He raised $300M to prevent heart attacks. Here's how he got his health tech startup off the ground. | Dr. Min, Founder of Cleerly

Cardiologist Jim Min watched too many 50-year-olds die with no heart-attack warning. He co-founded Cleerly to automate detailed coronary scans—no invasive procedures, no endless manual work. 

Yet healthcare’s glacial pace, payers, and federal approvals all stand in his way. 

Hear how he’s testing AI across thousands of patients, fighting for universal insurance coverage, and coping with near-burnouts. If you’re a founder navigating hyper-regulated markets, Jim’s journey is the blueprint.

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Why You Should Listen

1. Heart Disease Kills More Than All Cancers Combined – The staggering truth behind silent heart attacks (and why most diagnoses come too late).

2. Jim’s Big Bet on Early Detection – He’s using advanced AI to spot “dangerous plaque” long before a patient gets chest pain or drops dead.

3. A 10–15 Year Fight to Save Lives – The brutal reality of building a medtech startup in a system that moves slower than any other.

4. Surviving a 17-Day Runway – How his mission-focus (and supportive backers) pulled Jim’s startup back from the brink.

5. Why repeated failure drives game-changing breakthroughs

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Keywords

Heart Disease Detection, Medtech Startup, Coronary CT Angiogram, AI in Healthcare, Early Heart Attack Prevention, FDA Approval Process, CPT Code Reimbursement, Plaque Imaging, Cardiovascular Innovation, Clinical Trials

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(00:00:00) Embracing Failure & Surviving Dark Days

(00:01:56) From Cardiologist to Startup Founder

(00:03:07) What Most People Don’t Know About Heart Attacks

(00:06:39) Using AI & Imaging to Predict Heart Attacks

(00:09:19) Why Cleerly Needed to Exist

(00:16:34) The Reality of Healthtech

(00:20:41) How Cleerly Built its First Product—and Why it Wasn’t an MVP

(00:28:33) Raising $225M to Prove a Radical Idea

(00:33:57) Finding Product-Market Fit & the Fight Worth Having

Chapters

• 0:00 Embracing Failure & Surviving Dark Days
• 1:56 From Cardiologist to Startup Founder
• 3:07 What Most People Don’t Know About Heart Attacks
• 6:39 Using AI & Imaging to Predict Heart Attacks
• 9:19 Why Cleerly Needed to Exist
• 16:34 The Reality of Healthtech
• 20:41 How Cleerly Built its First Product—and Why it Wasn’t an MVP
• 28:33 Raising $225M to Prove a Radical Idea
• 33:57 Finding Product-Market Fit & the Fight Worth Having

Transcript

Dr. Min (00:00):
And I think like a lot of the people who are trying to start companies are overachievers and they've always succeeded in life. And I said, in business, you will fail. If you can get your mindset around that, that you will experience failure, you're going to experience some very dark days. Then all of a sudden they become easier to take. I mean, during the pandemic, right, like we were 17 days away from being out of operating capital. That was a dark month. Our donor, who is very special to me, like you know, I saw him on an interview one time and you know he described himself and his life he's like, look you know there's a jungle there and you can either be out on the outside of the jungle where it's pretty calm and nice, or you can be in the jungle and you're going to be fighting every day and trying not to get killed. And he's like, for whatever reason, I just like being in the jungle. To me, product market fit means, you know, when people recognize the utility of your products and they want them and they generally can't live without them, or don't want to live without them.

Previous Guests (00:58):
That's product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is Product Market Fit.

Pablo Srugo:
Listen, if you don't want the show to move up the rankings, you don't want it to get better guests, totally get it. You know what? Don't leave a review. Just don't do it. Why would you? But if you want to help out, if you want better and better guests, if you want to help the show move up the rankings, then take literally five seconds and hit five stars. Thank you.

Pablo Srugo (01:27):
Well, Jim, welcome to the show.

Dr. Min (01:29):
Pablo, thanks for having us.

Pablo Srugo (01:30):
So, I mean, we were chatting earlier and you're dropping a bunch of knowledge on heart attacks, which is admittedly not something, you know, not something fun in any way, but interesting in the sense that, I really knew nothing about it. And you're kind of an expert in that space. But maybe, you know, we'll talk a lot about that and kind of the problems that are happening in that space. But maybe give us like just a bit of background on yourself, because I think it'll help kind of set some context.

Dr. Min (01:56):
Sure, absolutely. Yeah, I'm a cardiologist by training. I did my postgraduate training at the University of Chicago and moved to New York City in 2005 and spent about 15 years working at New York Presbyterian Hospital and Cornell Medical College on the Upper East Side. There, like what I ended up emphasizing and focusing my time on was non-invasive imaging so that we could understand people's heart disease at scale and also prevention, trying to sort of do health care rather than sick care. So I was sort of the quintessential physician scientist. I, saw patients and then we ran a bunch of large-scale clinical trials that really informed the thesis of what we're trying to do here at Cleerly.

Pablo Srugo (02:39):
And, you know, at a high level, what do we know about heart attacks these days? Like when do they typically happen? What is preventable? What's not preventable? I unfortunately had a friend of mine whose dad just passed away recently from a heart attack. Super healthy, you know, ate well, exercised, late 50s, completely inexplicable. Do you see that somewhat commonly or is that really like an odd case? I mean, I don't know anything about this world, so really curious.

Dr. Min (03:07):
Yeah, I'll try to sum up some of the relevant statistics in an efficient way. But heart attacks are the number one cause of death. They're the number one cause of death in men and women. Cardiovascular disease deaths are the number one cause of death and a total 40% more deaths than all cancers combined. So just a massive thing. In the US, there'll be somebody who suffers a heart attack every 40 seconds, which is like why we all know somebody like your friend's dad right, and then the most common presentation for having heart disease like that is not presenting with chest pain or shortness of breath but it's simply having a catastrophic event dying of a heart attack or suffering a heart attack at home with no antecedent warning. And that's why it's a silent killer in the majority of people. And the most common diagnosis is suffering a catastrophic event. So we know how to treat somebody once we understand that they have heart disease. We have plenty of good treatments for it. Like 90% of heart attacks are preventable. It's not that we lack the treatments. It's that we're just not identifying people soon enough so that we can prevent these events from happening. And the last statistic I'll give you is the average age sudden coronary death, like fatal death due to heart attack in the U.S. is about 50.

Pablo Srugo (04:28):
Wow. I thought it was like mid-60s that was the average age for heart attacks.

Dr. Min (04:33):
I think a lot of the studies that we do are in patients who present with chest pain or shortness of breath, that symptomatic patient. It sounds bad to have chest pain, and it is. But in some ways, those people are sort of the lucky ones because they managed to progress their disease to a point where they actually feel it and become, you know, open to diagnosis. The ones who never feel it, those are the people who go out for a run and never come back or who go to sleep and never wake up. And that just happens thousands of times every day here in the United States. And we're just not finding those people early enough.

Pablo Srugo (05:06):
So the average age of those who actually kind of pass away because of a heart attack is around in the 50s?

Dr. Min (05:11):
In the 50s, yes.

Pablo Srugo (05:12):
Wow. Because we'll dig into obviously what your company does, but what are some of the underlying causes? I mean, maybe the key question is just like, how come we can't identify it most of the times?

Dr. Min (05:24):
Yeah, it's such a multifactorial disease, right? Like there's things that we consider traditional risk factors like cholesterol and blood pressure and diabetes. And there are things that we consider as what we call risk enhancing factors, kidney disease, lower extremity arterial disease, South Asian descent, HIV positivity, autoimmune diseases like lupus or rheumatoid arthritis, and the list just goes on and on and on. You can list thousands of them. There are probably hundreds of thousands of factors that contribute to heart disease that we just aren't aware of. Mental stress is a big one that I don't think we monitor quite well, but definitely exposes you to higher risks of having heart attacks and so on. So when something has too many factors that are contributing to the disease, I think the best way to do it is to find a single metric that integrates the lifetime exposure of that individual to all of those known and unknown risk factors. And that's what we tried to focus on, which was the plaque that is building up silently within the walls of the artery. That is the integrated summation of everything that that person experienced over the course of their lifetime.

Pablo Srugo (06:39):
And is that something you can see, like with imaging?

Dr. Min (06:41):
Historically, we could only see it through invasive tests. So you'd have to stick a wire or a catheter down somebody's heart artery. Obviously, not that many people are going to sign up for that kind of procedure. But in 2005, we saw the advent of a new technology called a coronary CT angiogram. It's performed on what we used to call the 64-slice CT. Now we have like 640-slice CT scanners and so on. And in truth, we didn't understand the vascular biology. We thought that all plaque buildup in the arteries was bad. What we did was we utilized it as a tool in the context of research trials, clinical trials, to better understand what we were seeing and how that affected somebody's outcome. And could we improve the natural history of that outcome by intervening with lifestyle modifications, medical therapies, even stent and bypass surgery? And what we learned was a lot of surprising things. We learned that not all plaque is bad. In fact, that some plaques are extremely dangerous for you and the strongest predictors of who will have a heart attack. And others are actually very stable and almost protected against having a heart attack in the future. And so what we said was, well, if some of the plaques are good and some of the plaques are bad, how do you turn the bad plaques into good plaques? And so we had done a serial study where we had patients that had undergone imaging twice, about three and a half years apart. And some of them were treated with certain medicines and some of them were not. And what we found was that the medicines, they didn't make plaque go away per se. They just transformed that plaque from the bad to the good plaque over time. And that was the mechanism of stabilization. So you can literally track your plaque and watch whether or not you're getting better or worse over time in a quantitative fashion and using a single metric that really integrates, again, the summation of all of those contributors to heart disease, most probably which we don't even understand. I think that that was the thesis. Once we figured that out, we tried to test that out into a clinical program where we thought we could really help people's health. We did that at Cornell. We ran that for many, many years. And we just saw such good outcomes that we said, you know, this has to be available to the world. And that was sort of the thesis of why we started Cleerly. Cleerly wasn't really trying to be an imaging company or an AI company. It was just really trying to standardize the approach to evaluation, education, treatment, and tracking of heart disease. And so we started that company about 2017, and now we're about seven and a half years in.

Pablo Srugo (09:19):
Maybe dive more into that, like what was it about what you were doing that couldn't be scaled without Cleerly, because from the outside looking at it, it's like you're doing this imaging, you're doing these studies, you're figuring out what medicines, what kind of procedures or outcomes or whatever drive the positive outcomes. What do you need a company for?

Dr. Min (09:37):
Yeah, it's a great question. So when we were doing that, we had the fortune of being supported by a very generous philanthropic donor. And what we did with some of that donation is that we hired 20 technologists, CT technologists who had gone to radiographic imaging school. And they were the ones who were tracing out all of the images so that we could quantify and characterize the amount and the type of plaque that there was. It was taking them eight, 10 hours to do a single patient's image. So it wasn't ever going to scale past the Cornell walls. And we didn't actually know when we started it. We had a pretty good hunch that it was going to work based on the clinical trials that we had run, but we didn't really know whether or not it was going to be effective once you applied it and implemented it in daily care. It did, it worked, but we just knew that there was no other hospitals that could afford the luxury of spending 10 hours analyzing a single patient's image. So we had to create automated solutions that could do that at scale. Fortunately, and parallel to some of the clinical trials that we did in 2013, I think, We had a computational biology arm and we shifted all of them to this new concept 12 years ago called machine learning. That turned out to be a good decision because as machine learning sort of evolved and we got to that 2017 timeframe when we started the company, that's when deep learning became a thing and was applied to image processing and extracting the kind of data that you need to get from the image in order to provide clinically actionable insights to doctors. And so we said, you know what, we understand sort of this computational approach to how to extract the data. And we understand the clinical approach that we learned from the clinical trials and our prevention program. So we said, well, why don't we put these two things together and really try to develop a standardized care management platform for, again, for evaluation, education, treatment, and tracking of heart disease.

Pablo Srugo (11:42):
Is there anything fundamentally different between looking at this imaging and looking at other images from whether it's MRI, CT scan, or X-Rays, or whatever? Because obviously there's AI being applied, you know, funny enough, like recently I had an X-Ray of my of hip and I obviously got the report. But then I also just gave it to like plain ChatGPT. And I'm like, what is this? And it was, you know, seemed pretty good. I mean, TBD, how accurate it was. Obviously, I can't actually test how accurate it was, but I was able to understand that it was a hip. And frankly, most of the things that it said were similar to what the report had said. So I was like, OK, that's pretty good. But what makes this kind of so different than that?

Dr. Min (12:19):
Yeah. I mean, so we apply our AI technologies onto typically acquired coronary CT scans of the heart. The CT scans of the heart require contrast, iodinated contrast that allows you to sort of brighten up the inside of the arteries so that you can see the walls of the arteries where the plaque builds up. For clarity, it's a it's a very simple test. Like at Cornell, I think we reserved 10 minutes or 15 minutes per, appointment. So it's not a long test. It's completely painless, completely non-invasive. And what a CAT scan or a CT scan is essentially just a fancy 3D X-Ray. Very safe. Like when we were doing it at Cornell, like I think our, averaged us was slightly over one millisievert of radiation. To put that into context, just walking around New York City or walking around Chicago, Illinois, you'll be exposed to about three millisieverts of radiation just from background radon exposure. So very, very low dose, very, very safe test, very, very quick, completely non-invasive. And so we understood that nobody was going to sign up for invasive procedures where they stick catheters into your heart. And things like that had to be non-invasive had to be safe, had to be rapid but also had to extract all of the information out of it. And to your point there's many different kinds of imaging. There's cat scans there's X-Rays, there's MRI's, there's ultrasounds in this particular case the only technology that's available today that allows you to look at that really bad plaque which is the very cholesterol, fatty-filled plaques that are building up silently in the walls of patients' arteries is the CT scan today.

Pablo Srugo (14:04):
But I mean, on the analysis side, like, why did it take kind of 8 to 10 hours of manual work to look at that? And what's hard about even today applying AI to it versus applying AI to, you know, my hip X-Ray? Or is it the same level of difficulty?

Dr. Min (14:17):
I think it's slightly more difficult. Like if you look at this CAT scanners, like the vendors who make them, like the GE's, Siemens, Philips, Canons of the world, like, they typically made their holy grail like scanners that can image the heart accurately. Why is that? It's because it's the most challenging. The heart arteries are very small and so you have to have something that has very high spatial resolution like the megapixels on your iPhone camera and then you also have to have something that has very high temporal resolution meaning the shutter speed on your camera has to be able to image a moving object and render it motion free, sort of like when somebody's running across the field and you try to take a picture with a camera with a slow shutter speed, they just look blurry. And so both of those things had to come into play in order for you to be able to image the heart very accurately, very non-invasively with these CAT scanners. And so I think that the acquisition of the image is very difficult compared to static things like your hip, like it never moves. It's just going to be there, right? And then the size of the plaques are just very small sometimes. And so you really need very accurate AI algorithms in order to effectively do this accurately. There's a number of studies that we've done as a company that have validated our technologies against every invasive catheter that you could think of to prove that what we're seeing is actually the disease that the interventional or the invasive tests also see. We've tested against what's called an angiogram, what's called an intravascular ultrasound, an optical corns, tomography catheter, and so on and so on. But we spent a lot of time doing research to get to the point of having a thesis for a company. And now we're spending an enormous amount of effort proving that the technologies are, in fact, best in class.

Pablo Srugo (16:12):
And then walk me through like the early days of Cleerly like, I'll admit most companies I work with, you know, we're talking lean startup, get something out there, get people using it, you know, get traction, like, obviously, in the world of health, and especially something like this, it's very different. Like, what is, you know, 2017, you decide to do this, because you want to kind of have this technology at scale, what is step one?

Dr. Min (16:34):
Yeah, step one is to make a product. So, you know, we spent a couple of years doing product development, got a couple of products through the FDA. The FDA, you know, as you point out, like healthcare is a highly regulated environment. And it's also an environment that is very slow to change, right? And the reason it's slow to change is because adoption of new technologies needs to be proven to actually help not harm patients. Otherwise, nobody's going to adopt them. So I think that, you know, for people who are going into health care, health tech, let's say, or digital health, these kinds of AI algorithms can be extremely useful. But the first hurdle you're going to get through is like you've got to make a product. The second hurdle that you're going to do is like you can't sell that product at that time. You've got to get it through the FDA and get it cleared or approved by the FDA. Once you get that product cleared by the FDA, you can sell it, but who's going to buy it and who's going to pay for it? Typically in healthcare, like you use your healthcare insurance, right? So now you have to engage with the payers. There's two sort of major bodies of payers. There's the public payers like Medicare and Medicaid. And then there's the private payers like Aetna, United, Humana, Cigna, Blue Cross Blue Shield. So then you have to do this process where you have to get a code that a CPT code or a current procedural technology code, that goes to the American Medical Association. Typically, what happens is they issue a transitional code or a temporary code. It's called a Category 3 code. And then you have to prove utilization. And then you can go back and get the permanent code, the Category 1 code. Once you get the code, now you've got to develop a corpus of evidence that shows that it's accurate, but that it also prognosticates outcomes, right? That what you see on the test actually can identify people who are healthy versus sick. And then what you have to do is demonstrate that it actually changes your management. What's the good of a test that doesn't do anything to change management? And once you have that management change, then you have to prove that it actually influences the patient's life in a good way and can improve the patient health outcomes. All the while on a foundation that demonstrates that you should really reduce the cost to the health care system, not increase the cost. And so the cost effectiveness or the cost efficiency is something that you have to prove. Once you get all of that corpus of data, now you can go to the payers and say, well, look, I've got a useful test that's accurate. It's prognostic. It changes management, improves patients' lives, and it saves money. But there's 1,100 payers in the country. So then you've got to go talk to them each one by one. And once you do that, hopefully you can get a coverage policy. But a coverage policy doesn't necessarily equate to reimbursement. You can be covered but not reimbursed. Conversely, you can be reimbursed but not covered. But you're trying to get both the coverage and the reimbursement. And so then you go through this effort. And this is probably I've just described the 10 to 15 year effort here to get to that point. So the product market fit of virality of just building MVP shipping product and, you know, there's an exponential growth. In healthcare, it's harder to do it than Ad-tech or something like that.

Pablo Srugo (19:46):
It's really hard to save lives.

Dr. Min (19:48):
Hard to save lives. Even after you're done with all of that, now you got to convince the clinical community that they should be using it, right? So then you've got to get into the guidelines, the professional societal guidelines for recommendations. You've got to have enough data out there with large-scale clinical trials to prove, you know what this passes the sniff test you studied 15,000 people for 5 years this seems like a real test. And so it's just and then they always say in medicine that things take about 20 years to change medicine. And if you think about it that is about the time that it takes for one generation to retire and a new generation to come about. So, you know, once people leave their fellowship, get into a certain practice, they tend to practice that way, right? Because that's the way that it's worked for them in the past. And so the introduction of new technologies to healthcare is just, there's just a lot of hurdles to get through.

Pablo Srugo (20:41):
So let's talk in more detail then about kind of each of those, especially the early steps. So like you said, build the product. So what do you define as kind of that V1 product that you set out to build?

Dr. Min (20:51):
Yeah, I mean, in our case, the V1, like we had this grand master plan to try to make the world's most comprehensive coronary artery disease solution. I think we've done that, but we probably, like in hindsight, like I don't know if I would have done it the same way. Probably I would have, but we could have built a more minimum product than we did. We just felt like that all of the stuff that was important to doctors and to patients should be included in the platform. And so we spent time to do that. We had an amazing engineering group. And we had amazing product people that just really thought through the problem. We architected it out from the get-go, and we were extremely diligent in that architecting process. I think that was important, the whole planning process. It's easy when you're excited to just go start to build something. And then you see that you forget a lot of stuff in hindsight like would I have built something a little bit different? I don't know. Like I mean you we could have built something faster I don't think it would have been better and I think that what changes medicine is better. Like not better for patients not faster for patient. So, I'm glad that we spent the time to do it. Did a lot of planning, probably six months of planning before we even started to write code. And then- 

Pablo Srugo (22:10):
But maybe just maybe stupid question, like in my head, like beyond just the AI that analyzes images and tells you what kind of plaque is there? What else is in that product?

Dr. Min (22:20):
Ah, yeah, it's a good question. So, I mean, we have multiple softwares that are embedded into a single user experience. The most important thing that we could have done is to get all of that actionable data out of the images, right? So, the amount of disease that you have, the extent, the severity, the type of disease was probably the most important thing. The problem with that is like, if I hand that over to you, it's like me speaking French, right? Or like Japanese to you. It's like a totally different language. It's the language of imaging rather than the language of you know, common, you know, colloquial speak. And so what I realized when, you know, because we practiced like for so long at New York Presbyterian and Cornell was that once we had that imaging data and we would hand it over to clinicians who weren't familiar with imaging. The most important data fell through the cracks because they weren't imagers. And we were good at translating it for them. We would talk about all these positive outward remodelling and constrictive nature of this plaque and this plaque is low density and low attenuation. And everybody's like, I don't know what this means and it doesn't mean anything to me. And so what we did was we learned over time to write up our reports as physicians in a way that people could understand it. And so what we wanted to do with the platform was also do that translation step automatically. And so what we do is we take the AI, it analyzes the images, it does very comprehensive all-in-one analysis of coronary artery disease. And then it translates it to another platform. And so that platform is really built for all the stakeholders across the care continuum. That means the imager. That also means the general cardiologist, the preventive cardiologist, the interventional cardiologist, the radiologist, the researcher, and the primary care physician, and most importantly, the patient, like the patient's got to know what's going on. And so we built this platform that really, as long as you can read, you understand exactly what's going on, what the things that we had understood from the clinical trials to be important and built on infographics built on, completely interactive 360-degree displays of imaging that are on it.

Pablo Srugo (24:33):
And are there typically, like, suggestions on, as a patient, here's what you should do to kind of, let's say you're in a bad situation?

Dr. Min (24:39):
We don't do that because, and the reason we don't do that, we thought about it. Like, we're regulated by the FDA as a clinical decision support tool. So, we output the important information. It's up to the doctors to do what they do. That is what decision support is. But more importantly, we would have done that anyway, because we are not here to disinter-mediate the relationship between the patient and the doctor. We want to enhance that relationship. You know, get in the middle of it. And so what we do is we provide all of the actionable data and then the doctors can act upon it as the doctors feel is correct.

Pablo Srugo (25:14):
And I guess that makes sense. Like, again, if I think about my X-Ray that I got, like the report is the report and then the doctor maybe tells me you could go see a physio or like do this or do that. I guess it's similar.

Dr. Min (25:22):
Very similar.

Pablo Srugo (25:23):
And is the idea that, like, everybody would get one of these scans, like, after a certain age every year? Because, like, what percentage of these cases, heart attacks, are completely asymptomatic before where people wouldn't think to get any sort of imaging done?

Dr. Min (25:36):
Well over 50%.

Pablo Srugo (25:36):
Okay. So the idea would be that everybody just does it kind of every year or something like that?

Dr. Min (25:41):
That's our North Star. I mean, like, we feel like we understand the vascular biology. We feel that we have an extremely safe non-invasive tool that has been evaluated with hundreds and hundreds of thousands, maybe millions of patient life years of follow up. And so, you know, we're doing a large-scale randomized control trial right now. It's about 7,500 patients. We're a little over 2000 patients enrolled. And the purpose of this trial is to test the hypothesis that image guided care, clearly guided care is superior to conventional standard of care in completely asymptomatic people. And so we believe that once you see the image, once you see the disease, you get those people with disease on the right treatment, you will save millions and millions of lives. The reason that we're investing in this trial, which is a long, expensive trial-

Pablo Srugo (26:33)
Yeah like how does that, maybe tell me more? Like how does that trial work? 7500 people all asymptomatic and you image some and you don't image others and then you do things about it? Is that like just high level?

Dr. Min (26:42)
And then people act upon uh the results doctors do and then there'll be a follow-up and we'll see which one is better. You know all of the data that has been published to date would suggest that imaging-guided or imaging-based evaluation on early detection of disease works. I'll give you some examples. Screening mammography, screening colonoscopy, screening pap smears, screening lung CTs, all of those things to combat breast cancer, colon cancer, endometrial cancer, lung cancer, share the commonality that they all use some form of imaging. In order to do early detection of disease at a point in time where it's treatable easily rather than at late disease when people are suffering catastrophic events. And so we believe that the same concept holds true here. Coronary heart disease is a silent disease in the majority. We will never get to them if we as doctors just wait in the clinic because they die at home. And so we need to go upstream and screen the world to find those people before their events occur. In order to do that, we've got to prove it. Right. And we've got to prove it within the context of a really well-performed, you know, very generalizable randomized control trial, which is what we're doing.

Pablo Srugo (27:55):
Seems like I mean, to me, as somebody who has no idea about any of this world seems like a no brainer, but I'm sure it's more complicated than that. Walk me through just on the fundraising side, because that's another thing that. You know, if something's going to take so long, you know, the fundraising becomes ever more important because there's no way you could just like be profitable. Like you just don't have those choices that other companies might have. What did you raise initially? I assume initially it was a lot about, you know, your background and credibility and that's what the round was based on. But what did that round look like? And then the next few rounds, like how do you structure the milestones so they get you the next round so you can do the next thing and so on and so forth?

Dr. Min (28:33):
It's a good question. When we did the Series A round, that was led by high net worth individuals and friends and family. And that was really just for product development.

Pablo Srugo (28:43):
That was your first money?

Dr. Min (28:44):
That was the first money.

Pablo Srugo (28:46):
And how much was that?

Dr. Min (28:47):
It was in the range of, I think it was $8.5 million. And so we did that when COVID hit. We did a small extension round just to extend the runway for about a year or so and then emerged with a couple of FDA cleared products. At that point in time, really the emphasis was on the symptomatic patient because that is what insurance providers allow you to perform imaging on, right? Patients who present with chest pain or shortness of breath. So we raised the series B round from some traditional sort of early stage Med Tech venture. And the thesis was like, let's go get those CPT codes. Let's go get those coverage policies. Let's go try to really tackle this addressable market of patients presenting with symptoms suggestive of heart disease. That turns out not to be a small market. It's about somewhere between 15 and 20 million people in the US every year who present like that. And so, so we did that.

Pablo Srugo (29:45):
And at that point, does that mean you're generating revenue from that?

Dr. Min (29:48):
We were generating revenue. Yeah.

Pablo Srugo (29:49):
Okay.

Dr. Min (29:50):
Like we didn't have insurance reimbursement. So we had to get revenue the way that we could. And so we started targeting patients and sort of longevity and. You know, in concierge and things like that. And, you know, they're very bright, these patients. And they say, like, look, you know, if I can get an early look at my heart, I'll do that. And so that's what the doctors were ordering our test on.

Pablo Srugo (30:12):
And that means they pay out of pocket since you're not covered? Many of them were paying out of pocket.

Pablo Srugo (30:17):
Okay. 

Dr. Min (30:18)
Yeah, but we really wanted to tackle it so that I mean, I didn't make a company so that people would have to pay cash. I wanted it to be standard of care and covered by insurance. So, we really focused a lot of our efforts from say 21 to 24 on market access, meaning the CPT codes and the insurance coverage and reimbursement policies. So that was great. But our North Star, as I told you, was always like, yeah, we believe that it's time like similar to a mammogram let's screen. It's a silent killer and people will never see them in the hospitals because they'll die at home. And we really need this screening thing otherwise heart disease will always remain the number one killer. Just because we don't see them as doctors, right. They die before they come to us and so that's when we had this idea that we would do this large trial and try to prove to the policy regulators that, you know what, like this should be recommended for people because it's, good medicine. We'll save millions of lives, save hundreds and hundreds of billions of dollars over time. And that's when we embarked on the trial in order to do the trial, that was very expensive to do that trial. So we were very fortunate to be introduced to some crossover investors, large mutual fund investors who, you know, they have very large capital to deploy and they, they believed and supported the concept that yes, like this is an innovative tool that leverages AI, leverages 20 years of clinical trial data, leverages a clinical experience that was like extremely successful in reducing heart attacks. And why don't we try to support that so that we can get a policy recommendation for universal screening. And that was our Series C round. So the Series C round came together with, Fidelity and T. Rowe Price.

Pablo Srugo (32:05):
How much was that?

Dr. Min (32:07):
That was about $225 million.

Pablo Srugo (32:09):
How much does it cost to get a big, you mentioned this trial, 7,500 patients. What's the cost of that more or less?

Dr. Min (32:15):
Well, we have a lot of in-kind support. Kroger Pharmacy is a partner that distributes the drug. Several pharmaceutical companies have donated in-kind drug, all in like if you include the in-kind support, like it's well over $200 million to do this.

Pablo Srugo (32:31):
Oh, wow.

Dr. Min (32:32):
It's a very expensive trial.

Pablo Srugo (32:34):
And the outcome of that, if it's positive, is what exactly?

Dr. Min (32:37):
What we're hopeful for is that it will result in a positive recommendation by the governing bodies to say we should be covered and reimbursed for universal screening of that population of people. Our eligibility criteria for the trial comprises a little over 100 million people in the United States. So it's a very large addressable market. And we just want to get them access to the kinds of care that they deserve.

Pablo Srugo (33:02):
And then, like you said, so let's say that happens. Now you could theoretically be reimbursed for those 100 million. You've got to go and get all of the kind of healthcare practitioners in there to understand that this exists and, you know, suggest it to like their patients.

Dr. Min (33:16):
Yes. So then there's an educational hurdle that we have to go through. And then there's a practice change that we have a hurdle that we're going to have to influence. And but, you know, with 8000 people and, you know, in three and a half year follow-up or four year follow-up. Like if the trial is positive, I'm hopeful it will prove to people that this is the right way to be doing things.

Pablo Srugo (33:40):
Well, yeah, I sure, I sure hope so. Let me stop it there. Like I, I, you know, typically we'll ask about kind of, maybe I can ask a form of this, but like, you know, cause this is the product market fit show, right? So typically I ask like, when did you feel like you had true product market fit?

Dr. Min (33:57):
I can address that, actually, Pablo, because the way that we've structured our company is that we've got the one arm that's doing this large trial towards our North Star. That, in some ways, could be construed like what a biotech company does, right? A biotech company is a pharmaceutical company that's trying to test a drug. They need to do a large clinical trial to get FDA and to prove to everybody that the drug works. And that's more an R&D kind of thing. And then we've got another side of our company that's really targeting that symptomatic patient population. We believe, and the evidence supports today, that we have the best in class coronary artery disease tool for symptomatic patients who are presenting with chest pain and shortness of breath. So what we want to do is really try to tackle that market from a commercial standpoint. And so, you know, the product market fit that you talk about, you know, I think it's, funny. You ask 10 people, what does that mean? And you'll get 10 different answers of what product market fit is. To me, product market fit means, you know, when people recognize the utility of your products and they want them and they generally can't live without them or don't want to live without them. And, you know, in health care, as we talked about, it's like highly regulated and there's a lot of different components, right, like CPT codes and coverage policies, reimbursement, so on. But last year was the first year we really started to sell in earnest in that typical medical environment, right, where. It's a fee for service environment where, you know, there's an insurance code. You perform a service. Somebody gives you a fee. They typically give it to the doctor in the hospital. And that's where we started to make a lot of inroads. And so, you know, you can feel it as a founder or feel it as an employee. Like, you know, the first time you go out, you're pushing a rock up a hill and then you start to feel like, okay, maybe the rock's a little bit lighter. And then at some point you feel like, hey, we went from a push to a pull where suddenly some customers are calling you and saying, hey, can you come by? And we're interested in learning more about the product and you know, that's just an evolutionary thing. How fast that curve goes from, you know, linear to hockey stick, that's different for every company. But I feel like what we're feeling is that, you know, a warm reception, you know, in the marketplace from the clients, we feel like we've got a tool that really helps human beings and patients. And yeah, it's just really literally in the last, I would say, 15 months or so that we felt that, you know, that warmth has been getting hotter and hotter which is good.

Pablo Srugo (36:31)
Can you give me a sense of scale or traction on that side of the business like how many patients have been screened on the symptomatic covered side or revenue or whatever you can share.

Dr. Min (36:43):
Yeah, I mean, we've done a blended, compounded annual growth of about a little over 100% over the last five years. And so we've been doubling, more than doubling every year, which is great. I think I forget exactly how many patients we've done in total, but it's probably got to be close to 100,000 at this point in time. So somewhere in that range or so. So looking like things are looking bright. I say that carefully because I think that in healthcare in particular, you should maintain some humility. Like right now, what we want to do is never be wrong. We always want to provide great things for patients. We always want to make sure that our tools help patients. And that is a constant iterative evolutionary process. And one that I think requires you to just stay a little humble and say like, you know what, like we're going to make better products and we're going to continue to add on to the platform. Our plan over the next year and a half is to introduce a couple more products that I think will be welcomed by the clinical community and the doctors and the patients. So, yeah, it's a process. Right. Like, I mean, I don't know, somebody I once said to one of our investors, like, look, as long as we get to that point, like, I think we're going to be good. And they said, no, no, no, Jim, that's not how it works. This was three years ago. And I said, what do you mean? That's not how it works. They're like, oh, it's going to break. Your company is going to break and then you're going to have to put it back together. And then for a while, things seem like they're stable and then it'll break again. And then you're going to have to put it together. But they're like, but companies are always breaking, Jim. Like you can look at the top 10 Fortune 10 companies. They're breaking and somebody's putting them back together again. So, yeah. So it's just it's like if, you know, I one of our our donor who is very special to me, like, you know, he was I saw him on an interview one time and, you know, he described himself and his life. He's like, look. You know, there's a jungle there and you can either be out on the outside of the jungle where it's pretty calm and nice, or you can be in the jungle and you're going to be fighting every day and trying not to get killed. And he's like, for whatever reason, I just like being in the jungle. And I, you know, I can share that outlook because, you know, it's sometimes it's frustrating. Sometimes it's aggravating. Sometimes it's stressful. But I mean, on a daily basis, I can tell you that we have an extremely mission driven company. And all of us wake up in the morning and go to sleep at night looking in the mirror saying we are trying to do good for mankind. I mean, and that in and of itself is motivating enough to wake up.

Pablo Srugo (39:13):
How many people are there now at the company?

Dr. Min (39:16):
A little over 200.

Pablo Srugo (39:17):
And, you know, let me ask you this. Did you did you think at any point, especially given the nature of this of Cleerly like, was there a point where you thought it would break? Like where you thought just not you're just not going to make it to the next step for whatever reason, it's going to fail.

Dr Min (39:32):
Oh, there were some dark days. That's for certain. Yeah. And there was more than one dark day.

Pablo Srugo (39:37):
Tell me about one.

Dr. Min (39:39):
I mean, during the pandemic, right, like we were 17 days away from being out of operating capital. That was a dark month, like where, you'll just tell people just be patient for 30 days. No, that's not what happens. Like, legally, you cannot do that. You have to put them on furlough or fire them and do a riff. And if you do a riff, you can't get them back. And who's going to go on furlough with a startup that is, you know, can't raise money. It just, those were some dark days, you know, and then there are times where, you know, early on, like when we started doing the product, like about eight months in, we're like, these machine learning algorithms don't work. Like what's going on? And so like, that was a very stressful few months. And then we worked really hard at it. And then about three, three and a half months later, suddenly they started working really, really well. And so, you know, there's just like, and it's all different kinds of things, raising money. It's the product. It's the, you know, working with the customers. It's like trying to get through the CPT codes. Like at any given point, I can enumerate for you probably a hundred pretty, pretty bad days. Like, but you know, you try to bounce back and that's like part of being in the jungle.

Pablo Srugo (40:50):
How did you ultimately get through that 17 day period? What did you do?

Dr. Min (40:53):
Very supportive friends and family, like extremely supportive.

Pablo Srugo (40:56):
And then, so my last question is what's like, I'm sure you speak to it with a lot of founders. Like what's some common advice that you find yourself, giving often, like what's one piece of advice you would give somebody listening.

Dr. Min (41:09):
And I think like a lot of the people who are trying to start companies are overachievers and they've always succeeded in life. And I said in business, you will fail. Like, and you know, there's a tennis player that has a tattoo. I think it's a Samuel Johnson quote. It says, you know, ever tried, ever failed. No worries. Fail again. Fail better. And if you cannot tolerate failure like it, you shouldn't start a company because you're going to fail and you're going to fail over and over and over again. And the goal is to fail better and fail faster. I think that's the biggest thing. If you can get your mindset around that, that you will experience failure, you're going to experience some very dark days. Then all of a sudden they become easier to take. If you don't expect that and you think that you will never fail. You'll never have a dark day. Then those things are sort of more influential bad days to people. So I think embrace the failure. We have a chief commercial officer who always says embrace the suck, right? Like, you know, a lot of it sucks. Yeah, a lot of it sucks. So just, you know, but as long as you've got your eye on a North Star and you believe in what you're doing, I mean, the one thing I can say is I am surrounded by 200 people who are mission driven. And that motivates me like you cannot believe. And then every time I hear about somebody like your friend's father, our team is even more motivated to try to get out there help educate and provide the solutions and tools to get people early diagnosis. So yeah, I think mission driven is another thing.

Pablo Srugo (42:44)
Well, Jim thank you for finding the good and important fight and thank you for taking the time to come on the show it's been great. 

Dr. Min (42:50)
Great, thanks so much for having me Pablo.

Pablo Srugo (42:51):
You remember like the first person who told you about Bitcoin? The first person who told you about Uber? You want to be that person because being first is cool. So be a cool person and tell your founder friends. Send it to them on WhatsApp. Put it in a WhatsApp group. Put it on a Slack channel. Let people know about the show. Let people know about this episode. Don't let somebody else beat you to the punch and share it with your founder friends first. Remember what Ricky Bobby said. If you ain't first, you're last.