bring a wearable patch at home, which over time,

we're not going to do everything at once, but over time can increasingly measure more and more molecules continuously. And our aim is to really tie this into very specific clinical and then later consumer applications, they're going to provide a lot of value. We're not in the business of generating data for fun. We're only going to generate data that's actionable and that's really valuable. But there's so much white space and landscape to build into. And the bottleneck has been technology. This is a very underappreciated space, almost because, and I've been on this journey now since 2020, people just didn't think it was possible. So we don't even really think about this. The world is based on blood testing, which is obviously wonderful. We will all benefit from that every

year. But there is lots and lots of things that we ought to be measuring a lot more frequently. And there's some really big macro trends behind that I think are making now like a great time to build a company in this space. Yeah, no doubt. There's a lot of strong tail ones. I'll put it this way. Like 10 years ago, I wouldn't have thought that you'd listen to a popular technology podcast where with a certain amount of frequency, right, they're talking about what Brian Johnson is, you know, posting on X, right? You know what I mean? And so it's like, it's definitely taken on a new sort of fervor, even over the past five years, I would, I would say. So yeah, really significant, really significant tailwinds. And I get for everyone listening,

Adaptix.comio, you got to go check out the website. It's a really cool site, but also the technology, I think is super interesting. But in terms of the form factor, it's a, it's a patch, at least the iterations you're working on now, it's a patch. It's not a wearable. It's not a ring, it's not a watch, it's a patch. It's going to end up iterating down into the same form factor as a continuous glucose monitor. You're going to put it on and then you're going to forget about it. And you know, you may wear this thing for a couple of days for certain conditions or you may wear it for example up to a couple of weeks and then repeat that if you need to. So we're looking at different durations of wear depending on the different applications that we're, you know,

that we're going to unlock. Got it. And I mentioned this earlier. We're recording this in mid-two in case you happen to be listening to this, you know, three, six months down the road. Where's the company at, you know, current state in terms of kind of life cycle? You know, we're about three and a half years old, a little older than that. We've been building prototypes ever since, you know, we started the company. For about the last 15 months, we have been doing human studies under IRB guidance. And really just working through, does this work, you know, in humans? You get a lot of stuff working on the bench top, and that is very, very difficult.

do. But for a company like this to gain any traction, it's the human data that we need. And that's extraordinarily difficult. So we've been, you know, we've been coming up that learning curve. 2025 was all about banging our head against the wall. The very, very difficult stuff. And I'm so proud of our team that over the last six months, you know, Scott, I've built, you know, I built my solar company. I've had the opportunity to watch so many entrepreneurs build these really amazing companies when I was a venture capital investor. And the way I think about it is you got to climb this ladder or climb up this mountain. And there's just like boulders coming out. And you don't get to have success, any kind of success, even that intermediate level of success, until you get past some

of those. It's kind of like that SpaceX story where they had failure after failure after failure. And you just got to like knock those problems down one after another. And we still have a lot more to knock down. But what is really exciting is, you know, over the last six months, we've been able to show that we've been able to measure some of our key markers continuously over multiple days, really to de-risk, you know, the core science of what we're doing. And now we can start to really address some of those commercial risks and talk about what is the pathway, you know, through that FDA approval, ultimately collecting all that clinical data that we need. And it's a really exciting space for us because at the end of the day,

clinical data speaks loudly, anyone can look at what we're doing and say, okay, well, you know, this thing actually works, you know, and this thing, you know, has a, has the potential to ultimately be a big deal. So exciting times for us, but again, I feel like we've been dodging and smashing boulders that are coming down the hill from us all the time. And they've gotten a little smaller, those boulders. So it's a good place to be. We got a, we got a ways to get out. They've gotten smaller and you've gotten faster at dodging.

Exactly. It's funny that you say that because I was just recording an interview earlier today with Bob Paulson, who's kind of a serial, kind of more pure play med tech entrepreneur, but a number of different startups under his belt over the years. And we were talking about kind of just creating a category one CBT code, right? Which is what, you know, his company's been focused on over the past four to five years. And I was like, so, so it sounds like, like you've been able to climb the reimbursement mountain. He was like, well, yeah, but we're just

trying to stay here. You know what I mean? Not fall off the mountain. You know what I mean? I was like, that's a good, that's a really good analogy, right? Because it doesn't, it certainly doesn't. The boulders never really seem to kind of stop, maybe to get a little bit smaller. Yeah, exactly. You get better at at pivoting around them. That's a good kind of segue into kind of maybe the next, call it 30 minutes or so of the, of the discussion, which is, I think, kind of, you know, intended to cover like more foundational, you know, foundational aspects of kind of company building. And I guess the first one I wanted to get to was, was really kind of talking about your transition from, you know, kind of operator to venture

investor now to operator again. And so I guess you've seen a ton of ideas right over the years. You're in the heart of Silicon Valley. What did you see early on in Adaptics that said, you know, I'm going to spend the next, what I call it, five to ten years or maybe even longer, right, focused on this. And maybe frame that up in a way of like other entrepreneurs, right, that are thinking about taking a swing and an idea, what should they be thinking about? What should be the signs that maybe would cause them to, you know, to lean in, you know, with more seriousness? You know, I think this is multifactor.

I think there's a lot of things that you'd like to see line up. You know, for me, my path into electrical engineering, my path into optoelectronics, it was not the only thing I could do. I could have been a physician. And I sometimes joke with my friends that maybe sort of later in my career, you know, now. I'm sort of back to doing maybe what I should have been doing or what I could have been doing. And so I think for me that, you know, when I have the opportunity to be an investor, you know, and I was asked you, hey, would you like to, you know, take a look at these technologies and help build the firm, you know,

in that direction along with several other really talented partners, it was very easy for me to go do. It was something that I wanted to go do. Not everyone wants to do that mid-career pivot. Everyone wants to go do that, but I'm here in Silicon Valley and these types of things happen. And so for me, it was, it was personal. I absolutely love this. It was solar energy at that time was not in a great place here in the U.S. So it was something that I felt that I needed to go off and go do something new anyways. And I was just so grateful to have that opportunity.

But I've been thinking about this stuff for decades. and the thing that sort of led me to where I am today is, you know, when I, when I started working as an investor, the CGM was relatively new. It had been out for a while, but more and more people were starting to use it. And we managed to get our hands on some of these CGMs. And it became very evident to us that having a curve, and I'm an engineer, so this is, to me, this is like, duh, right? Of course you want a curve rather than a single data point. But having, you know, that continuous curve and being able to look at my behavior and my metabolic health and what that means, it's an absolute game changer. And, you know, physicians don't oftentimes think of things that way because,

you know, our world is based in blood testing. But it became very easy for me to, to, and the rest of the partners at the firm I was at, to develop a conviction around, hey, wearables are going to be really important. continuous monitoring is going to be really, really valuable. And the Holy Grail that we were looking for at that time was, could we truly measure some of these molecular signatures non-invasively? Could we do this with a watch through the skin, maybe on the ear, for example, where you can oftentimes get good blood profusion? And so at that time, we were looking at, for example, non-invasive glucose sensing, which folks continue to work on today, non-invasive blood pressure sensing. And there's been progress in these areas, particularly in the latter one with at least one company getting

clinical FDA approval and now consumer wearables, you know, making some inroads into that. But we were always looking for a platform. You know, when you look at the number of blood tests out there today, there are thousands. You know, there's probably 50 or 100 that are the main ones that we look at. But when you look at everything, for example, that LabCorp or Quest offer, it's thousands. And when you start mapping that into different clinical conditions, it's obvious, like, if we could measure these things and we could get granular data, that this is going to be very valuable. And there's really two categories of continuous data that the world needs to be aware of. There are some markers that move quickly. Glucose is one. Insulin is another one. Drug monitoring is

another one. You take a drug, that drug level is going to go up. And depending on lots of drugs, will metabolize over the course of a few hours. And you might want to look at that very carefully. Various hormones, which is one of our foci, do change throughout the day. So that's what kind of what we call it Adoptics, dynamic physiology. And that is completely lost outside of glucose and soon-to-be lactate and ketones. Outside of those markers, we can't really measure anything continuously. So dynamic physiology and measurement of that is not having as big of an impact

as it needs to. The other category that's missing in healthcare today is an easy way to collect molecular trends. So there are many, many markers, for example, that are kind of supposed to be flat. So not that interesting to measure with a blood test. It's just kind of supposed to be flat and, you know, that number is supposed to be dialed in. But there are classes of patients that when they are sick. For example, heart failure patients that particularly after they've been hospitalized, then get onto a lot of meds, and their situation can change over time. And in today's medicine with relying on infrequent blood tests, you miss all of those changes and trends. And oftentimes we get to those patients too late. This could be for diuretics. This could be for potassium.

This could be for detecting decompensation early. And so we look at those applications where changes in trends that could be captured with a wearable represent like a really, really big unmet need. And so, you know, like we saw this coming. We were looking for platform technologies. And when I reconnected with Professor Tom, so who by the way was my old classmate from Stanford a gazette years ago, I hadn't kept in touch with them, but I reconnected. with him, we were introduced by a common friend at Wilson Sincini. I learned that he had been

building a platform and I was like, wow, this is what I've been looking for for almost five years. And let's go see, you know, if we can go turn this into a real technology and ultimately a real company. So I think there was a deep personal conviction. Like I'm on a mission here at Adoptics. I think this technology is needed. I think it's inevitable. But just as important, I think the market is moving behind this. We've seen AI explode, obviously, recently. But even a decade ago, we could see big data starting to turn lots of different data sources into something that's a lot more insightful, a lot more actionable. We've seen consumer wearables really take off. Obviously, we've seen in just recent weeks, ORA filing for going public, whoop raising a big round.

We've seen health influencers come on board on YouTube and other channels really, talking about managing their own health. And I think all of this just says the world has a need and an appetite for more data. And companies that can deliver unique data sources are now going to be able to deliver something that's much more valuable today. And in the future, we were able to 10 years ago. And today, when I think, for example, about adaptics and delivering continuous data streams, AI is going to be ingesting our data first. It's not going to be a physical looking at this first, it's all going to be processed by AI. AI is going to have context of the patient, of the medical records, whatever is available in that particular data ecosystem. And the value that

we're going to get out of these unique data streams, I think, is exponentially higher today than what it would have been 10 years ago. And these are all the things that I'd been seeing and sort of contemplating. And when I met Professor Tomso and I said, hey, this is not a one molecule technology. This could be a platform, if done appropriately and carefully over time. Hey, this could be like the next big wave beyond, for example, like what we're doing in today's CGMs. And so I just knew that, hey, this was a mission I could latch on to and go build a good team around and go do for a very long time. You have me leaning in as you're kind of describing, describing some of the context around why you decide to kind of, you know, go all in on adaptics. In terms of the

technology itself and being able to measure molecules in maybe a different way. Has there been some sort of some breakthroughs or even, even recently that are allowing, you know, folks like Tom, right, to kind of see some early wins, even if it's on benches. Has that kind of that landscape changed pretty dramatically over the past, call it handful of years? So Tom and also Professor Kevin Plachco, they were at the UC Santa Barbara together. Tom moved to Stanford a little over a decade ago. So the two of them really invented this entire field of aptamer-based molecular switches. At Adoptics, we call them programmable molecular switches. And this has been a long journey.

This has been fundamental research that was building on each other each year, starting at UC Santa Barbara. That work has been continuing. There's other academic groups working on this. And Tom and Kevin had a breakthrough paper in 2013, where they showed the and this was done in a rat model, you know, of measuring a few different drugs continuously. And what the technology is is a completely new way of measuring the concentration of molecules inside the body continuously. And these are tiny strands of DNA that are designed to latch on to a molecule of interest. So take a target, it could be a drug, it could be a hormone. But here's like

the real genius is not only does it latch onto the molecule, but it will let go a little while later. And it does that reversibly. So it does that cyclically. So here you have these molecular switches sitting, in our case, interstitial fluid. And along comes, for example, a hormone and it will be captured by this molecular switch. We can read that out, but it lets go. And it kind of is always grabbing and letting go. This is different from a blood test. In a blood test, we want to to capture that analyte, make a measurement, and then we're done. We throw that assay away. But what we're doing is we're sitting inside that interstitial fluid, and it's just sitting there, there's no sample preparation going on, and it's just passively grabbing and letting go these molecules,

and then we turn that into a measurable signal. In our case, it turns in ultimately into an electrical signal. And that was the breakthrough of this passive switch that's turning on and off. And the really cool thing is we can design these switches for nearly any molecule that we want to sense that's present in dermal interstitial fluid. And so they've been developing this. This is obviously like a big scientific breakthrough. There's a lot of like tools that you have to build to understand how to synthesize these molecules. Tom has been a real pioneer in developing tool sets around designing and screening these molecules for a long time. There is a design methodology for building these switches, lots of trade secrets.

And when I came to this, you know, I would say in academia, they had done these for like a handful of switches. And we always knew in principle we could scale this to lots of different switches. And after my time as an investor, I ended up joining Stanford for a year as a researcher. And so Tom was my boss, my old grad school, my old grad schoolmate ended up. being my boss, and so I joined Stanford Med School as a researcher, and I was embedded in his research lab. I worked side by side with the grad students. I wanted to have that conviction that this technology was translatable outside of academia, you know, and make it ready for commercialization. That is an extremely tricky thing to do. I do not generally recommend this, because it's really, really hard.

But what made it workable for me was when I joined the lab, my first week was discouraging and then incredibly encouraging. When I got into the lab, I saw all the students hand pipetting chemistry around as they were developing these molecular switches. Long days, 12, 14-hour days to sort of do like a series of steps. Lots of bespoke processes talking to each other. Does this going to work? Is that going to work? And I was like, hey, how long does it take to sort of get somewhere like reasonable, like on one of these switches? And they were like, you know, maybe a year, you know, maybe longer. And I was like, uh-oh. This is, this does not sound like a startup, right? But, you know, much to my, you know, very good luck. I met a person who was going to be my

co-founder, Dr. Alex Yoshikawa, who had just finished his PhD at Stanford. And he, he was staying on as a post-talk and figure out what to do next. And Alex has this very unique background. Before becoming a PhD student, he worked at a startup for three and a half years. He knows how to build startups on his own because he had done this as an early employee at a company called Emerald Therapeutics and then later Emerald Cloud Lab. And the really key amazing insight was Emerald Cloud Lab is this amazing company that does biology in the cloud.

They scale up lab automation to do experiments for companies. And so they've got liquid handling and PCR and all sorts of stuff, all driven by software. And they do that automatically. And he was one of the early people who figured out how to do that in those early days a long time ago. And we developed a conviction that all of that research that was done in academia, we could processize it, we could automate it, we could build a software layer on top with intelligence. we could build new screening tools that could all be done automated. And I asked Alex, hey, could we squeeze that year down to like weeks?

Like, could we like do that? And he's like, I think we could go do that. And I'm like, well, if we can do that, now we have startup style learning cycles, right? Now you can go try to develop something new, see what you get, fix it and just keep doing that. And scale that massively in parallel. So that was the singular unlocking conviction to go build adaptics. Because if it was going to be like super long learning cycles, like we do see in other industries, that's hard to build a startup on.

And it's super hard in MedTech as well. I mean, this is the biggest challenge in MetTech is to be able to figure out how learn and iterate rapidly. Obviously, each of us has to do clinical studies where you can't really speed that up, but at least on the development side, if you can learn as much as you can and iterate very, very rapidly. And when I saw that, and we really talked about it,

and then we also did some of the core technology development and animal studies while I was doing that short stint at Stanford, we decided, hey, let's go take a swing at this. And, you know, it's taken us a while. You know, again, we had to dodge those boulders and we got hit quite a few times because no one has ever done this before. But we are now a legit plight. platform and we can iterate on these molecular sensors extraordinarily rapidly.

It's a very exciting space to be in. It makes me wonder how much really interesting technology is sort of stuck in academia, largely because of those slower iteration cycles, right? And could there be entrepreneurs like yourself, right, that come in and with a fresh look, say, look, I mean, this is the constraint, really? I mean, there's other ways to solve this with startup-style thinking. Hey, everyone, let's take a quick break to catch you up on Medsider courses. These eight-week courses are designed to help you learn winning formulas from world-class

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Again, that's medsider.com forward slash courses. Okay, let's get back to the conversation. This is actually a gigantic gap in the market today where, you know, I think one of the things that always has surprised me, and this happened at Solar Junction, and it has happened here at Adoptics, is there are so many things that are not or are not desirable to invest in when you're in academia.

A lot of it is just turning the crank and repeating and repeating and repeating and repeating over and over again to sort of learn your way into something that's workable. That's not really the job in academia. And there's a gap in the market, whether it's people, it's also funding, of being able to look at opportunities and trying to find where, hey, you know what? Like, if there was an investment made in that technology set and there was a small team focused on sort of iterating in that way, you can dramatically accelerate where, you can dramatically accelerate where things are in academia to now making it commercially interesting. That's not always

going to work, and that's a very tricky and risky thing. I don't have any general guidelines, but we had that conviction, you know, pre-adaptics. It's the core reason why we started the company. But I do generally think that there's a lot of things in academia that are sitting there stranded. Right? It kind of look like they're maybe way too early, but maybe they're not. Yeah. Yeah. Yeah, no doubt. You mentioned the platform aspects of this technology, right, a couple different times. But you've chosen to start out with cortisol, I believe, first. So help us think through your approach to that, right? Because I think that's often a challenge for, especially for like really innovative companies, is like, hey, we could go several different directions here,

but we've got to choose, we've got to choose one. And so walk us through kind of your thought process and choosing cortisol to kind of start with. So I give you a bunch of different reasons. One is it's really hard. And if you can managed to do something apart, like hopefully, hopefully you're, you're creating value there. But the core reason is, you know, cortisol is a hormone. It's a dynamic hormone that changes throughout the day. And as we looked into this, let me back up here a little bit, hormone is this daily rhythm. And today, cortisol is measured with either a morning blood test, a late night saliva test. We can also collect urine 24 hours and try to estimate total production. The problem

The problem is that's like taking three data points and trying to recreate an entire curve. And this is fundamentally preventing the appropriate understanding of cortisol rhythms and how it's impacting health. So we looked at that screaming out at us as like a huge unmet need that maps into lots and lots of clinical applications. Let me draw an analogy for you. So we're all familiar with the electrocardiogram, that little electrical pulse that that's coming out of your heart.

The electrocardiogram, you just take that single curve. It tells you so much about your body. It actually maps into six different health systems within your body. We looked at the number of derivable features within that one continuous signal. There's something like over 100 that you can map into different diagnostic use cases. And we looked at the same thing for cortisol. It's the same story. cortisol maps into actually 10 different health systems in your body.

And the number of derivable features that we can take out of that cortisol curve and map into different insights and diagnoses is very, very large. Like we've been counting these, it's going to be like that electrocardiogram. So that was sort of like one really big conviction. The other thing is, you know, we're really focused on hormone sensing. And hormones are very different, for example, from a marker like glucose, which is what we matter today in diabetes. Hormones are the operating system of the body. They don't affect one disease or one organ. They have receptors across every organ system in the body. In many cases,

every cell in the body has a cortisol receptor. And so when we think about the value cortisol monitoring can bring to the market, we're going to start in like very, very focused conditions where cortisol dysregulation is clearly known to be a driver of these diseases or these conditions. But over time, the literature has shown over the last several decades that cortisol dysregulation affects a whole host of conditions. And that, again, is like what we like to call it, one of the molecules that's in the operating system of the body. And this is generally true of all hormones, which is why they're so incredibly important.

And this is just a gigantic opportunity with technology that really has not been possible today. You'll know, for example, with the marker estrogen, when a woman gets older and her estradi levels decrease, there are a whole range of health systems, you know, in her body that begin to change. And this is a massive opportunity across all of hormones. So it's not a one shot on goal marker. It's many, many shots on goal. But we are focusing on very specific conditions, which we think are more amenable for early adoption, and then we'll build into others over time.

Got it. Yeah, and I think anyone that's ever had a cortisol test, probably in most cases, probably either saliva or blood, understands that when you start to kind of peel back the layers of the onion, I mean, how is it that's accurate, right? I mean, because my cortisol is going to be, like, wildly different. You know, we looked at the patient journey for a lot of these diseases, and there is so much follow-up testing that is needed to just sort the step out. It can take months to even years of follow-up testing to conclusively understand what's going on. So that was again another

opportunity for us is we can run a one day or few days of just getting that curve. And with pattern recognition being so easy today with algorithms and with AI, we can tell a physician exactly what's going on with someone's cortisol rhythm. It's a huge opportunity. On that note, I think my notes show, and I don't recall the exact date, but you recently presented, you know, first in human data on this, you know, continuous cortisol diagnostic at the ADA. When you think about the reaction, right, from physicians, is there generally an acceptance of using kind of a new way to measure cortisol? Or are you seeing pushback or what are you doing to try to counter maybe some of the skepticism around this new way to measure cortisol? You know, I think for all of us working in MetTech, we have to think very, very carefully about workflow integration and workflow optimization. So this is going to be a new type of data,

how a physician prescribes it, how they look at the data, when are we going to be able to give very clear diagnoses versus maybe more screening type of information. There are naturally, I think a lot of questions around that. But what I would say is, and this has been very nice to see because it wasn't always like this, you know, when we were incubating adoptics and even early on, once you show the data and you start to say, hey, look, this part of the curve tells you this. This other part of the curve tells you this, right? This replaces all the testing that we could do. And with algorithms very quickly, we can start to, you know, bucket, you know, these patients. And so we're starting to see a lot of, you know, interest in like, hey, this could be revolutionary.

I don't have to think about that blood test and, you know, think about, you know, was it done at the right time? Did we catch the peak? Do we need to follow up with this? Like, I can get that curve. I can get that curve multiple times. And I can start to like really understand that. And so, you know, the response we've gotten in just the last three weeks has been really, really positive. and one of the nice things about cortisol is not only is there a lot of clinical indications for us to go into, but consumers have been interested in cortisol for a very, very long time. And each of us, for example, are affected by stress. Ironically, I'm building a cortisol company and I'm affected by just a stress of trying to build a startup company. And funnily, we have seen even internally that our cortisol can be disaragasy.

and for a variety of different reasons. But yeah, I mean, I think that the, you know, the reaction has been positive. I do think the experts and the key opinion leaders we're working with are cautiously optimistic about us bringing the market. But, you know, the experts in the area, they understand that, like, hey, you know,

this data is great, but let's collect a lot more data, which we're in the process of doing. And let's figure out how we're really going to report that data back into the system. we can't put extra interpretation burden on the physicians, on the medical system. And this is obviously across MetTech. And so that's been, I think a lot of the discussions around how do we shape a product offering, how do we make sure that the on-the-ground clinicians, the nurses, the physicians are able to use

the device, prescribe the device very easily and get that immediate value that we ultimately want to deliver. So, so crucial, right, to understand kind of the full, the full ecosystem, right, the workflow, how your technology fits into that, who wins, who loses, who's impacted, et cetera. Yeah, at all, it all matters so much, which is one of the fun things about med tech. It's also incredibly challenging, too, as you well know. I want to get to the topic of fundraising, right, especially considering you've sat on both sides of the table, but before we get there, we've talked about like the huge opportunity with consumers, right? You're

obviously starting out kind of with a bit more of like a medical focus. How are you balancing the two? I mean, are you moving kind of both, both along and parallel? Is it kind of medical first and we'll see kind of the consumer opportunity down the road. Like, how are you thinking about sequencing those? Look, it's a great question. And look, it's an evolving story and strategy. Our device does have to go through the FDA. We are a minimally invasive device. So just like a CGM, we've got a small polymer probe that breaks the skin. And so we will be a class two submission going through the FDA. And with that, you know, anyone building in MetTech, our number one currency is trust.

trust, right? And, you know, we want to build a company that hopefully, you know, is around for a very long time. And trust is our fundamental currency. And so going into clinical applications where we've got the endocrinologists, like, deeply engaged, understanding what we're doing, being able to apply this in some of the more severe conditions initially, and then moving in this, you know, towards, you know, the wider spectrum of cortisol disres. regulation, I think is a very, very valuable and needed path. And, you know, as I said, cortisol affects every major organ system in the body. So there's lots and lots of use cases. We're going to start, you know, in one set of use cases, but we're already seeing interest from physicians of like, hey, I would use this over here in my clinic. I work in autoimmune. Audioimmune is all about

inflammatory conditions. Cortisol plays an important role, you know, in managing, you know, those patients. And that's not something we're starting in initially, at least that's not our current plan, but we're seeing lots and lots of opportunity there. So we think it's going to be actually a virtuous cycle. More on the consumer side, there's going to be a lot of people who are normal or a little bit less than normal, who are just undergoing normal everyday stress. We think chronic stress is a massive, massive opportunity. One thing that I am acutely aware of is that developing a consumer-facing product,

takes a lot of care. It takes, you know, a lot of communication with the FDA on what we're going to do and what we're not going to do. No one has ever really built a stress product properly. We kind of do it. You know, consumer wearables today approximate stress with things like HRV. Cortisol is the direct measurement of your stress response, along with adrenaline nor adrenaline, but we're focusing on cortisol. And this gives us an opportunity to build and shape a product that has never, ever been done before. And it's going to take us a little bit of time to do that. This is an extraordinarily exciting opportunity because stress touches, you know, sleep, meditation, breathing, a gigantic list of supplements, exercise, sleep architecture, so many different

things that we want to walk into this. And one of the things we're doing right now is we're partnering with consumer wearable companies that are saying, hey, Adoptics, If we take a look at your device under a clinical study, look at cortisol levels, and we pair that with consumer wearable data, and we start to build out a more deeper understanding of stress and what a product would be. And we think, for example, on a consumer side,

a really killer application would be, you know, a consumer wearable today, that data paired with Adoptics as cortisol data is going to give us an even bigger picture that ultimately, I think, together brings a really exciting product. And so we're walking into that. It's a really exciting space. We're now getting a lot of interest. We're talking to, you know, a lot of the major wearable companies about partnering with them and thinking about really interesting ways to bring

this to market. You know, when I started the company three and a half years ago, investors and advisors were like, look, Vigit, you got to pick one. You can't be everything to everyone like, you know, pick and focus and just do one or the other. The really interesting thing, Scott, is the world has changed. We have big, successful consumer health companies that we didn't have three years ago, four years ago. For example, hymns and hers, Roe, you know, you can go there. They are now starting to manage more and more clinical type of care. We have blood testing companies like function health, levels health, superpower, inside tracker, right? As consumers, we're now able to go to these companies, order a bunch of blood tests, crack those longitudinally,

now get an MRI from them if we want to, get specialty diagnostics labs like an advanced lipid panel, an aging panel, for example, AI sitting on top of that. That's only going to grow And for example, Andresen Horowitz a number of years ago said, hey, one of the next big trillion-dollar companies is going to be a consumer health platform. I don't know which one it's going to be, but I do think it's going to happen. I'm really excited about it. I am getting a lot of value around that. Adoptics now has the opportunity to partner with one of these companies.

They're going to have this gigantic audience, this gigantic distribution system. We can now offer, you know, a wearable sensor that can be used. again, with the blessing of the FDA, through a channel like that, without having to build all of that on our own. And that, I think, is a fundamental structural shift that has really opened my mind to saying, hey, we can have one sensor, we can build different product offerings around that, maybe different markers, certainly the software, the data, the data presentations going to be a little bit different for clinical versus consumer.

By the way, Dexcom and Abbott have both done that on the CDM side. again, that was another big tailwind for us to see and to see success and to see consumers, you know, really getting behind that. And we think there's going to be a big appetite for that. So lots of tailwinds, lots of changes. The world is different today than it was previously. So we are, we're keeping our options open and we're trying to build this so we can serve ultimately both of those markets. It's so important to keep optionality on the table if you can, right, as a startup. up. And I got to think, you know, whatever, two, three, four years ago when some of those

investors, who are probably smart folks are telling you to focus on one area. They also didn't see, you know, whoop raising at whatever, it was like $11 billion valuation or something crazy. I don't know. I can't remember exactly. It was a big number. Yeah, I don't think a lot of people saw that, saw that coming. So I love kind of your thinking on that. I know I want to leave a little little bit of time to get to the rapid fire portion in the interview, but I got to ask you a question about fundraising, right? Since you have a, you sat in unique seats, right, on both sides of the table. How has that helped, I guess, your journey, you know, raising capital for Adaptics, because I think what my notes or my notes, you know, and then lead up to this conversation,

I think you've raised a little over 20 million kind of in financing to date, something like that. I don't have the exact number. But because you, you know, you spent so much time, right, as, as a, you spent several years as an investor, how's that helpful? What can you tell other founders or CEOs, right, that may be, maybe especially insightful, you know, considering that experience. You know, this is an evolving story. Look, it's very difficult. You know, even for me having been on the other side of the table for a long time, you know, I think I have really come to appreciate both as an investor and now doing it on my own at Adoptics at how important storytelling is.

One other major tectonic shift that happened since I was an investor, you know, to pretty soon after I, you know, I began incubating Adoptics is attention spans have gotten shorter. When I was an investor, we largely did one hour in-person meetings. So I would look at my calendar and I would have, you know, sometimes 8 a.m. to 8 p.m. back-to-back meetings, an hour. You know, in an hour, you really get to sit down and go through. And when I was an investor, I was the deep tech catch-all partner. So I was context shifting in a really big way going from healthcare to 3D printing to sensors to autonomous. of us vehicles, all in, you know, all in the course of the day. But you can do that in an hour

meeting. But with COVID, everything shifted over to Zoom first, people being a little bit more distracted. And so this just really drove home the point. And I continue to work on this, on my own, on a daily basis of really nailing down that story, doing your best to capture people's attention. And Scott, you're really good at this, but like, you got to work on it. You got to work on it all the time. And as a founder, you know, as a CEO where this is my responsibility, it's a constantly evolving process. And, you know, I think there's situations where you could be working in a market or a device or an area that's hot. And, you know, and maybe it's a easier story.

It's a clearer story to tell. But, you know, certainly with Adoptics where, you know, it's a long-term story. Bringing a sensor like this to market is quite. a mountain to climb. We think the payoff can be there, just given a lot of the things we've talked about, you know, in the, you know, in the discussion today. But that's the single most important thing. And, you know, I think the other thing is, everyone cares about health. So you've got to think about reaching a wide range of investors. And, you know, at Adaptics, we've got some nice tailwinds, you know, from a macro kind of market standpoint. And so, you know, we look at, you know,

trying to reach generalist technology investors. Obviously, there's the MedTech investors, but also family offices, for example, and angels, right? And so you got to go broad. It's never, never easy. It seems like it just gets harder and harder as the company progresses. And, you know, particularly in the case of, you know, big opportunities like this, you know, capital needs are high. And so it's a hard thing to do, but just got to keep working at it. Yeah. Two things that stood out in that answer. One is I would have expected fundraising to maybe be slightly easier for someone with your background, but like, I think that's healthy for all of us to hear. Like, it's just never, it's always challenging. It's never easy, maybe with the exception of

Elon, you know, never, never easy to raise capital. And then two, just the importance of storytelling and always improving upon that, right? Because at the end of the day, even if your technology is really, the market's massive like yours is, super novel technology at the end of the end of you still need to capture attention, right? You still need to cause someone to lean in. It's so hard because the more you work on something, the more that's like sitting in your head, like, visiting and things. Like, I talk too much. I talk too much on this podcast, right? Right. And, and, you know, getting someone to help you boil that down, whether it's your co-founder, whether it's your spouse or a friend or, you know, there's folks out there that even do this for a living. That's been really valuable.

Yeah. I'm right there with you, right? Like, you're, we're so in the weeds, so, you know, so often that the concept of kind of zooming out, right, and trying to sort of sort of, sort of, almost reframe your story, right, to someone who's never heard it before, that's, that's way, way harder to do than, uh, than most people, most people think. So with that said, I don't we only have a few minutes left. I want to get to the rapid fire portion of this interview because this has been, this has been fun. I can tell actually you do a good job of storytelling, right? Because like, there's been several moments when I'm like, I'm pretty captured by the, by the story. So, so with that said, again, adaptix.bio is the website. We'll link to it in the

full write up on a medsider, but adapt, t-y-x. bio, ad-d-tt-y-x. bio, adaptix.bio, adaptics. bio. Highly encourage everyone to check out the website. It's really, really interesting technology. So it'll be fun to really fun, especially for someone like myself to kind of watch your journey over the next few years. But a couple rapid fire questions before we wrap this up. Let's fast forward to mid-27. What are you most excited about at Adaptics? You know, our goal is to have a boatload more data and really bringing cortisol in our fundamental stress response to lots and lots of different, you know, conditions. And we're going to be collecting data on a full. focus group of patients that I think will just immediately benefit from that. So I'm looking forward

to more and more data, which I think is fundamental to building the company. We're building a new chemistry technology, sensing chemistry to the world, and data speaks louder than really anything else. So really exciting about that. And then we've got a lot of molecules that we're going to be adding around cortisol. These are other hormones that I think just really significantly broaden and add value to what we're doing. And we're going to be bringing those off the bench top into early human studies. So really excited about both of those. That's cool. All right, what's the billboard message for other med tech or health tech entrepreneurs, right? What's like the one lesson that you think they need to really understand? Yeah. Scott, I'm going to tell you something a little

bit that's unusual. And I really struggled with this. I do not come from a health care, our MetTech background. And my advice is seek expert opinions, but do not trust it. We got so much, I tell you, Scott, when I was looking at this and Tom and I were incubating this, we got so much discouragement from the quote unquote experts. Experts are experts in the past, and you always should solicit it and write it down and think about it, but you should not blanketly follow it. And I still struggle with this on a daily basis because I do feel like a little bit of an imposter. I don't have a medical degree. I'm not an expert. This is my first medical device company. But I will tell you that like taking a hard look at it, you know, Elon says,

think about this from first principles, think about the future you want to build. That is so, so true. Because I don't think Adoptics ever would have gotten off the ground if we simply listen to the experts. Wow. I wouldn't have expected that answer, but that's really good. Very, very challenging, though, at the same time. Last question. Any advice that you'd whisper in the ears of the younger Vigit, you know, if he had a chance to go back in time? One of the biggest things that I've learned is the value of huge, huge audacious goals. We did this at Solar Junction. We're doing this at Adoptics. We're always described as crazy. You can't do that. But what the world does, doesn't recognize is when you try to reverse engineer from a crazy, crazy goal, the focus that it brings the different pathways that you'll consider that you wouldn't otherwise consider, we are doing some really crazy things that Adoptics that anyone from the outside would say, why on earth are you doing it that way? That's 100x harder. It is 100x harder, but as we crack that, we are able to climb up a gigantic taller mountain than I think other approaches would have done. And this is counterintuitive.

We walked into this in my solar company. We were very young and dumb back then. But obviously, like, you know, some of the great examples are things like SpaceX, which obviously has been in the news recently. But it is an incredibly focusing and valuable thing to do, not just in MetTech, but in any endeavor. And I'm still learning about this. We're still navigating that. But I do, believe in gigantic, you know, the big, hairy, audacious goals and reverse engineering back to today and what you need to do today to build towards that. And, you know, my former boss, and, you know, when I was an investor said, you know, be obstinate about your vision, like that big thing you want to go there, but be flexible about how you're going to climb up that mountain, but never walk

away from saying, that's my Mount Everest. And too many people kind of start to work. where we are today, say, hey, I'm going to, I'm going to climb up that mountain, and then I'm going to go find my way up the big path. But the problem is you don't know what mountain you're on. And oftentimes the mountain you think you're on, it's not actually the one that maybe you ultimately desire to be on. And so it's an evolving lesson. I continue to think about that almost on a daily basis.

But I wish I understood that when I was younger. And I think lots of people should think about that. Yeah, such good advice. And it reminds me of how powerful it is. to be close to places like Silicon Valley, right? That's what's so special about it is you have so many people that have been around other people, right, that truly understand kind of what a real audacious goal sort of looks like.

And if you're surrounded, if you're surrounded by people that think like that, it really does change your perspective. Yeah. So I know we're over on time, but now this has been a super fun conversation. I sort of expected it to be fun, but you took it a level up. So this has been great. Thanks so much. fun to speak with you, Scott. Yeah, likewise. Likewise. Likewise. I'll have you a whole other

live. But for everyone listening, again, we'll link to Adaptix website in the full write-up on MedSider. Appreciate everyone's attention, as always, until the next episode of Vetsider goes live. Everyone, take care. Hey, it's Scott again. One quick thing before you go. You see, I love bringing you insightful conversations with the best founders and CEOs of medical device and health technology startups. But here's the thing. I'd be super grateful if you could help me reach even more ambitious doers who share our passion. So if you found value in this podcast, if you found yourself nodding your head while listening, or if you simply enjoy what we're doing with Medsiter, please take a moment to leave us a review. It's super easy.

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