You got to grab your research disclosures from our website at morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative. Thanks for being here. Really excited to have HeartFlow with us, and dig into another healthcare AI story. Maybe, John, just to start, if you could just sort of hit where you guys sit in the market, what your application is, what the need is, and sort of what your value prop is. Yeah, sure. Thanks for having me. Pleasure to be here. We are a technology company. We use AI, we deploy AI to better diagnose coronary artery disease. At our core, that's what we do. I think, this is a tech conference, but you're probably all aware of, you know, heart disease in and of itself is the world's number one killer. We think we're deploying our technology to a very, you know, 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 the patient's been through the healthcare system and it hasn't appropriately been diagnosed. That's really the problem that we're trying to solve. We're at the very early innings, but we believe we can create a new standard of care using our HeartFlow technology to do that. 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 HeartFlow technology is reimbursed. Well, first off, it's all cleared by the FDA. It's reimbursed, so it's covered by Medicare, it's covered by commercial payers. Our physician customers and their hospitals, they make a margin by using our HeartFlow technology. Similarly, we have separate revenue streams for those reimbursed technologies as well. 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 second 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, you know, imaging modality and whatnot. Yeah, sure. I should mention, our technology sits on top of a coronary CT image. Okay. That's what we deploy our AI to. if you- 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? 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. Okay? That's the market that we're 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, in the, like I mentioned, the really early innings. We're about a 2% penetration against that total non-invasive testing market. 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. A Coronary CTA, again, is the frontline 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? These are stress tests, treadmill tests. Sometimes you call them nuclear tests. The vast majority of the market still relies on those. We really believe our technology is better and can improve on the inaccuracies. Just a note on those, 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, 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. We can avoid those false positives and those false negatives. Patient ends up with a cardiologist, gets a CCTA. Yep. Image goes in the cloud to HeartFlow. Yeah. What's the platform and the products or solutions that come off of that then at that point? Yeah, good. First of all, we have a technology platform. We're not a singular test. Okay? Our platform, and we're committed to this, but our platform continues to expand year on year. Okay? 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. Okay? The first part of our platform, we call it the RoadMap Analysis. This is a workflow tool. We have clinical data that substantiate... It allows CT readers, so these are the physicians that are reading that CT image, to read it faster with less variability. Okay? We provide that free of charge for every CT that's sent to HeartFlow. Okay? 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. Again, we back this with clinical data, so we know it's accurate against the invasive gold standard. Okay? 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. Okay? Separate insight than plaque, and again, separate reimbursement for the physician. Lastly, which we're launching here shortly this year, we have what's called a navigator tool, a PCI navigator tool. 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. That's the platform in as it stands now, but again, we fully intend to continue to add components to it. 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. Mm-hmm ... on your side. 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? Yeah. Can it not, et cetera? Yeah. First thing I'll say again, we're in healthcare. 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. Okay? That human serves a really important component. They ensure quality of the algorithm. Okay? The first step that occurs when we ingest these CT 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 coronary tree. Okay? If that model is perfect, then all of our algorithms can run autonomously off of it. Okay? Because CT images come, and sometimes they have artifacts in them, sometimes, they might be blurry based on a patient's heart rate when 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. Okay? 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. If we were having this conversation, you asked kinda how long does it take to do. If we were having this conversation, you know, 15 years ago when the company was founded, that quality control analyst probably spent 20 hours doing those connections. Okay? Last year, at the end of last year, they spent about 20 minutes. Okay? Every Is that fundamentally been a technological improvement? Yeah. Exactly. That's 100% what it's been. Every unit of time that's taken out is a function of our algorithm getting smarter over time as we feed it more data. We've taken a lot of time out over the years, and you can look at our margin expansion over the same period of time and see that occurring. I've got super high confidence that that expansion is gonna continue in the future. 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 gonna 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. You maybe just spend a second on the algorithm. You've talked about, you know, you've got a 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 in the investor community right now on, you know, how proprietary or not is the data, how proprietary or not is an algorithm or a piece of software. Maybe just talk us a little bit about the training and building of the algorithm, the testing that's went into it, the proprietary nature or not of the data you have, et cetera. Yeah. Good question. First thing I'll say is, you know, right now we've got, give or take, call it 160 million annotated CT images, okay. These are clean CT images that have been for lack of a better word, kind of scrubbed by our analysts over the course of time. This is a data set that's incredibly diverse. We've been growing it for 15 years. As different anatomies come through, 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. Like I said, we've grown it over time, and as we speak, it's growing, okay? Every time we ingest a CT, we grow it. 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. That's one really important piece that I think serves as a compelling moat, so to speak, as we move forward. The other is around, you know, as I mentioned, this is a re-regulated space, okay? 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. That's a skill set that we've built, and I think we're pretty good at over time. There's another kind of data that's I would argue equally as important as the data we use to train the algorithm. That's our clinical data, okay? At the end of the day, our customers are physicians, okay? Physicians, you know, by and large, make decisions on, "How is this gonna help me treat my patient better?" The way you impact practice patterns and change behaviors, remember, we're trying to shift behavior from this traditional standard of care to this new one, is through strong clinical data. 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. That's taken us 15 years to accumulate. That's orders of magnitude more than any other, anybody else has got, and we're continuing to invest in that. 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, okay? 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? After we, kinda go live in an account, we work to integrate across that entire ecosystem. That can be challenging in a lot of respects, and it's taken us a long time on how to do it well. Where we are now, we really think it's a, it's another kinda compelling piece of our moat because once you're in, the switching costs are pretty high, and we see a lot of really kinda sticky behavior. 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. Mm-hmm. I think that's actually an exceedingly rare asset or capability. Mm-hmm. across healthcare. You know, I talked to Tempus earlier today. They've got that. 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, 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? 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 bi-directional 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, okay? I just say that to say there's a lot more pipes for us to kinda connect, and, you know, if there's 300 new ones entering the category every year, that's gonna keep us plenty busy. This is just U.S. Yeah, this is just U.S. Yeah. It's by virtue of that that we set up these data pipes. Once that occurs, the minute one of these patients that I mentioned, this is patients coming in for a non-invasive test for 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. 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. They get integration into their workflow. Okay. 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. As we launch new components of our platform over time, we have that data. Because we have those data pipes, as we launch that technology, we do it in a very frictionless way, okay? Literally, there's a new button on their already existing user interface. 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. You know, I'd assume there's at least some form or fashion of a moat there because you went through the InfoSec reviews and all the things that the hospital would get. Yeah. Yeah. In order to get. 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 1,500 accounts, you know, currently. That process, however, you need to go through. First you need to build, you know, clinical champions. 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, at the health system. That process to land that next new account can take upwards of a year. Okay? 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 gonna be over the next, you know, couple of years? Yeah, perfect. 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. 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. This is an analysis that's FDA cleared, and it's paid for both through Medicare and a large growing number of commercial payers. We started launching this last year. 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? We're really excited. Is that largely your existing account base you're going and penetrating or? The majority of that is existing, but there's some news as well. Yeah, good question. We're super excited about kind of the market interest on plaque. Plaque, from a patient applicability standpoint, has double the applicability of FFRCT. More patients can benefit from this reimbursed technology. Okay? Now we're still in the early innings of that. Kind of the initial phases of this is you got to sign a contract, you 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. 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, 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 expansion? Yeah. It's covered. You know, the applicable patient population is really driven by the coverage that the physician will get paid for it. Where FFRCT is relevant to about a third of all patients based on their disease burden, plaque is about two-thirds. Yeah. Yeah. Much bigger. You could go get a HeartFlow analysis, not need an FFRCT, but very likely you're gonna need a Plaque. Right. Yeah. I should say with plaque, you know, we're measuring disease down to the cubic millimeter. 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. Right. Much, much higher fidelity set of information around what you want. Yeah, 100%. Yeah, you can't get it with, you know, human eyeball. Right. Yet it's not appropriate. There's no physician out there that's gonna 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. Yeah. Invasive is the gold standard. Yeah. Okay. We talked about, you know, sort of plaque, how that could impact, you know, 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 are you sort of focused on? What are the growth and value drivers as you play forward here? Yeah. I think, you know, in the near midterm, super healthy kind of base business. You know, our core FFRCT business has tons of runway ahead of it, and, you know, that's the beauty of creating a new category is the more we're shifting towards, you know, CT plus HeartFlow, the more, you know, runway there is. There's great opportunity with that in and of itself. Plaque coming online is super compelling and, you know, the top focus of the teams right now. We still have this database, right? We have a very long track record of using that database to introduce new technologies that we then can launch through the same bi-directional data pipes as we call them. In 2026, the next element that we're launching is our Heartflow PCI Navigator. This is our Heartflow PCI Navigator tool. This, again, is intended for downstream usage. This is interventional cardiologists, they can use our platform to help plan for a PCI procedure. Okay? We really like this for a couple reasons. One, that interventional cardiologist can be a great champion for HeartFlow within the health system. If they use our technology on all of their patients, they're gonna help champion a CT first pathway across their health system. 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. We know we can deliver value to an important stakeholder through this. That's our 26, kinda platform expansion. In 27, we have a what we call a serial Plaque Analysis planned. That's where you can track disease progression, or hopefully regression, from scan A against scan B. 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? As you go into 27 and you're working with your cardiologist, and you wanna 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? We're gonna 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. That takes us through 2027. You know, beyond that, we have other technologies planned, but not yet for disclosed discussions. We're very excited about opening up a new addressable market. Okay? Everything we've been doing up until now has been symptomatic patients with chest pain. That's a six-- excuse me, $5 billion total addressable market. The next door neighbor to these patients are high-risk asymptomatic patients. Okay? Then beyond that, you have sort of at risk and low risk. We're gonna enter the high-risk asymptomatic market next. That's another $6 billion TAM. Okay? 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. 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 gonna 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 gonna be plaque regression, so again, how much does plaque change over time, and then second, LDL. It's intere- Change in biomarkers. It's in- We'll capture. Sorry to interrupt. Yeah. We'll capture longer-term, you know, hard outcomes, but we don't believe that's needed to open it up. Just maybe 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, the goal of these drugs is to prevent the disease from growing, you know. Again, there's a lot of analogies here between what we do and how cancer has evolved over time. If 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. We believe with our technology we can get there. Right. Awesome. Well, thanks again for coming, John. Really appreciate it. Exciting year ahead for the HeartFlow team. Yeah. Great. Thanks for having me. Thanks.