All right. Thanks for being here, everyone. Great to see you. Glad to have the HeartFlow team with us today. Maybe quickly before I jump in, you've got to grab your research disclosures from our website at morgansanly.com slash research disclosures. If you have any questions, please reach out to your Morgan Stanley sales representative. um so uh thanks for being here really excited to have heart flow with us um and dig into another healthcare uh ai story maybe uh john just to start um if you could just sort of hit where you guys sit in the market what your application is what the need is um and sort of what your value prop
is yeah sure so thanks uh thanks for having me pleasure to be here um so we are uh we're a technology company. We use AI. We deploy AI to better diagnose coronary artery disease. So at our core, that's what we do. I think there's a tech conference, but you're probably all aware of heart disease in and of itself is the world's number one killer. So we think we're deploying our technology to a very serious problem. It kills more people than all forms of cancer combined. Every 40 seconds, somebody in this country is having a heart attack. Half of all those heart attacks are a total surprise, meaning they've been through, the patient's been through the healthcare system, and it hasn't appropriately been diagnosed. So that's really the problem that we're trying to solve, and we're at the very early innings, but we believe we can create a new standard of care using our technology to do that. And everything we do is backed with clinical data. Our clinical data proves our accuracy. It proves our outcomes. We're very proud of that. What's unique in our AI and the insights that we deliver to our physicians is the use of our technology is reimbursed. Well, first off, it's all cleared by the FDA, but it's reimbursed, so it's covered by Medicare. It's covered by commercial payers. So our physician customers and their hospitals, they make a margin by using our technology. And similarly, we have separate revenue streams for those reimbursed technologies as well. So we went public in August of just this last August and super excited for what the future holds with our technology. Maybe we could spend a
I can sort of double-clicking on the non-invasive testing market for cardiology. What does that look like? You know, maybe spend a second on CCTA, which is the underlying imaging modality and whatnot.
And I should mention our technology sits on top of a coronary CT image. Okay, so that's what we deploy our AI to.
But you don't own that equipment?
We don't own that. We deploy that into our cloud. and we put our technology on top of that. Now, relative to the, as you referred to it, the non-invasive testing market, if you take a step back, our current patient population that we're treating with our technology are patients with symptoms, okay? So that's you're mowing the lawn on the weekend, you're running to catch a flight, you know, you're chasing your grandkids, what have you. You have some type of a symptom. That could be chest pain, shortness of breath, dizziness, fatigue. Ultimately, that patient finds their way, in most cases, to a cardiologist, and that cardiologist's job is not to run them straight into the hospital and do an invasive procedure. It's to diagnose those symptoms non-invasively. So that's the market that we're sort of playing in currently. In total, there's 9.5 million non-invasive tests every year in this country. If you monetize that against our technology, that's about a $5 billion TAM, okay? Now, our penetration within that is just, you know, like I mentioned, the really early innings were about a 2% penetration against that total non-invasive testing market. But, again, we believe we're on the right side of history here, and we can create a new standard of care. You asked about the coronary CTA. So the coronary CTA, again, is what we – that's the front-line test that patients, in some cases, but in an increasingly amount of patients, are getting ordered for this non-invasive test. That's about 10% penetrated, and then we're a fraction of that.
Maybe just spend a second, actually, what are the other non-invasive types of tests?
Yeah, so these are stress tests, treadmill tests. Sometimes you call them nuclear tests. And the vast majority of the market still relies on those. And we really believe our technology is better and can improve on the inaccuracies. Just a note on those, and this is well understood in the clinical data, 55% of the time they diagnose with a false positive, meaning you'll go and you'll get a nuclear test and be sent into the cath lab when you don't need to be there for an intervention. More concerning, 30% of the time, they miss it altogether. And that's when these patients go home and unfortunately have bad events at home. Again, we have clinical data that proves we're much more accurate than that, and we can avoid those false positives and those false negatives.
So patient ends up with a cardiologist, gets a CCTA, image goes in the cloud to heart flow. What's the platform and the products and solutions that come off of that then at that point?
Yeah, good. So first of all, we have a technology platform. We're not a singular test. And our platform, and we're committed to this, but our platform continues to expand year on year. Right now, we have four components to it. The first sits at the front end of the workflow, and I should say wherever that patient is in their journey, whether or not it's detecting it, diagnosing it, managing it, or treating it, our goal is we bring clinically validated, reimbursed insights to our clinicians so they can take better care of their patients. The first part of our platform, we call it the roadmap analysis. This is a workflow tool. we have clinical data that substantiates, allows CT readers, so these are the physicians that are reading that CT image, to read it faster with less variability, okay? And we provide that free of charge for every CT that's sent to HeartFlow, okay? And it's a really nice component of the model, and I can speak more as to sort of how it enables some other things in a moment. Next, sort of in between the bookends here, we have two reimbursed technologies. Each serve a separate insight for clinicians, and each are reimbursed separately, so they're sort of separate revenue streams for us. The first is our plaque analysis. Plaque analysis measures plaque, whether it's calcified, non-calcified, or low attenuation plaque, down to the cubic millimeter. And so that's orders of magnitude more precise than any physician could do with the human eye. And, again, we back this with clinical data so we know it's accurate against the invasive gold standard. Our next reimbursed piece of the platform is our FFRCT analysis. What FFRCT does is it models the blood flow across any disease that's found and tells the physician whether or not the blood flow has been impeded to the point where that lesion or that disease spot of the coronary tree needs to be intervened on. So separate insight, then plaque, and again, separate reimbursement for the physician. And then lastly, which we're launching here shortly this year, we have what's called a navigator tool, a PCI navigator tool. So again, if you follow that patient all the way through the continuum, and they end up needing to be in the cath lab with a disease that needs to be treated, we now have a tool where the interventional cardiologist can plan accordingly to take care of that patient. So that's the platform as it stands now. But, again, we fully intend to continue to add components to it.
So maybe a couple other questions on the platform. One of the things I don't think we've talked about yet is one of the unique, I think, advantages, although maybe it needs a little explanation, is you've got a human in the loop still on your side. So not just the physician treating the patient, but on your side you've got a human in the loop. Maybe just talk about how that works, John, why that is or isn't necessary. Could that human go down to zero over time? Can it not, et cetera?
So first thing I'll say, again, we're in health care. This is regulated. This is FDA-cleared technology. This is technology that needs to operate within a regulated environment. As part of our FDA clearance, we are required to have a human in the loop. That human serves a really important component. They ensure quality of the algorithm. So the first step that occurs when we ingest these CTA images from hospitals and clinics, It comes to our cloud, and the first thing the algorithms do is they create a precise 3D model of that actual patient's. If that model is perfect, then all of our algorithms can run autonomously off of it. But because CT images come, and sometimes they have artifacts in them, sometimes they might be blurry based on a patient's heart rate while they're getting the scan, when they show up, they're not always pristine. That's where our human in the loop, we call them a quality control analyst, make a couple adjustments all the way. And the analogy I sometimes use is if you have a Waymo taxi driving around San Francisco, if you give it a perfect map of the city, they won't run the stop sign, they won't drive up, or it won't drive up on the sidewalk, what have you. Similar here, what these humans in the loops is they're making that city map perfect and pristine. From there, the algorithms take over, and that's how our technologies are sort of brought to fruition. Now, if we were having this conversation, you asked kind of how long does it take to do. If we were having this conversation 15 years ago when the company was founded, that quality control analyst probably spent 20 hours doing those connections. Last year, at the end of last year, they spent about 20 minutes. okay so every every that fundamentally been a technological improvement exactly that's 100% what it's been so every unit of time that's taken out is a function of our algorithm getting smarter over time as we feed it more data so we've taken a lot of time out uh over the years and you can look at our margin expansion over the same period of time and see that occurring and i've got a super high confidence that that expansion is going to continue uh in the future to to get to your last question, will there always, you know, can we always take a human out altogether? You know, we never say never. I think where I've got really good line of sight on is we're going to take that time down and down and down. If you were to take the algorithm or the human out altogether, that's a new regulatory filing. And we'd have to evaluate whether or not that's a strong business case,
you know, when it's appropriate to. So you maybe just spend a second on the algorithm. You've talked about, you know, you've got 150 million plus annotated images. You've talked about the algorithm improving over time. You know, there's a lot of talk at the conference and the investor community right now on, oh, you know, how proprietary or not is the data, how proprietary or not is an algorithm or piece of software. Maybe just talk us a little bit about the training, building of the algorithm, the testing that's went into it, the proprietary nature or not of the data you have etc yeah so good question so first thing
I'll say is you know right now we've got give or take call it 160 million annotated CT images okay so these are clean CT images that have been for lack of a better word kind of scrubbed by our our our analysts over the course of time this is a data set that's incredibly diverse we've been growing it for 15 years so as different anatomies you know come through the cloud as different types of CT capital comes through we've got a very diverse data set there this data set to the best of our knowledge is the largest that exists and it is proprietary to us and like I said we've grown it over time and as we speak it's growing okay every time we ingest a a CT we grow it so that's one really important kind of component of the business model and we use that data to create new algorithms to expand gross margins we use that same data to create new technology that we launch back to our existing customers through those same data pipe and connections so that's one really important piece that I think think serves as a compelling moat, so to speak, as we move forward. The other is around, as I mentioned, this is a regulated space. You need FDA clearance. You need to know how to approach the FDA in order to get that clearance. You need to know how to produce products at scale and deliver them back to physician customers underneath a quality control system that's auditable by the FDA you need complaint handling you need design controls You know no different if you were an implantable device, so that's a skill set That we've built and I think we're we're pretty good at over time. There's another kind of data That's I would argue Equally as important as as the data we use to train the algorithm and that's our clinical data Okay at the end of the day our customers are physicians. Okay, physicians physicians, you know, by and large, make decisions on how is this going to help me treat my patient better. The way you impact practice patterns and change behavior, so remember, we're trying to shift behavior from this traditional standard of care to this new one, is through, and the company has invested over time, you know, we were founded in 2010, and credit to the team in 2010 for making the commitment to do this. We have over 600 peer-reviewed clinical publications in the market right now. And that's taken us 15 years to accumulate. That's orders of magnitude more than anybody else has got. And we're continuing to invest in that. And then I think the last piece is we work really closely with customers. And again, we've learned this over the years on how do you take this technology and integrate it into a health systems ecosystem? So these health systems, there's a lot of different stakeholders. You could be an interventional cardiologist. You could be a CCTA reader. You could be a general cardiologist. You could be an internist or a primary care physician. Okay. And after we kind of go live in an account, we work to integrate across that entire ecosystem. Now that can be challenging in a lot of respects and it's taken us a long time on how to do it well. But where we are now, we really think it's it's another kind of compelling piece of our moat, because once you're in, the switching costs are pretty high, and we see a lot of really kind of sticky behavior. And then the last piece, I should say, everything we do is, you know, backed by really strong IP, and we've got a good IP portfolio
as well. You mentioned the sort of bi-directional data pipes. I think that's actually an exceedingly rare asset or capability across healthcare. You know, I talked to Tempest earlier today. They've got that, but if you go talk to, you know, a very large percentage of our clients, they don't really have that in any form or fashion. Maybe they're passing a PDF to their client or something, but there's not a true data relationship. Can you talk a little bit about what that looks like for you, what it's been like to build that, where you're at in building those connections, and where you
need to go sort of in the future? Yep, yep. Okay, so first thing, just for kind of context here, At the start of this year in the U.S., we were connected to about 1,500 accounts, roughly, okay? And those are hospitals or those are clinics, okay? Anyone that has a CTA, you know, within the building. Once we're into those accounts, that's where this bidirectional data pipe comes in. We're in about 1,500. That number, again, is growing just about every day as we're adding more. The total hunting ground is around 3,200 accounts, and that 3,200 is growing by about 300 a year. And I just say that to say there's a lot more pipes for us to kind of connect, and if there's 300 new ones entering the category every year, that's going to keep us plenty busy. And this is just U.S. Yeah, this is just U.S. So it's by virtue of that that we set up these data pipes. Now, once that occurs, the minute one of these patients that I mentioned, and the patient's coming in for a non-invasive test to diagnose coronary artery disease, the minute that patient has a CCTA, it comes to our cloud automatically. Once it's in our cloud, we digest the data, we create the analysis, and we bring that analysis back. So by the time the physician is ready to make a decision or make a diagnosis, our technology is there waiting for them. Okay. The benefits that the customers, you know, yield or glean from this model is they get instant access to our technology the minute they need it. They get access to our roadmap technology for every one of their CCTAs. That's irrespective of whether or not they need any of our other tests. And they get integration into their workflow. Okay. So those are benefits for them. From our standpoint, there's a number of benefits as well. We get to consume that data. It builds into our database so that 160 million annotated CT images that's growing and growing and growing. We mine that data to create new algorithms. Those new algorithms help us expand our gross margins. Those new algorithms help us create new technologies. So as we launch new components of our platform over time, we have that data. And then because we have those data pipes, as we launch that technology, we do it in a very frictionless way. It literally is a new button on their already existing user interface. So physicians like that because they get it quickly and easily. And obviously we like that because it's a very efficient way to bring new technology to market.
I would assume there's at least some form or fashion of a moat there because you went through the InfoSec reviews and all the things at the hospital.
Yeah. Yeah. So in order to get a great, great, great point, we've got really high confidence that we've got a good model where we can go get the next new account. And we've done that, you know, to the tune of 1500 accounts, you know, currently that process, however, you need to go through. First, you need to build, you know, clinical champions. But then beyond that, you've got to bring in administration. You've got to bring in IT. You've got to bring in information security. In some cases now, you've got to kind of navigate a sort of an AI board at the health system. That process to land that next new account can take a lot of boards of a year, okay? So, again, a little bit of a barrier going in, but once you're in, it makes for a pretty sticky customer on the other end.
Maybe we could double-click on one of the things you mentioned, which is plaque. That's a newer sort of offering, at least from a commercial perspective for you. Maybe talk a little bit more about what that is, how that launch is going, sort of what you expect out of that. How important is that going to be over the next couple of years?
Yeah, perfect. So just for reference for the audience, The vast majority of our current revenue is all coming off our initial test. That's our FFRCT test. And that's a durable business that we believe is growing very nicely with lots of upside relative to penetration. The next kind of layer of cake, so to speak, of growth is our plaque analysis. And this is an analysis that's FDA cleared, and it's paid for both through Medicare and a large growing number of commercial payers. And we started launching this last year, and at the start of this year, we're in close to 500 accounts just at the start of, you know, early January. We think we'll be in north of 1,000 by the end of this year. Okay, so we're really excited about it.
Is that largely your existing account base you're going and penetrating?
The higher the majority, the majority of that is existing, but there's some news as well. Yeah, good question. So we're super excited about kind of the market interest on PLAC. And PLAC, from a patient applicability standpoint, has doubled the applicability of FFRCT. So more patients can benefit from this reimbursed technology. Now, we're still in the early innings of that. So there's a lot of kind of the initial phases of this is you've got to sign a contract, you've got to take them live. Now we're in this, you know, help them ramp and use it. Now, there's a lot of questions out there on exactly what is the right way to use this analysis. That's probably the number one question that I get, that the team gets. So we're leaning into quite a bit of medical education to help physicians understand how to use it. Now, that being said, based on all the early indicators, I'm extremely excited about what 2026 has for plaque. And I think by the second half of this year, we'll see some pretty material impact by virtue of all the early demand we've seen.
You mentioned how much it expands the patient population. Could you spend another second on who is plaque applicable for, you know, what's the experience?
Yeah, so it's covered, you know, the applicable patient population is really driven by the coverage that the physician will get paid for it. So where FFRCT is relevant to about a third of all patients based on their disease burden, plaque is about two-thirds. So much bigger. And so you could go get a heart flow analysis, not need an FFRCT, but very likely you're going to need a plaque. And I should say with plaque, you know, we're measuring disease down to the cubic millimeter. And a lot of people probably have had calcium scores, you know, That's usually a question I get. Calcified plaque is one type of plaque. Okay, there's non-calcified plaque. There's low attenuation plaque. Physicians really need to understand the full profile of what your composition of your plaque burden is in order to better treat you. And that's what we aim to do with our analysis. Much higher fidelity set of information around what you want. Yeah, you can't get it with the human eyeball. And yet it's not appropriate. There's no physician out there that's going to send you into the cath lab for an invasive procedure just to understand your plaque burden. That wouldn't happen.
Which is effectively the gold standard, invasive than the gold standard, right. Okay, so we talked about sort of plaque, how that could impact the near term. It sounds like you've got a lot of excitement there. As you maybe try to look out the next several years, what is it that excites you guys? What do you sort of focus on? What are the growth and value drivers as you play forward here?
Yeah. So I think, you know, in the, you know, whatever you want to call it, near midterm, super healthy kind of base business, you know, our core FFRCT business has tons of runway ahead of it. And that's the beauty of creating a new category is the more we're shifting towards, you know, CT plus heart flow, the more, you know, runway there is. So there's great opportunity with that in and of itself. PLAC coming online is super compelling and, you know, the top focus of the teams right now. But we still have this database, right? And we have a very long track record of using that database to introduce new technologies that we then can launch through these same bidirectional data pipes, as we call them. In 2026, the next element that we're launching is our navigator. This is our PCI navigator tool. This, again, is intended for downstream usage. This is interventional cardiologists, and they can use our platform to help plan for a PCI procedure. We really like this for a couple reasons. One, that interventional cardiologist can be a great champion for heart flow within the health system. So if they use our technology on all of their patients, they're going to help champion a CT-first pathway across their health system. So that's a compelling piece. The other piece is we believe in the power of the platform. The stronger the platform, the stronger the platform. And we know we can deliver value to an important stakeholder through this. So that's our 26 kind of platform expansion. In 27, we have what we call a serial plaque analysis planned. And so that's where you can track disease progression, or hopefully regression, from scan A against scan B. So if you think about this longitudinally, 2026 is really the year of patients getting their first plaque analysis, okay? You don't need a plaque analysis every year, okay? But then as you go into 27 and you're working with your cardiologist and you want to understand whether or not the therapeutics that you've been on are actually impacting your disease burden, what do you need? You need your second scan, okay? So we're going to launch a serial plaque technology that will co-register against the first and allow physicians to see exactly how the disease burden is being changed, hopefully in a positive way, relative to the therapeutics that that patient's been on. So that takes us through 2027. You know, beyond that, we have other technologies planned, but not yet for disclosed discussions. we were very excited about opening up a new addressable market okay so everything we've been doing up until now has been symptomatic patients patients with chest pain that's a six excuse me five billion dollar total addressable market the next door neighbor to these patients are high risk asymptomatic patients okay and and then beyond that you have sort of at risk and low-risk. We're going to enter the high-risk asymptomatic market next. That's another $6 billion TAM. We have high confidence that our existing technology doesn't discriminate whether or not you're having symptoms or not having symptoms. What we need is we need clinical data in order to open up that market. And so we have randomized controlled trials that are planned this year against three subpopulations. One is patients with high calcium scores. The other patients are patients with prior heart attack. And then the third is patients with prior plaque. And we'll have separate clinical investments against each of those subpopulations to open up that high-risk asymptomatic market. All of that, we believe, is going to hit us or help us before the end of this decade.
What do those trials fundamentally look at? You know, what do you have to demonstrate to get FDA clearance or to get adoption from the market?
The two primary endpoints are going to be plaque regression. So, again, how much does plaque change over time? And then, second, LDL. It's interesting. Change in biomarkers. We'll capture longer-term, you know, hard outcomes, but we don't believe that's needed to open it up.
Just give me one last question on that. You mentioned now a couple times sort of plaque regression or comparative plaque analysis effectively. Does that over time start to get you more integrated with the pharmaceutical companies? Like, is there a deeper partnership there in the way that they're delivering drugs and you're measuring success?
I think the opportunity is absolutely there. And what we are able to do is take a picture to tell whether or not the drugs are working full stop. you know so the goal of these drugs is to prevent the disease from growing you know and again there's a lot of analogies here between what we do and how cancer has evolved over time but if you you know if you find a tumor you treat it and you take another picture of the tumor and you make sure it's getting smaller or it's not spreading that paradigm doesn't yet exist in coronary artery disease but we believe with our technology we can get there right awesome uh well thanks again for
coming John really appreciate it exciting your head for the heart flow team yeah great thanks for having me thanks