Medsider: Learn from Medtech and Healthtech Founders and CEOs - Fixing Healthcare Bottlenecks from First Principles: Interview with Enspectra Health CEO Gabriel Sanchez

Episode Date: December 17, 2024

In this episode of Medsider Radio, we sat down with Gabriel Sanchez, co-founder and CEO of Enspectra Health. The company's flagship VIO platform is the first FDA-cleared imaging modality for dermatology in over 25 years. Gabriel holds a B.S. in mechanical engineering from MIT and an M.S. and Ph.D. from Stanford University, where he also served as an instructor in bioengineering and launched Enspectra to commercialize his groundbreaking research. VIO enables high-resolution, noninvasive imaging for skin cancer detection and health biometrics.In this interview, Gabriel talks about his transition from academia to startups, how he narrowed down his idea to meet a pressing need in healthcare, the importance of speaking FDA’s language—or finding someone who does—and how he balances dilutive and non-dilutive funding. Before we dive into the discussion, I wanted to mention a few things:First, if you’re into learning from medical device and health technology founders and CEOs, and want to know when new interviews are live, head over to Medsider.com and sign up for our free newsletter.Second, if you want to peek behind the curtain of the world's most successful startups, you should consider a Medsider premium membership. You’ll learn the strategies and tactics that founders and CEOs use to build and grow companies like Silk Road Medical, AliveCor, Shockwave Medical, and hundreds more!We recently introduced some fantastic additions exclusively for Medsider premium members, including playbooks, which are curated collections of our top Medsider interviews on key topics like capital fundraising and risk mitigation, and 3 packages that will help you make use of our database of 750+ lifescience investors more efficiently for your fundraise and help you discover your next medical device or health technology investor!In addition to the entire back catalog of Medsider interviews over the past decade, premium members also get a copy of every volume of Medsider Mentors at no additional cost, including the latest Medsider Mentors Volume VII. If you’re interested, go to medsider.com/subscribe to learn more.Lastly, if you'd rather read than listen, here's a link to the full interview with Gabriel Sanchez. 

I'd say plenty of your strengths. Don't try not to let other outside influences and how they categorize you influence the way that you approach the problem. But I would listen to as much advice as I can. And then you've got to decide what you're going to follow. That's the way I would approach it. Because there's a lot of meaning in that. But especially if you're carving a new, if you're carving a new space,

a lot of people are going to tell you that you're wrong and you're crazy. But that's not necessary. That does not, that's not necessary and sufficient to say that you are actually doing the risks. But it can be wrong and quills. Crazy. So you want to listen to that and reflect on it a little bit? 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 is Scott. This episode of MedSider is at town with Gabriel Sanchez, co-founder and CEO of Inspector Health. Gabriel and his team are developing bio, the first FDA cleared imaging modality for dermatology in over 25 years. This novel technology enables high-resolution, non-invasive imaging for skin cancer detection and health biometrics. Gabriel holds a BS and mechanical engineering from MIT and an MS and PhD from Stanford University, where he also served as an instructor in bioengineering and launched in Spectra to commercialize his groundbreaking research. Here for you the key things that we discussed in this conversation. First, if you're an academic with a good idea, here's a simple roadmap. Assess whether your idea addresses a real pressing need, not just something people want.

Adapt your technology to align with this pressing need. Dive into prior work, even failed attempts, for inspiration and insights, and finally, be prepared to go all in. Entrepreneurship is not a part-time job. Second, start by identifying the biggest challenges in your field and target areas where your technology can create meaningful change. Take a step back and look upstream in the process to spot inefficiencies and contribute to downstream bottlenecks in healthcare. Instead of simply patching issues, think about how you can prevent the problem by addressing inefficiencies earlier in the workflow. Third, super-tri-startop's growth by strategically combining grants and venture capital. While grants

preserve equity, they can be time-consuming to secure. Paring them with venture funding, keeps operations moving while leveraging non-dilutive funding to amplify your progress. Pitch to investors by emphasizing how grants extend their capital and present grant agencies with the momentum and validation provided by investor interest. This dual funding approach not only reduces dilution and increases runway, but also enhances your project scope and scalability potential. All right, before we dive into this episode, I'm pumped to share that volume 7 of Medsider mentors is now live. This latest edition highlights key takeaways from recent Medsider interviews with incredible entrepreneurs like Bill Hunter, CEO of Canary Medical, Brian Lord, CEO of

Pristine Surgical, Don Crawford, co-founder of Safion and current CEO of Corvista Health, and other proven MedTech founders and CEOs. Look, we get it. Keeping up with every MedSider interview isn't easy. That's why we created Medsider mentors. These e-book volumes distilled the best practices and insider secrets from top founders and CEOs, all in a downloadable easy-to-digest format. To check the latest volume out, head over

to medsiderradiot com forward slash mentors. Premium members get free access to all past and future volumes plus a treasure trove of other resources. If you're not a premium member yet, you should definitely consider signing up. We recently revamped Medsider with swanky new features especially for our premium members.

In addition to every volume of Medsider mentors, you'll get full access to our entire interview library dating back to 2010. You'll also get Medsider Playbooks, curated guides, path with actionable insights and topics like fundraising, regulatory challenges, reimbursement strategies, and more. And if you're fundraising, don't miss our exclusive investor database featuring over 750 life science VCs, family offices, and angels. We've even created three custom packages to help you with your next fundraise. Learn more about Medsider mentors and our premium memberships by visiting medsiderradio.com forward slash mentors. All right, without further ado, let's dive in in the interview.

All right, Gabriel, welcome to Medside Radio. Appreciate you coming on, man. Always a pleasure. Thanks, Scott. Yeah, looking forward to the discussion and learning about some pretty, pretty cool technology for sure. With that said, I recorded a very short bio at the outset of this interview. But let's start here, without getting too far into the weeds. Give us a one to two minute kind of elevator pitch overview of your background leading up to starting in spectra. Yeah, so my journey came primarily through academia. So I did my my undergrad at MIT and my master's in PhD at Stanford and all my degrees are in mechanical engineering, but over time, I gravitated more and more into sort of the life sciences through the research I was doing

in grad school and becoming more and more interested in the medical device than life sciences space. So I invented, we'll talk about this, I invented the core technology, which is really behind in Spectra during my PhD for a completely different application for a science need really in studying neurodegenerative diseases and muscle. And I was primarily on an academic track, and my mission was to be a professor. And so I was an instructor in the bioengineering department after my PhD, and I taught for a few years, but I just really felt that we had solved some interesting problems that had been plaguing the imaging world for decades in my research, and that if we applied them to certain applications in the practical world, we could have a different type of impact. And so I decided to take the plunge. I left academia

about 10 years ago to do this full-time and licensed out some patents and raised some money and basically went from concept now to where we're post-FDA cleared. We just got a breakthrough on our next iteration of products which are going to be a little more software and AI-focused.

And we're right on the cusp of bringing this into the market. And in terms of what this is, we're working on applications in dermatology. We've developed something we call a virtual biopsy or biopsy for short. and it looks under the skin surface with cellular resolution to reveal sort of the structure and molecular composition in a way that's in many ways equivalent to what you would see on a normal

histopathology slide. And so the idea, though, is that you can get that information at the point of care, non-invasively, real-time, digitally, and in large abundance of data. And so we've been developing that's per primarily skin cancer detection. That's our long-term vision. But what we have discovered is there's a broad interest in dermatology ranging from skin health and aesthetics all the way to developing drugs for inflammatory skin conditions, and of course, obviously, an oncology for skin cancer. So that's a quick summary of where we're at.

Yeah, definitely. It sounds like a kind of a platform type of technology. And I think your background is going to be fun to dig into as well. And really your journey, right, over the past, because as you can imagine, there's a lot of, this podcast is a very startup focus. And there's a lot of physicians, PhDs, even engineers that, like, they've got what they think, is maybe a good idea in their head. And I don't needy, haven't taken the plunge yet, haven't taken a swing, debating that, etc. Definitely, I think it would be fun to get into that topic in more detail.

But this idea of virtual biopsy, tell us a little bit. I'm on the site right now, which is in spectrahealth.com. We'll only to it in the phone might up on MedSider, but for those listening, it's E-N-S-P-E-C-R-A-Halth.com, in Spectra-Helfth, just as it sounds. But for skin applications, like, out of the gate, let's not go too broad with, like, how the technology could be potentially utilized elsewhere. But like you mentioned pointed care, kind of skin diagnostics.

Give us a sense for how this is done today. And then like how is it bio? The product we call bio, that's right. Like how bio would actually use an healthcare setting now. Yeah, absolutely. I think we'll talk a little bit about making the plunge. But the key to any sort of successful venture in the space is you need to be satisfying a core need.

Right. It's wonderful that people want what you have. But that's great. But if they need it, then you're essential. And then it practically has to be necessary to be able to survive. the challenges that you need to make this happen in the medical space. So one of the things I did when I was started this company was we were looking at what we had accomplished, which was a new waste image tissue, but that wasn't, the research area was not

necessarily a commercializable direction that we could really take it. And so we took a step back and said, okay, where are the big challenges in imaging? All diagnosis, which is done with histopathology, is done with technology that's over 150 years old. It was basically developed in the 1870s. it has not changed. We talk about digital pathology, but that still hasn't changed the process. You're still cutting out the tissue.

You mounted it on glass, you stain it, and then you scan it. So it's on the back end, but that's like, you know, the wrong end of the ice cream cone in our opinion, right?

So what we were thinking about was like, can we get access to that information in a non-invasive way? That's a core need. What is the most common application for that? It's going to be disease diagnosis. What's an important disease,

cancer? What's the most abundant cancer? Skin cancer. Oh, skin's on the outside of the body. Maybe we can do it's non-invasively. So that's how we narrow our way into that. When you look at the way things are done now,

you have to go to the dermatologist to get your spot evaluated. And then if there's enough concern to take a biopsy, that biopsy gets cut at that point in the office, and then it gets shipped in FedEx to a lab, typically, unless the lab's in a big, consolidated office practice. But basically, it always goes to the lab.

It gets sliced, stained, mounted, and then imaged, and that can be a problem. anywhere from a handful of days to a week before you then see the information. And then statistically, when you look at the data, we do about 16 million biopsies a year, about, we identify roughly 8 million skin cancers, which means that about 50% of those biopsies ultimately reveal benign conditions. So that's a lot of extra scars, and these are scars in places that people don't want them. And it's a long waiting game that actually drives patients nuts when you're stressed

out not knowing what's going on. So what we want to change in the process was like, could we model what we see in other imaging, like really in radiology, right? Like you have, you don't just crack into the body or cut in. You can look inside and you can pre-plan and know what you're going to do. Could we look in an ultrasound, have the scan get done, get the data, and then evaluate the data in a way that you don't have to, you can skip all that process. And so we could essentially compress a one-week process down to something that's going to be done at the point of care. And so that's our long vision. We've taken some major steps in getting there. So we developed the technology and we proved that the technology can visualize these features that you

would normally see on a histopathology slide. And we'd prove that out in a very rigorous to feature by feature with the FDA using clinicians that have been trained on our image atlas and then tested blindly on our images to predict the histopathology. There's quite a burden because this is going a little tangent here, but I was shocked to find that we, We were the first new modality evaluated and cleared by the FDA in over 25 years. So imaging is really old, right? Like I said, the microscopes that we used for histopathology were developed in the late 1800s, x-rays over 100 years old, ultrasound's 70 years old, MRI, CT, 60 years old.

These have been really longer established even before the FDA really came into beam and they were just grandfathered in. This was the first instance, like, for the review team that we're working with at FDA where they've had to validate a new image. but we use imaging to validate the other therapy. So then the problem was like, okay, we almost need like another type of imaging that we can prepare for this too. And that's where we basically came up with this plan of imaging tissue

and then subsequently still biopsy and some of these are we're imaging people that are getting cut anyway and then building up an atlas and proving out the features and then building this up from the bottom up to show that it can really do that. And key in that in the study, getting back to your original question, was we proved that the medical assistance can, actually gather the data. So the dermatologist would do the skin check and identify the lesions of concern and they place down a targeting sticker, which is a little donut that ensures that our device goes and images in the right place. And then the assistant captures the data. So it's more

of a model like what you would see in sonography. And then those images are digitized and then they can be interpreted by the clinician at any point. Right now, these are interpreted by clinicians that have dermatopathology training and they've been trained on our image atlas to our. understand how to do the translation between the modalities in the long run. This is where we see the AI tools really helping to streamline in terms of computerated detection and CAD-CADCADD applications. And that's actually what the breakthrough designation that we got recently was for. So our vision is to digitize this process because the bottleneck in dermatologists,

we just don't have enough dermatologists. We have more people that go to a dermatologist every year than have diabetes. It's about 44 million office visits. And it's, and imagine, it's if you had to, the only way you could get your mail was to go to the post office. You'd have a traffic jam like crazy every single day, right? You have to go to the dermatologist ultimately to get a diagnosis. And despite all the activity, and this is what really drew us to this space in terms of needs, all the innovation that you see in dermatology is really focused on referring people to the dermatologist.

Should I biopsy this spot? See, these are the cameras with the AI or the sensor. type tools that are measuring correlated proxies of whether this is cancerous or not. And their whole focus is to try to funnel people that should get looked at into the dermatologist. That's really important. I think that's an upside of the funnel. We're trying to get people that should go in it. But the problem is we can't keep up with the volume now.

It's actually going to make us even more necessary. And so our vision is we're used by the dermatologist, where the bottleneck is, and try to decouple this dependence on cutting out and processing tissue. It's a long journey, but like I said, we've made some tremendous strides in that direction, and I think we've really proven that we could go the distance. So that's what I'm excited about. Yeah, I like that analogy, that funnel analogy where you're solving for that bottom of the funnel bottleneck, which is seems to be the bottom of the funnel is always a little bit more narrow,

but it seems like it's really bulging at this point. Doing more and more. Yeah, I had no idea like the prevalence of the number of dermatology does it. That's cool. So, like, where are you guys at in terms of stage right now? Yeah, so we're right on the cusp of commercialization. We'd raised a series A in 2019, and that was focused on building the clinical version of the device, running the studies that we were going to need to get through the first FDA clearances,

executing those studies, and then getting the clearance. And so we ran two clinical trials over the course of the last few years of roughly 200 patients in total. One was a preliminary evaluation in healthy skin to just baseline the technology and understand what we see in normal tissue. And then the second was a targeted study. And then this is something we honed in on by the Q submission process with the FDA to figure out, okay, how do we have established a validation for a new modality for imaging some of these features of histopathology and living tissue? And we executed that study. And in 2023, we submitted the data to the FDA and then we got cleared in early 2024. And out of that step, that's for the imaging platform. And then from those data, we've also built several interest.

AI prototypes in terms of looking at features of oncology and how you would maybe streamline and support interpretation. And then we submitted those prototypes and that initial data as a package for a breakthrough designation in the summertime. We got that in, I think, in June. And so I would say we're getting all the pieces in place on the board so that we can really make a go at this. We're raising money now to do an initial launch with some KOL so that we can really hone in the details. We've really studied the space. We think we know we have an idea for how this will fit in the workflow and what the business model will be, but we really want to test all those assumptions, prove out the end of economics, and make sure this is going to work for

everybody and seamlessly integrate into the workflows. And so that's the point where we're at now. We've got an end goal would be like once you commercialize and let's fast forward two, three years into your commercial launch. This is a point of care system that kind of similar to the analysis you used. Most people are familiar with maybe their spouse is pregnant and may go to an ultrasound and the synographer does ultrasound. It's like that sort of model where you don't look like being a dermatology sonographer, if you will,

for a better description. That's exactly right. There's a lot of movement around point of care ultrasound and we're thinking of this as point of care pathology. And I think this, I believe this will be the first true digital pathology platform because we're not taking samples out. We're going directly from tissue to a digital representation

with no steps in between. And that's really in the same model of what in radiology. And step one is just decoupling the need to actually cut the tissue to see the information. And then phase two is layering on useful software tools to help streamline that interpretation. And all of this with the focus of basically helping dermatologists sort of see the patients, start this very large volume because they're really inundated. Yeah, that's cool. That's awesome. Ten years in the making, but you know, like something like you've got right.

It costs of some real pretty special stuff. That's cool. Yeah, it's in Spectra Health. Again, for everyone, everyone listening, we'll link to it the full write-up on MedSider. But yeah, really cool technology. Let's transition, maybe spend the next 20 or 30 days talking about some various kind of functional aspects of your journey. And the first one I want to start out with is really early stage development, right? You're mechanical engineer by background.

So you've got like a pretty solid understanding of how to make things, in essence, right? And I presume the bio platform now looks a lot different than what it looked like back in 2014. 15 and those early years. So this is probably a topic that we can discuss for the next 15, 20 minutes alone. But if you had to surface maybe one to two like really key learnings for maybe other PhDs, other physicians, other entrepreneurs that want to take a swing at something, what do you think are like some of the most important things that you've learned over that, over that period of time going from alpha to beta to the current bio platform?

Yeah. In some ways, that's the most fun interval. It's also usually the most ten years because you're, you have to. no money, you know, mis-versus, so I can think of a few things that are good. I should say, I speak very confidently and I'm opinionated and decisive about things. So when I speak about this, it doesn't necessarily mean that it has to be this way for you. I'm going to tell you what word for me. I love it.

I love it. I say roll up your sleeves and get dirty. I'm a hands-on person. I was good with my hands. I was good at designing things. I came from a more mechatronics background. So I had, I'd been going in like in a robotics, mechatronics direction. So it was good with general mechanisms with software even and actuators.

And through my PhD work, I branched out into imaging and got into image processing and now. And then AI became a thing. And so been continuously learning. But in those early days, you're probably the cheapest resource of your time, right? So if you prototype something and it doesn't work, which you won't. That's the other thing you should expect it to work. Then you just do it again. And if you're not paying us for people to do, that's just your time, you know.

So I say get, roll up your sleeves, get in the trenches and get. scrappy about the two or three key elements that are the biggest risk factors that people doubt about this space. And in our space, they were all technological. This is not actually a new need or idea. People have been like, wow, wouldn't it be nice if you could image. Skidnauton, and basically, it's obvious. The challenge is that's just not the way optics work. This is why we put things on glass, because glass is a good window. People are not. And it's hard to look through people to see what's beneath the surface. And you can't really fudge on that

because the doctors need to see what they need to see to know whether they're going to make a decision or not. And so getting the right system to actually deliver cellular scale resolution, that's one of the key elements, but the other key element is molecular composition. You need to know what stuff's made out of.

And this is why when we make histopathology, we do two stains. You've got a pink and a purple stain and counterstain because it highlights different structures and you can tell a lot of information from that. And those are the big things that had really been holding the field back. And we had made a lot of progress on that in my research, and my PhD for this different application where we were studying muscle disease.

And so my core focus was like, let me just show that you can actually implement this in some capacity on the bench, but that you can do it in skin and then just build it. At that time, it's two of us. And we're just like, me and the other person and physically in there doing it, it done. The other piece of advice I would give and that there's different schools of thought on this. I came out of the Stanford Biodesign world, which I think is like absolutely the recipe for success. Now where I'm a little bit contrarian is I, when I'm trying to come up with things, I will study everything that's been done before, both the successes and the failures.

And I will dig, learn how to read, review literature, look at what's been filed at the FDA. Now, this is a little contrarian because a lot of times they'll say, you want to keep yourself independent so you don't get, you know, hated by what others have done and lat down to that, but I feel like I'm disciplined enough and creative enough that it actually inspires me and informs me more.

And so I looked very deeply that like some of the best optical groups in the country have tried to crack this problem. They haven't. Where are they falling short? Dig into that and prove out those areas. Then we could prove out those areas

and then we were able to raise some money and say, no, we think we've got a way to really do this. Now that we've de-risk the technology, that focus is shifting much more towards, okay, how do you commercialize this successfully, right? And you fit into the workflows and the economics of the system. But that'd be some of my advice.

Yeah, it reminds me if I had Dr. Stephen Michelson on the program. He's the founder Ferrapulse, and now he's running now field medical. He mentioned some, like, Ferris, which is Boston Scientific Choir has done quite well with it over the past year or so. But he mentioned this, when he was first building that system, he was like, no one else was really building it with me. It was like, I was thinking, like, I was literally, building it with like,

self-competence. I'm trying to solve for what you said. It's like the most technical, the technical alimax, right, which he perceived to be the biggest technical quality of at the time.

Yeah, exactly. But yeah, your point about like, I'm right there with you. Like, looking at other people's failures, if you're creative enough, like that shouldn't be,

I'm concerned. In fact, I'm very much, I'm a big believer in the concept of stealing like an artist, like, the problem. Rather's have failed and,

and use that kind of as, creative fuel, if you will. And the failures are the most informed. You know, for sure. Yeah, Tim, I can't remember their last names. It's not my head, but Tim and Jeff with the Vino Stent, the co-founders of Vino Stead. They mentioned something similar, but within the context of clinical research. They basically

look at all of these failed trials, and they're like, one by one just pinpointed exactly what drove those failures. And then that's a really one informed kind of the clinical roadmap, but it's similar. I'm a big fan of that. So that's good stuff. Let's shift a little bit to your kind of transition. You just a little bit, your transition out of

academia, but like when you think about that, I'm sure it's probably hard to narrow it in on one or two things. I'm sure you've got friends that are still in academia, maybe, that have maybe some, an idea or maybe a way to repurpose technology. What do you think are like the biggest things to make that transition work successfully? Yeah, one of them I mentioned, which is that I think that it's about building something around a need,

which is a little bit of a transition you might have to make if you're trying to spin something out. because a lot of what we're doing in academia is it's needs centered, but it's usually on a scientific need, right? Or the very exciting things sometimes are in fringe, unexplored areas, which might be very meaningful in terms of informing the general world of science and medicine. But if you look at the market that would target, it might not be a commercially viable opportunity, right? So you need, probably the first thing you got to do is you've got to really step back and you need to be, you want to play to your strengths, but you've got to also be flexible.

And so I had developed these techniques for kind of a different application, but if I really want to get this out there and have a big impact, I need to find something that people can laugh at onto and use it right away. And it can't just be basic science R&D, right? And I think that my advice first would be if you think you got something and it's really unique, can you identify a real need that's worth targeting? And it might even mean that you're going to change that technology. Like you almost want to, that is where you do want to separate your mind a little bit. And I did that more where I went back to the drawing board and I said, let me find a of the place where there are genuine commercializable needs, but I can, the solution would play to my strengths, which is that I know how to make kind of unique optical systems, and then I'll apply what I have done, some of what I've done before to really target a solution for that. I think that's the key one. Now, for me, this may not be for everybody, but for us to raise money, like somebody had to take a plunge. And so I had co-founded this with, you know, my two other colleagues at Stanford who are still

professors there. It just did not seem like we would be able to raise money without the dedication of going in all in. And I took that plunge and I have seen a lot of people that want to do tech transfer out of the university, but that is very uncomfortable. And I understand that because I had a young family at the same time too. But I think if you want to do this, you have to at least be risk tolerant and sometimes risk driven. It's tricky and it's not going to be for everybody. And then that's nothing wrong with that.

I think my academic career would have been great too. And it would have been built on a lot of this. We would have been advancing this science for expanding the world of imaging and understanding in medicine. It's just it would have been, in my opinion, that stays a little bit siloed in the academic world. And I thought that this could have a practical impact in the social world, in the clinical world, if we can spit it out.

So just a different approach. But you just have to discern for yourself what you think. Makes sense. But then, but don't try to jam. They always say what the hammer are looking for. the nail, but I think most problems are screws. Right? And if you have a camera screw, like it doesn't work.

It wouldn't be right to book or, you know, more sophisticated approach. You got a twist. Oh, yeah, no doubt. I don't know. I don't be your co-founders, but it seems like you're pretty compelling guy to listen to. Hey there, it's Scott. And thanks for listening in so far. The rest of this conversation is only available via our private podcast for MedSider

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