From Palm Pilot to AI Assist: Inside the Reinvention of epocrates with president David Minkin

0:00Hey, Tim. Hey. Morning. Good morning. It is World Cup season every four years. It's amazing. I was just on a trip in Philadelphia and happened to stay at, I guess, like the official fan hotel of the Croatia team. It was pretty wild. That's pretty good. They were having a lot of fun. I wasn't even there on game day and they were still having a blast. if you know every four years i become like a very casual soccer fan as opposed to not a soccer fan at all and having it in the u.s has been like pretty it's been pretty awesome to see it's it's amazing yeah it's absolutely amazing and right now we've got wimbledon and world cup right now which is like epic good coming off the heels of a very great nba finals it's been a good sports summer usually the doldrums we're out of it right it's a lot to keep up with uh should we dive into business here?

0:47Let's do it. Welcome to Health Tech Remedy. This is the show where physician leaders in health technology break down the stories behind today's most interesting healthcare companies and ecosystems that build them. I'm Trevor Royce, joined by my co-host, Tim Showalter. And today we're talking about Hippocrates. This is one of the most recognizable names in digital health for clinicians. It's like my favorite app on my Palm Pilot back in medical school, a statement that definitely dates me. But for many physicians, Hippocrates was one of the first apps they used regularly, like myself. And it was the thing that you pulled up in clinic or on the wards to check a dose every time you wrote a prescription.

1:28And it's maintained relevance for the past 25 years as well. Yeah, absolutely. Tim, that does date you. Hippocrates would date you too, because I think it's been around since 1998, but actually it's the Palm Pilot. But, you know, similarly, Hippocrates was, it was the thing in med school. And it's just cool to see that it's still relevant and has, I think, a million daily users. We'll get into that. And one of the interesting things about Hippocrates, particularly for this episode, is obviously that it sits in this intersection of some big health tech themes. Point of care, clinical decision support, which mentioned already.

1:58The AI piece, it's well-suited for that era, so to speak. Workflow, pharma engagement, and kind of how these legacy reference tools can become something more like a real-time point of care clinical intelligence platform again in the modern era. And I think later we'll speak with David Mencken, the president and general manager of Apocrates, and he's been leading the platform through this next phase, including the rollout of an AI assist and engaging Apocrates in this evolution from a medical reference app to clinical engagement and an intelligence platform across the healthcare system. Yeah. And also, Adam, I'm excited to talk to David.

2:33I think he's got a very interesting background in this role, something more of a media background than a clinical background, which I think has some interesting implications for how we might view the product overall. And, you know, maybe that's just the sort of skill set that's needed to move things forward. Wanted to start with, I think what the obvious point is, as the listeners can probably tell from our initial discussion about Hippocrates, is that I think they're, the reason why this company matters so much is that they already have a tremendous clinician mindshare. So if we think about like level of trust, level of familiarity, how broadly it's installed and used, this is really a company that is uniquely well-suited to enter conversations where everybody already knows that point of care information matters.

3:20So, you know, clinicians have already, you know, sort of grown up in medicine like myself using this tool and they realize the clinical utility. So when you're writing a prescription and you need to know what's the dose I should use? Do I need to adjust for this patient's kidney condition? What else interacts? This is the sort of tool that's already established its role in providing the answers to that question. Yeah. I, you know, remember as the right-eyed, bushy-tailed medical student with my, you know, newly digital device, you know, an early iPhone, one of the, I had a little folder on the, or I had a little section of apps on the homepage that was like medical stuff.

4:00And And Hippocrates was the first one that I downloaded. We're checking, you know, dosing and interaction. So basically we replaced that old red book. What was it? The Physician Desk Reference, the PDR. You know, it was the new version of that. Now we're in this new era. So it's pretty cool to see it still contributing. And, you know, that's what makes it this an interesting company for our podcast is there are a lot of digital help companies trying to create new behaviors, but they're already so deeply embedded in workflows and as you put it, the mind space. So I guess the question then is, you know, can a tool that clinicians historically used for quick drug lookups and drug-to-drug interactions become a broader layer?

4:38Can it help clinicians navigate not just drugs, but guidelines, patient-specific context, safety beyond drug-to-drug interactions, treatment alternatives or pathways, all these kind of bigger clinical questions? Yeah, I mean, I think it's interesting when I think about how a tool like this can add clinical impact, I think it's, you have to know that the clinician is going to go somewhere and ask the question, which is, I think, part of the opportunity and challenge for Hippocrates. I think obviously people will think of it. It's on the list of reference resources that folks would go to. But I think the challenge that we're in now, and we're at an interesting inflection point for health technology, is that you still have to have the clinician ask the question.

5:25so the classic app for Hippocrates has that challenge where the physician has to actively go to the app and ask the question and I think this is where that AI assist is so interesting is there an opportunity to have physicians who have already grown to trust Hippocrates or other reference tools, can we get them onto a platform where the answers are being prompted already and are available right within their workflow so that they're being supportive with information like what is the dose of amoxicillin rather than rather than have to answer that yeah so maybe this is a good time to take a little bit of a deeper dive into this ai assist i mean i think that the general concept is let's move away from this as as you rightly put it you know a search and a reference tool to sort of conversational decision support in the era of llms and their sophistication so i think instead of saying you know i'm a doc i'm going to navigate these sort of static pages or these static sheets?

6:23Can we answer a medication related question in a more conversational way so that I get the context and I have easy access to, you know, other relevant topics without going back to say a table of contents or whatever the structure is? Yeah. I mean, I think sort of the wrong way to do it would be to do the like chat GPT rollout, which is this amazing story. Like I remember when that came out and I enjoy coming up with prompts for vacation planning with Chad GVT. But when you're in clinic and you've got, you know, no more than 15 seconds to spare, I think what you don't want is just a window with the blinking cursor and you can type in your question.

7:07I think that it has to be sort of a information constrained assistant that pulls from vetted approved resources and gives that suggestion right away with having a premium on clinician time. And so I think fundamentally, Pocrates and this AISIS story needs to fit into workflows in a different way than what we're used to for seeing generic chatbots, essentially. Yeah. Yeah. And I guess this is in a sense upon, but you don't want it to be overly prescriptive, meaning you don't want your tool as a clinician, I'm assuming, but also through through real lived world experience. Like, I don't want the app to tell me what to do without flexibility for the physician-patient relationship, the clinician expertise, and all the, you know, complicated features that are overhanging any clinical encounter.

7:58You know, ideally this type of tool says, you know, here are the issues, here's some options, here's the source material, and then you, the doc, make your clinical judgment on what's best. Yeah, it's like, here's what you should consider, not here's what you should absolutely do. Yeah, and I think it's interesting from a physician behavior perspective because I do think you're right. I think that's what would generate trust if the recommendations are presented as a suggestion and different physicians may want to sort of present it in different ways. But I think the general thread is make it a suggestion that preserves clinical judgment and not too prescriptive.

8:37I think that makes a lot of sense. so I think you know kind of covered this concept of AI assist and moving from a reference tool to more sort of engaging clinical environment tool how about on the commercial and the business side I mean Hippocrates as we've discussed is somewhat unique in that it was the sort of first mover in this digital world of health care and it does have mind share of clinicians and you know I think there's some brand equity built in there. How can they leverage that in this modern era? It's interesting because they're definitely, the software's interacting with physicians at just the right time to have, if there's a, say, life sciences company that wishes to have useful information at point of care when the physician's making a prescription, it's really a high intent moment.

9:29So obviously the doctor's in there asking a question about a specific, indication or drug. So there is an opportunity, but there's also this other side, which is, which is a challenge that Apocrys will have to take on, which is that people are used to looking for very succinct reference materials, I think within this platform and making sure that any interaction with, with say a pharma sponsor would be sensitive to that relationship between the, the, the trust of the physicians and what they're looking for, for, for fast information and what the goals are, would be, it's a really tough thing to get right, I think, for hypocritus.

10:07Yeah, I think that's the narrow path to thread or the needle to thread, so to speak. You know, have a nice commercially viable platform while preserving the usefulness of the clinical experience, the lack of bias, clinically credible tool that physicians continue to trust. Maybe it's the last topic to cover before we dive into the interview is their relationship with Athena Health, friend of the pod, you know, we've had them on earlier, so we should cover some of that. But as I understand it, in 2013, Athene Health acquired Apocrates for almost$300 million. Yeah, and I think that's an interesting sort of sandbox, I think, to try out what Apocrates looks like within a sort of ideal opportunity to be integrated within the EHR.

10:51And I think the The big question is, you know, in that environment, how are users using it most? Is it a standalone, independent reference app, or does it then through this partnership become integrated into the broader clinical workflow? Yeah. This would be a great topic of discussion with David Minkin when we have him on here in a bit. Fantastic. Well, I think we've provided a good backdrop for the interview, so why don't we move forward and bring in David Minkin, president and general manager of Aukratis.

11:28Today, we're talking about one of the most familiar digital tools in medicine for over 25 years, Hippocrates. I mean, it was the hottest app on my palm file at a med school and has continued to remain relevant to medical practice for this entire time. But Hippocrates is also evolving. Under the leadership of David Minkin, president and general manager, the company is moving from a reference app toward a broader clinician engagement and intelligence platform, including the recent launch of AI Assist. David brings an interesting background to this role, and we are so fortunate to have him on as a guest.

12:02David, welcome to Health Tech Remedy. Thanks so much, Tim. I'm super excited to be here this morning. Hippocrates is a product that many clinicians have used since medical school or residency, and I know you came to it from a different background, from digital media and publishing. Tell us a little bit about your career background and what attracted you to Hippocrates. What did you see about the opportunity?

12:24David Minkin: Yeah, totally. And thank you for being such a loyal user of the platform for so long. So, you know, Hippocrates, and you're right, I came from this from a non-medical background. I have a media background. Hippocrates, I think, has one of the rarest assets in digital health. genuine earned trust with clinicians that really has been built over more than 25 years. So, as you said, it started with Palm Pilots. It was literally, you know, in the white coat pockets before the smartphones of today existed. And that trust is not something you manufacture through a marketing campaign. When I looked at the landscape, I saw a platform with deep clinical credibility, a massive, highly engaged user base that hadn't really yet been given the tools it deserved for what medicine actually looks like today.

13:18David Minkin: And the opportunity I saw was essentially a reinvention problem. Hippocrates in no way was broken. It had just been really, I say, defined too narrowly for too long as a static drug reference. So the question I came in asking was, you know, what does this platform become when you give clinicians something that moves and responds and learns alongside them rather than just, I don't know, sitting there waiting to be looked up as a sort of reference app? And that's the question that really attracted me to this business and made me want to be here. You know, I've historically, as we discussed, I have come from this media background.

14:05David Minkin: You know, there's a pattern in the places where I've worked previously. I've worked at that sort of intersection of consumer technology and high stakes professional environments. And the thread is really that platforms that earn trust by being genuinely useful to experts, that's where I want to be. I don't want to be in a place that's dumbing down things, and that's not the Hippocrates way. Great. And I'm curious, when you got into the role and you started to talk to clinicians and see how they're actually using Hippocrates, was there anything that surprised you about the way clinicians were using it?

14:41David Minkin: I was taken by how loyal the audience is to the app. You know, there is just such a, the majority of our users actually are people who have been using this app for over a decade. And I think that was the most shocking realization for me coming into this, was that sort of, that loyalty, which, you know, I've worked with some very big niche publishers in the past, And, you know, you see some of that, but to have the bulk of your users within that cohort, that was really surprising. And I think really speaks to the trust that this platform has engendered over so many years and the utility of it. Yeah, it is.

15:34I can relate to it being a trusted product with a lot of loyalty behind it. And physicians are famously reluctant to change, obviously. So I'm curious about that as you approach really modernizing Hippocrates for the new era of technology and AI. How do you push for change while also respecting that loyalty and the expectations of physicians?

15:58David Minkin: Yeah. I mean, I think, you know, the honest answer is that you have to treat trust as this hard constraint, right? It's not an aspiration. So every product decision that we make, what to build, how to build it, what to put behind a paywall, how to handle, you know, commercial content, your clinical content, that has to get filtered through one question, which is, does this hurt trust with a clinician? In practice, that means a few things. It means keeping AI assist, which I'm sure we'll talk about in a bit, completely free of sponsor influence. Our AI responses aren't shaped by our pharmaceutical advertisers in any way, and we're very explicit about that.

16:40David Minkin: It means being transparent about what the tool can and can't do. You know, Hippocrates is not a diagnostic tool. AI Assist is not a diagnostic tool. It doesn't prescribe. It doesn't introduce bias into clinical content. And it means building with clinicians, not just for them. So since April, we had 75 clinicians in our alpha lab generating over 5 ,000 pieces of feedback on answer quality, on clinical accuracy, on workflow fit, on language. Our product and our clinical intelligence teams, they've analyzed all of it. And that's not just a beta test, that's really a development methodology that we have in place.

17:25David Minkin: So, yeah, we're super excited. But to answer that core question you had, it's really about the trust. And this is sort of what it looks like to earn trust rather than to just assume we have it. That's great. And maybe just to set the table well for listeners who may not be physicians, may not be daily users of Hippocrates, can you provide some use cases for how clinicians engage with Hippocrates, say, during a busy clinic day? You know, what are the sorts of things that they're coming to the app for? Yeah. So, you know, So essentially, Pocrates historically, as I said, has been this reference app.

18:07David Minkin: So the HCP is at the point of care. They're in an exam room with a patient or they're about to be in one or they're just left the exam room. And they have a question. They have a question about usually a type of drug, the interactions, the dosing. It might be disease-related questions that they have. But essentially, Hippocrates serves as that sort of know-it-all reference within your pocket. So, you know, back 25, 26 years ago, that was on a Palm Pilot, but today it's either on an iPhone or an Android phone. Yeah, that's great. And obviously, like in those clinical environments, you know, one change that has definitely happened in health care in general is that we're constantly dealing with more administrative complexities, more, you know, higher patient volume, more documentation requirements.

18:57And I'm curious how you think about Hippocrates meeting clinician demands to reduce their cognitive load and to embed within the workflow to make it simple. How do you think through that? Yeah.

19:09David Minkin: So, you know, I think this is a question that as apocriteans, we have to take very seriously when we're developing our product, because I think there's a thin line between, you know, what when something, you know, an app can be helpful versus when it's an interruption. And so, you know, our operating principle really is that we earn the right to be present in those critical clinical moments by being genuinely useful. That means the engagement that we're pursuing is pull-based. It's not push-based. Clinicians are coming to us because they have a question. Our job is to answer it faster and better than anyone else.

19:51David Minkin: You know, we aren't trying to inject alerts into the workflow or compete for attention they haven't offered. So, you know, fully understand that that clinicians do have this cognitive overload and we see our role as a way of just cutting through that and giving the answer that they're looking for at that time when they exactly need it. That is a great, great perspective. And I want to transition a little bit to what you're building now and sort of what the future, although in the AI world, it's always weird to see the future because things are moving so quickly. It's almost the present. But I know that it's, you know, it's increasingly a clinician, you know, intelligence platform and engagement platform.

20:37And it's evolving over time. What do you think that means for clinicians, say, who are engaging with Hippocrates and later in 2026 or 2027, compared with the version that many of us started with, you know, a decade or two ago?

20:50David Minkin: Yeah, I think the simplest way to put it would be along the lines of, you know, historically clinicians come to Hippocrates for information. Going forward, we want Hippocrates to help clinicians make decisions. So that's the shift from information to intelligence. At least that's how we're framing it. So a reference tool, what we've historically been, answers the question you thought to ask. An intelligence platform, that helps you work through the full clinical decision, evaluating the options, comparing therapies, assessing risks, validating the call you're about to make. We don't believe that clinical decision making, you know, happens in a single lookup moment.

21:34David Minkin: It happens across a sequence of questions, often under, you know, intense time pressure, I don't have to tell you, and often involving, you know, what I'd say are competitive considerations. So what we're really building is this AI layer on top of Hippocrates' deep content foundation. So that's drug monographs, that's pill IDs, that's calculators, interaction checking, disease references. That's all made accessible through the ways that clinicians increasingly expect to work, which is, you know, conversationally. I think we've all become or are starting to become accustomed to that. So, you know, I think when we think about the historical Apocrates and that sort of reference look up and coming to a drug monograph and getting the information there, you know, the goal isn't to replace that monograph.

22:26David Minkin: The goal is to make the monograph and everything else we know reachable through a single natural question rather than, you know, five separate navigation steps. And that's what we believe that a deeper workflow integration for Hippocrates actually will look like in practice. It's fascinating because I think what I hear in that is a real opportunity because if you can make it easier to get the right information to inform a clinical decision, you potentially expand the set of clinicians who will meaningfully engage, right? I mean, to me, I think the folks who need it most are often the least likely to ask the questions.

23:09David Minkin: Yeah, yeah. That's, I mean, look, I hope that's right. You know, that's part of our thesis for sure. We believe that Hippocrates has and will continue to be a real utility for the clinicians that we serve. But we also believe that this evolution that we're going through with our product will make it even more of a utility for an even broader audience, as you suggest. So that's certainly what we believe and what we're going for. And are you seeing this expand the types of questions that clinicians are asking or looking to have answered as you move into the AI assist era? Yeah, I think so. So, you know, you know, the way I think about that is like the drug monographs, they're really, they were built for completeness.

24:02David Minkin: You know, a clinician at the bedside needs specificity and they need speed. And those are fundamentally different design objectives. That's, how Hippocrates has historically worked. Clinician searches for a drug, they open the monograph, they navigate directly to the section they need, whether that's, again, dosing or interactions or contraindications. That workflow remains very valuable, but it does assume that the clinician can frame the right search query, navigate the right sections, and then synthesize the output into a specific clinical situation all in real time while the patient is waiting there.

24:37David Minkin: So the way I describe AI Assist and where we're going from a product standpoint is as this sort of intelligent guide within Hippocrates. So it helps clinicians move from a question to the information and tools needed to support the clinical decision all within that single workflow. So, you know, to answer your question, yes, I do believe it will, by that nature, allow it to answer more types of questions than historically could have been done so within a very static framework. So, you know, asking a question naturally instead of navigating to those, you know, five different sections, AI assist is going to surface what's relevant in the right sequence at the moment that it's needed.

25:25David Minkin: That distinction, I believe, really matters. The AI is not in any way generating an answer from scratch. It's making 25 years of trusted Hippocrates content accessible the way clinicians increasingly expect to work. So right now, that does cover specific medication questions, dosing interactions, side effects. But we are expanding that across our full drug library this year. And then over time, the vision is a more connected experience where AI is helping clinicians find answers and discover relevant resources and take action more efficiently across everything that Hippocrates knows. So, yes, I see the depth and breadth of the information we're able to surface via AI to be much deeper than, you know, what can be done through a single, you know, traditional user query.

26:18David Minkin: Interesting. As you're building this, I was reflecting on your background. I'm with a media focus, and I'm sure you've got a very nuanced lens on clinician engagement and really what works in terms of seeking those folks at the right point in time to impact patient care in a positive way. And I'm curious in your role, what metrics matter to you? Like, what are the set of outcomes that you think at the programmatic level are really the North Stars for new development within Hippocrates? Yeah, I think, look, I think it's about, you know, and this is very relevant to my media background. It's about engagement.

26:59David Minkin: It's about understanding, like, how often are users, you know, clinicians coming back to the platform? How much time are they spending with it? You know, are we seeing them and then, you know, they get their question answered and then we don't see them for many, many months? Maybe that happens sometimes if there's a specific answer they want. But ideally, we get to a place where, you know, we are the go-to when there's any sort of question that is around point of care. And that's really that metric, that understanding of both the number of clinicians that we're serving, but also that frequency of which they're engaging with our platform.

27:39David Minkin: Those are really the two key metrics. And then I'd say a third metric that's just as important is specifically when we're thinking about what we call our lean forward sorts of moment, which are really the content that is the drug reference content or the content that's coming out of AI Assist. How much, how long is it taking the clinician to get the answer that they want? because at the end of the day, we want to, you know, for all the reasons we've talked about already, you know, clinicians are busy. They've got things to do. They're in a room with a patient. We want to get them their answer quickly.

28:15David Minkin: We want it to be very succinct. We want it to be concise, easy to digest, all those synonyms. We want to be just super practical for what they're trying to achieve. And so understanding, like, how much time it's taking to get that answer is also a very critical metric that we take seriously. I wanted to cover just for our listeners who may not be familiar with the relationship between Apocrates and Athena Health. I wanted to get your perspective on how Apocrates fits within the Athena Health ecosystem more broadly and how to think about that. Yeah. So for those who don't know, Athena Health is one of the leading cloud native EHR platforms, and Apocrates sits alongside it as a distinct clinical intelligence layer.

29:03David Minkin: The EHR manages the workflow, so the chart, the orders, the documentation. Apocrates handles the questions that arise within and around that workflow, so the medication question, the interaction check, the quick reference that a clinician needs in real time. We see the relationship is very complementary. A clinician using Athena One for their documentation and Apocrates for their clinical decision support is getting two tools that are each purpose built for what they do. But they're part of the same broader ecosystem operating under the same parent company, but I would say with two distinct and generally non-overlapping functions.

29:45Yeah, I'm curious that you, in the digital health space, there's always this discussion and tension around whether clinicians want information within the EHR versus outside of the EHR. And I'm just curious what you've learned about that in terms of the Hippocrates-Athena Health relationship, if there are insights about how clinicians are engaging with Hippocrates in that context versus others.

30:10David Minkin: So, you know, I think it needs to be both, ideally. I think ultimately it's the preference of the clinician in terms of how they want to use it, you know, how they want to use us. Do they want to use us within the EHR, you know, on a desktop? Or is it easier to do something from a mobile screen? Both are correct. There's no wrong answer. But the way I see it is very much that Athena runs the EHR workflow. We're that clinical intelligence layer. And those are really two distinct functions that serve the same clinician. And we're better for being part of the same ecosystem. And whether there's crossover or not, I think crossover is good, but I don't think it's absolutely necessary.

30:52Well, I wanted to get your thoughts. It's obviously a really hot area right now. There are many AI-first companies that are trying to make an impact within digital health. Of course, Apocrates has been in this space for over 25 years. And I'm curious, as you look from your vantage point, what are the advantages that Apocrates has based on its user base and its space within the ecosystem?

31:19David Minkin: I think going back to my first answer about trust, I think that's the most critical piece of the advantage that Hippocrates has in the space. You know, that underlying content we have, AI Assist, our new AI product, that's drawing on our own clinical database, content that has been reviewed, validated, and maintained by clinical experts for literally decades at this point in time. So, you know, we're not scraping the internet. The AI is working within a very curated and trusted knowledge base, not generating content from scratch. Second, we have amazing guardrails that I think, you know, really are an advantage for us.

32:02David Minkin: You know, AI Assist, you know, it's not a diagnostic tool. It doesn't prescribe. It doesn't introduce any sort of bias into the clinical response. and doesn't incorporate any sort of sponsored influence into what it says. You know, we see those as really non-negotiable product principles rather than just, let's say, marketing language. And then third, you know, I really think it's about the clinician staying in the loop. So the design philosophy and what Apocrates does, and specifically how we're thinking about AI is that it supports clinical judgment. So not that AI is in any way replacing that judgment.

32:42David Minkin: The clinician is always going to be the decision maker, the tool. The idea is really that it just gives them better, faster access to relevant information so that the decision that they ultimately make is the most well-informed decision that they can make. you know we've been collecting extensive feedback from our beta community to validate that this is all landing the way we do we want it to but you know to answer your question i i think that that trust piece is probably the most critical piece and everything that we're designing is really built on that trust foundation and that's how we're we're distinguishing ourselves in this this ecosystem great well i know we're coming towards the end of our time together so i wanted to move towards a couple final future-looking questions.

33:27So the first one is, as you look ahead, say three to five years from now, what do you want Apocrates to be in the life of a clinician?

33:38David Minkin: So I think I want Apocrates to be the trusted environment where clinicians can bring their hardest clinical questions and then leave with answers that they can then act on. the path is already very clear for us directionally. Medication lookup, that's a really important entry point. And that's, it's what we've always done well, and it will always, at least as far as I can see, remain the foundation. But the destination is broader. Treatment options, dosing decisions, safety considerations, therapy considerations and comparisons, conversational support across really that full arc of clinician decision-making.

34:21David Minkin: Not just what is this drug, but rather I'd say, you know, help me think through this patient. So what that requires isn't just better AI. It requires a clinical credibility to be trusted in those moments. And that's where Hippocrates starts from, a position of strength that I think newer entrants just don't have. You know, we have an MPS score that we're very proud of, approximately 65, so mid-60, super high, which is, you know, well above health technology benchmarks. A majority of our active clinicians, as I said earlier, have been using Hippocrates for more than 10 years. So many tell us that they change prescribing behaviors or prescribing decisions based on what they find within our platform.

35:12David Minkin: So it's called the five-year vision is to really fully earn the role that foundation makes possible. The platform clinicians rely on, not just for quick lookups, but for the decisions that actually matter. And that's really what Hippocrates is building towards. I wanted to close with a question about future career goals and impact for health tech founders building in the space or, say, clinicians who want to make an impact. What advice would you give to those founders and early career folks who want to build new technologies for clinicians to make an impact on patient care? I think I can think about this from what isn't the right thing to do and then what is the right thing to do.

36:10David Minkin: So I think, you know, thinking about the answer to that question where, you know, the goal would be to replace the physician, that's a bad idea. I think there's a lot of breathless coverage in media about AI that can diagnose diseases or read scans. And while some of those capabilities are really genuinely impressive, the clinical, the ethical, the liability landscape for truly autonomous AI and medicine, I'd say, you know, at a minimum is very complex. So, you know, where I think the opportunity really is, is really about, and you were mentioning this earlier, it's about cognitive load reduction.

36:53David Minkin: the thing that's actually making a difference for clinicians right now isn't that AI is making decisions for them it's that AI makes the information gathering and synthesis steps faster and frankly less exhausting you know we hear it all the time clinicians are burnt out they're spending enormous amounts of time chasing down information that should be you know instantly accessible, AI that reliably cuts through that or any sort of product doesn't have to be AI, but AI, without introducing new risk, that's going to be more valuable to the average clinical, in the average clinical day, than a diagnostic AI will be for most clinicians in most settings, I believe, for quite some time.

37:39David Minkin: So that's the space that, you know, I'm focused on. Well, that's great advice. David, thank you so much for your time. It's great to hear about all the new developments within Hippocrates. Yeah, thank you so much, Tim. I really appreciate it. That's it for this episode of Health Tech Remedy. Thanks for joining us. Be sure to like and subscribe the podcast and share it with friends on your favorite platform. Stay tuned for our next upcoming episode where we talk about the latest in health technology.