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What If the Patients Who Need Your Test Are Already Hiding in the EHR? Sagacity Diagnostics · Diagnosing Dx

• David Filby: Welcome to the show this week, Raymond. How are you? Raymond Tarr: I'm doing really well, David. It's a pleasure to be here. David Filby: We've got some really exciting things to talk about today. And actually I was thinking about this before the show. that arguably the biggest priority in the industry that we keep coming back to at the moment is this theory of adoption, but ultimately how do you educate and make aware to create adoption. And actually what we're going to talk about today Is something that is really going to focus on increasing adoptions. I'm actually really excited because I think this is a really on point discussion about arguably the biggest challenge in the industry at the moment. So before we do that, it'd be great to get to know you a bit better, your background and career and what you've been doing if you'd like to introduce yourself. Raymond Tarr: Yeah, of course. So I'm Raymond Tarr. I'm the founder of Sagacity Diagnostics, which is in a nutshell, we are a clinical decision support provider, education provider, tool provider. So my background is I've spent over 25 years in the diagnostic space, launching new technologies, worked for some, fantastic people like Carl Wittwer, who co-invented the LightCycler system with Kirk Ririe, that basically launched molecular testing into the hospital systems, revolutionizing healthcare. I've been blessed to work with them on the commercial side as well as on that academic side. I've worked for companies like Cepheid that completely turned PCR into a commonplace in the healthcare system as well. So I've always looked at driving new testing, building new tests, building new systems. Recently migrated over to Alexion, which became AstraZeneca. My role there was to speed up the diagnosis for patients that have rare disorders. And you know, it was really eye-opening. Instead of going after more testing, you realize quickly as an example that there is a lot of data just sitting in the EHR. So being a lover of analytics, being a lover of math and data and the whole thing, and of patient care, started working in the area of patient finding, patient education, clinician education, and really driving some change. Working through that whole process about two years into that working on the rare disease space, ironically, we became caught up in the system of looking for a rare disease diagnosis. My wife had been injured on the job that caused sort of a cascade of health events. And we found ourselves for the first six months caught up in the churn in the healthcare system until we finally had a chance to take a step back and say, wait a second. We're not gonna be one of these groups of people who get lumped into the four and a half years, seven years of diagnosis time. We can do this better, we can do this faster, we know what the kinks are. And sure enough, we took a step back, we organized the diagnosis, the care, and everything, and shortened her diagnosis down to six months, so saved about three and a half years of just sitting in the system. So having seen that. I think I would say I was motivated to do good work for patients and clinicians in this space. It changed to Drive. And Drive is a never ending fire. I'll never need to watch a Rocky film to get excited for something. You know, I will just absolutely continue to drive this mission to change healthcare for the better. And so that was the birthplace of PathfindEHR, our first product. And so that's pretty much me in a nutshell. David Filby: Awesome. And so Raymond, what were the types of roles that you had performed throughout your career in diagnostics? Raymond Tarr: So I started off as a researcher first, moved into the commercial side as a kind of a scientific liaison between commercial and R&D. Loved that role, realized quickly that I was probably a mediocre scientist at best, but I was a pretty darn good commercial person. So I transitioned into a sales role, rose through the sales ranks, managed government accounts, managed people obviously, like directors of sales and things like that. Continued to grow my career up through at Cepheid as an example, on the commercial side, I was the GM for Asia Pacific and so started that program pushing basically the PCR across the Greater Asia hemisphere there. So managed to do that work. And then I've been the head of diagnostics at AstraZeneca as an example to AstraZeneca Alexion as well. David Filby: What was it like going onto that side of the industry, onto the sort of therapeutic side, but still obviously in a diagnostics capacity and was that your first exposure to rare disease as well? Raymond Tarr: I would say it was definitely my first exposure to rare disease. And it was quite the transition. You know, within the diagnostic sphere as an example, we are a regulated body of companies. but once you move into the pharma space as an example, that compliance and regulation really expands greatly. So it really manages everything you do. The beauty of it is though, when I moved over, you know, I potentially had some diagnostic bias moving into pharmaceuticals. And what I learned quickly was there are amazing people doing great work on that side of the house, too. And so merging the two diagnostics, that expertise with these people who truly know just about everything there is to know about disease and caring for these patients, just was probably some of the most rewarding. You know, five years of my life to be honest. David Filby: Working for pharma and seeing their perspective in diagnostics and the amount of testing that goes on around rare disease, was it eye opening, was it potentially shocking in terms of what you know, the statistics and the reach that you were now becoming aware of? Raymond Tarr: I would say the statistics initially surprised me until I saw how people were implementing their workflow. and I realized that you have a lot of people directing or trying to direct a diagnostic pathway when they don't understand how data or patients flow through a hospital system. So rather than becoming an advocate or a partner to the healthcare system in a lot of ways, you're disrupting the work that they're doing because you're trying to sort of force fit something that you see as being a benefit. So as an example, you have a therapy that is part of a disease state that has two parts and you only have clearance or an indication for treatment for that part B. Most of the pharmaceutical companies are pushing for just dialogue and diagnosis around part B. And so they ignore the part A of the disease. And in some cases, what's ironic is you have to rule out that part A of the disease in order to get to part B, but you're completely ignoring this. And when you think about messaging to highly intelligent clinicians, you're saying we're here to do altruistic work by helping you with the diagnosis and ignoring part A, because we only get paid for part B. So the the great thing about AstraZeneca was that they allowed us to look at disease as a whole. So we didn't run into these issues of, well, we only have an indication for B. They allowed us to do diagnosis for that patient, whether it was A or B. We were diagnosing disease. And that was where we were able to have impact and shorten that diagnostic journey even more greatly. David Filby: And so you'd come across this personal situation that you tackled yourself, which is obviously incredibly fortunate that you have this vast knowledge of the diagnostic space and rare disease that meant that you could see a real, long challenge ahead and were able to overcome that. Was the insights from your time with Big Pharma plus that, is this the reason that Sagacity exists? Raymond Tarr: 100%. It's a culmination. They always say that you're the sum of all your parts. And it's very true in this case. So without that experience in rare disease, likely I would have continued to push more technology, more assays, more data into the system. Knowing how rare disease works gives a sort of this competitive advantage. The new term is a competitive moat. Everyone loves to use that term. But it truly does in this case because we understand both sides of the equation and we understand the patient side very deeply, but we also understand the clinician side very deeply. So when it comes to partnering with the clinicians, people tend to vilify doctors in a lot of ways, you know, like, my doctor missed this or they should be doing that. And, when you look at the amount of work that these folks put into their job, you as the patient, it's incredible. The amount of pre-work that they do, the amount of education that it takes to get to that point. And so what we find is that by partnering through that, really truly partnering with the clinicians to drive change, they also know where basically the obstacles are. They also need help overcoming some of that. And that's where we come in. We can marry additional opportunity or leverage better tools that they can use. And we can do that through partnership with the pharmaceutical companies, with the diagnostic companies, and drive change for the good. David Filby: So let's get into it. So who are Sagacity? Raymond Tarr: So Sagacity, I have two additional co-founders. One is Travis Musick. He also comes from the diagnostic space, worked for Ventana, Roche, worked with me at a couple other places as well. Excellent at commercialization. So that's very important because one of the things that we've talked about is everything that we do is scalable. The one thing that we focus on is getting this into the hands of the clinician. And it has to be done in a very broad way. You can't just right now a lot millions of dollars are being spent on creating AI systems that will go into the EHR as an example, and pharma's pumping money into it, and it's brilliant work. The problem is no one knows how to commercialize it, no one knows how to scale it appropriately. So always keeping our eye on that is really important. So Travis Musick is one of my co-founders. The other co-founder is Robert Smith, who is a longtime entrepreneur, creator of SaaS. I mean he's really the genius behind our technology. He comes from a space where there's a lot of analytics and things like that through his work with the NFL and you know some of the work that he was doing there. And he's always wanted to apply that horsepower to something that made him feel like he was having a human impact. And so when we started talking about this, he jumped in feet first and just has done some amazing things. So at the end of the day, we've created a product called PathfindEHR, and what PathfindEHR is going to be is three parts. So right now we've launched our PathfindEHR Pathways, which is an educational platform for clinicians sponsored by Pharma. So it'll be free for the clinicians to come into the system, receive education around the disease. So everything from epidemiology, disease definition, the diagnostic pathway, treatment options, all of that is embedded in the system. It's very much like an up-to-date chapter in that regard. We've then taken it a step further and we've included SQL language. So if you want to create, for instance, so basically what we're doing is automating the health informatics role in some respects. So, if you want to integrate in your healthcare system, your, like say Epic, you want to create an alert in the system. The SQL language is already written there. So you'll be able to take that and move it into your Epic system, do the work, and now you have a system for flagging patients coming into the emergency room as an example that look like a specific disease. There's SQL language for stops. So what that means is the doctor goes and they order a prescription, but that patient doesn't have a particular vaccine. The stop pops up and says, hey doctor, you also need to order the titer for this particular vaccine or order the vaccine for this patient before they can get therapy. So now the doctor knows, hey, I need to get this done before they can get their therapy. And a lot of places in our system, we can do the order set right there. So it says here's the order. They just click on it, they're done. So then the script goes to the pharmacy, patient goes to the lab or wherever they need to go for testing. So it's all built into that system. And then on top of that, we also build what's called a recipe for Epic. We do this for Cerner, Epic, or any EHR. And the recipe is basically something that you can cut and paste into your search bar. So like the SlicerDicer in Epic. And what it does is it runs a suspect patient list. So the amount of time that it takes you to find all the patients that meet a specific disease profile in your population takes the amount of time of cut and paste into your system and hit enter. So you can find your suspect patient list that exists within either your health system, but as well as even in a an independent physician practice can do this. A lot of times they use like their front office staff or their billing staff to do that type of work. And they can do it in their office too. So again, we talk about that scalability. This has been done at over 150 health systems and over 80 independent physician practices. It's not difficult to do. What's difficult is the physician part. So the physicians still do the work. They have to analyze that patient record and bring them back in potentially for additional testing and things like that. So that's PathfindEHR pathways. And then as we continue to build, we have a PathfindEHR research piece that will be used to manage clinical trials, research, and do deeper medical record searches that will be on the other side of the firewall. So Pathways sits on the outside of the hospital system. Research will fit inside the EHR system and can look deeper for a disease state. It'll be, likely software as a medical device, so it'll have to go through a whole clinical trial. And then our final piece is pulling patients back into the equation. So one of our frustrations or my frustration, I can say as a caregiver, is once the diagnosis happens, it seems like it's kind of we're done. You know, move on. That patient, that person has to live with that disease for the rest of their life, more than likely. So, how do they do that? And I think that that takes a community approach. And so we will have pathways for patient, and that'll be a portal where they'll have access to all of that medically curated information on disease, but then they'll also be able to write their experience with living with disease, where they find their resources. Advocacy groups can post links and support and things like that in the system as well. But more importantly, the system will do some clinical trial matching for these patients so that they can participate in clinical trials. And then the second piece is there will be some patient self-advocacy tools. So the idea is move away from Google Health, if you will, and use this system where if the patient has dialogue within the system around my disease, these are the things I'm experiencing, it can produce a report that's medically relevant that they can take to their clinician and allow their clinician to scan the barcode, read through all the information, either agree or disagree, obviously, as they walk through it. But it gives the patient the ability to self-advocate as well, which I think will help tremendously, both from a clinician's point of view, but also from a patient point of view, gaining a diagnosis and also living with disease. David Filby: So if I work backwards from someone who potentially has some sort of rare disease who has gone undiagnosed, what you're saying is one of the core parts of your system is that if this sits within some sort of EHR system, it will be able to identify patients who should be getting tested because it understands symptoms associated with potential rare disease and it's able to go through whether it's an independent clinic or whether it's a large health system it's able to go we've gone through all your data these people should be getting tested for this rare disease they're not being tested let's get them back in let's run these tests and we'll be able to identify more rare disease and I assume that would be an ongoing thing and rather than just being a sort of hindsight and historical look through their records, it then becomes a go-to resource as and when people come in and have you know checkups and visit their doctor. So I know I'm probably rambling, but so to work backwards from rare disease, this really helps diagnostics companies that have great science, great testing that is just not being adopted even though there's candidates out there that should be getting tested, but it's being missed for obviously a variety of reasons. Am I getting close to the point? Raymond Tarr: Yeah, absolutely. So on the diagnostic side, we did some work where there are two forms of testing. One is highly efficacious, the other is not. I mean, you would actually improve its sensitivity by flipping a coin every time you received a sample in-house. And the problem that this, the organization large lab was facing was the cost. One is extremely inexpensive and the other one is a little bit more expensive, but the difference in sensitivity, so being able to diagnose the patient, you know, you were talking about 40% increase in sensitivity. I mean, that's tremendous. And so when we started doing some work around this as an example, you mentioned in the health record, so we worked with this large health system to concentrate on their patients. They ran our system. They identified all the patients that they've already diagnosed, of course, was in their dashboard. Then there was a second tranche of patient that was, so this is in a ultra-rare disease. They found 22 patients in their health system that required additional workup of some kind. So on the diagnostic side, that's 22 tests that need to be ordered in order to help diagnose this patient. If you go the route of a test that's say 25 to 37% sensitivity, you're gonna miss the majority of those 22 unless you get lucky and just happen to find that really sick patient that comes up positive. On the other side, if they order the correct testing, which in our system, as I mentioned, you can do order sets. So the order set that came up was the most efficacious test. So it automatically, for the clinician was able to order the right test. So those tests were being ordered. But I should mention too that there was a third tranche of information that came across when they did the population study, and that's misdiagnosis. So, as I mentioned, we had double digits in the diagnosed as well as in the potentially needing diagnosis group, so the suspect patients. But there were over 600 patients in that particular health system that may have been misdiagnosed. And this particular test will clarify whether they have sort of one disease state versus the other. And the scary thing is, is in this particular case, this particular disease, if you're misdiagnosed and being treated for the misdiagnosis, you're actually exacerbating your symptomology on this rare disease. So you're actually making the patient sicker over time. And so if you think of the scale there, I mean 600+ patients, all they require is an additional test. So from the diagnostic side, right, you're getting more testing. That's 600 patients that should easily be tested using the more efficacious testing, plus the 22 that they saw in their system that should be, they're also suspect patients. So it really drives it drives testing volume, it drives the appropriate testing. And one other important piece of this too is the timing of the test. Sometimes treatment can occur that will confound a diagnostic. So when patients are plexed in the hospital, that can confound some of the like an ADAMTS13 test that comes up, it'll confound the result. And so with our system, it can say like, hey, we suspect this patient might have complement involvement. You should run this test before you do any treatment. That way you draw a fresh sample, it goes to the lab, it's like, you know, the old term garbage in, garbage out. You remove the garbage. And so by doing that, it also improves the testing but reduces cost for the hospital too, because now you're not running multiple tests on a sample that probably should have just been run right out from the gate. David Filby: And so do you see the need to partner with diagnostics companies who are creating new tests and discovering new specificity sensitivity, is that part of the business model that you'll need to be partnering with these companies to get their testing and their science into your system so that you can find new potential candidates all the time? Raymond Tarr: Well, new as well as existing. So, the new the new folks obviously are gonna be looking for the patient. You know, who's the right patient at the right time? And this system helps with that beautifully. But there are companies, you know, I was recently I watched a news clip on Guardant Health and they're explosive growth and they're doing extremely well in the marketplace. And then the statistic popped up that, only 40% of men are having their prostate test done timely. So I believe the guidelines have changed to roughly around age 48. So I'm 54 as an example and I've yet to have a test done. And I started thinking about that where I go for a physical every year. I'm very diligent about it, you know, all the family history and things like that. So I always go. But no one's ever brought up, hey, you're due for this test. And so there's another opportunity for even companies that have an existing strong test to alert the pay you know, the clinician while they're doing the ten thousand other things that they're trying to do for you to remember that, hey, you know, this guy's 54 you probably should have a prostate screening test done. And so, you know, 40% when you consider how well these companies are doing in the marketplace, it really kind of knocked the legs out from underneath me. I thought that, we were doing much better than that from an adherence point of view. David Filby: And yet unfortunately not surprising as a 40 year old male. Unfortunately that is just you know, I can see it. I can see it in conversations with friends and family, you know about how unaware or uneducated, the average, middle aged male is when it comes to the standard of testing and even how testing is performed these days. Do you see eventually the system moving outside of rare disease into other indications? Raymond Tarr: Yes, for sure. We focus on rare just because you always focus somewhere, you always start somewhere and David Filby: You have to, yeah. Raymond Tarr: we have deep knowledge there. But we also have deep knowledge in oncology, cardiology, other areas. And so what I would say is almost every area, we're starting to lean into some work, for example, some groups have reached out on obesity. And the GLPs, for example, are a great new drug class and it's revolutionizing how we take care of ourselves. But there are patients, there are some patients that will do better than others as an example. And so when you think about identifying the patients who will do really well on a therapy that could be potentially expensive, you want to identify them and get them on the right therapy. So there's work that's being done with us at this point, too, to even look at those populations and identify the right patient so that they have access. We did some work when we were at Alexion, our government affairs and medical team just did a superb job driving this type of process as well in for health equity purposes. So they were looking at underserved populations in the Boston area, and there's an organization there that supplies specialist care for the indigent population. And so what they were looking at doing was finding those patients that could let's say you have a rheumatologist that's coming in for a week's worth of work to see patients. Well you want to identify the patients that really need to see that rheumatologist, take advantage of having that specialist on site. So they started doing work around that as well. So yeah I think our system can be used for just about any disease You know, the more difficult the diagnosis, I think the more value we bring, but we've worked on the oncology side, for example, where one of the therapies required a specific test in order to be on therapy. 80% of their scripts were being held up by the pharmacy because the doctors weren't aware that they had to order the test to get the drug. These are diagnosed patients for all intents and purposes. So by putting an order set in the system using our technology, they were able to unclog that pipe and get that 80% cleared out. So, you know, we can work just about anywhere. It's about workflow and that partnership. David Filby: I'm excited about this because I said it at the top of the show, I think one of the biggest blind spots that early stage diagnostics companies where you're a single novel science trying to bring some sort of new test to market, one of the biggest blind spots those companies have is that you hope that they're aware of their reimbursement pathway and regulatory hurdles of what their commercial strategy is and and they have to get over, you know, that good science isn't enough and you hope they have all these other things lined up. And then even once they've got those things lined up and even they get to FDA approval or maybe they're you know commercialised as an LDT, one thing that can really surprise them is just how hard it is to drive adoption and raise awareness of their test. And so for me, I think in previous years I always felt reimbursement was the biggest challenge in the industry, and it's obvious why that is, but I do genuinely think that education and awareness is right up there with it, and so something like this I think really hits right in the centre of what is a really big challenge in the industry. So, where are you as a company then? Because you mentioned that some of the stuff you want to do will actually need studies and trials, but where are you in terms of the product being commercialised and used? Raymond Tarr: So we are absolutely live and well with the PathfindEHR pathways piece. We've engaged several pharmaceutical companies, a couple diagnostic companies. Interestingly, there's some CROs that have reached out as well because as you had mentioned and intimated there, they're looking for patients to enroll in they're very project-based. So you know, we're working on a clinical trial for this particular disease this time. One of them was a very specific use case where it was a 50 mile radius around the center of a city. And they wanted to know how many potential patients can we find in this area. So we are fully commercialized at this point. We are moving forward with several of our potential clients. As I mentioned, we're only about two weeks post launch. So you know, no POs sitting in the inbox yet. But when you build your career around doing the right things and helping people, it does pay off in the end. I mean, the amount of support and goodwill that we're getting organizations moving through, I mean, you know, as an example, one of the largest pharmaceutical companies in the world right now, we're engaged with five departments within that company. And the use cases vary across, you know, you can imagine five different groups, but the beauty is that you know these are all just conversations that we're having. They're seeing the value in this. And things that you mentioned are true. So if you think about launching a product, you know, you start with your funnel. How much do you have in that funnel? Well one of the things that we can definitely stand behind is that, when we launch these projects, we find two patients, for example, for therapy, we'll find two patients for every one that needs therapy at the time. So we're doubling the number of patients, more than doubling the number of patients that you might have on your therapy or being tested from a diagnostic point of view. But then we were finding four to one on average that are in the watch and wait. They still require diagnostic help. So if you're launching a new test or trying to figure out within a health system, how do we justify doing a test that's been traditionally a send out? how do we justify it in-house? Well, if you run our population suspect patient list, you'll see how many patients you potentially should be testing in your health system. So that gives the lab the ability to now monetize as well. That information will also help when it comes to the payer and reimbursement over time. You know, the payer needs to know that this is a necessity, that this test is going to bring change or save money somewhere or bring a patient. You know, for instance, like when we were going through our diagnosis, we were seeing nine specialists. In the end, we needed one. We just didn't know which one. So by cutting that down by, over three and a half years. You know, we saved all that opportunity cost there by identifying the disease sooner. So, there's a lot of ways that you can save money that draws attention, building your funnel, knowing what your population really looks like, what is your TAM overall? You know, what is that total accessible market? and again, this is zeroing in on the right patient. The way that we do our work, there might be some patients that have symptomology that we might miss. So it's not bulletproof. It's not 100% but those patients are likely those patients that might have disease, but their symptoms are so minor that they never it's sort of like, you know, I have a headache every once in a while type of thing. You know, that's not something that requires a change in lifestyle. So yeah, so we're we're fully launched, fully engaged. we're still driving towards the research side. We are in the process we've had a few great conversations with venture capital and private equity people. We're sort of on the fence as to whether that's the route we go or do we continue to try you know, just self-supported through customers and things like that. But those are all business decisions yet to be made. So whole set of different problems, but exciting problems nonetheless. David Filby: Just to clarify on that, is the question whether you raise capital at all or whether you raise capital from institutions like a VC or PE? Raymond Tarr: We're wondering if we can become self sustaining right off the bat. I mean, all of our models show a very positive return and that operationally we should be profitable in the short term. But at the same time, it's ironic because I harp on scalability all the time. And I tend to think that potentially like to scale this in the right way, we will need some additional capital. And we were introduced to some people that I believe in the right fit in that regard. I've worked for other VC and other PE groups that were really tough and outside of the sphere of diagnosis and diagnostics, which cause some friction because they want you to adopt the way that they do things in their industry that don't necessarily work or they might even be illegal in the diagnostic area. But we've been paired with a couple groups where one actually represents a population that has a really high rate of rare disease so they're personally motivated as well. and it's a group of clinicians that run this VC group and so far those kind of conversations have been really, really eye opening and fruitful. David Filby: That's awesome. And so final question for you, Raymond, what's the milestones and future plans that we should be on the lookout for and to watch Sagacity's progress? Raymond Tarr: Yeah, personally, you're gonna see people really leveraging this. This is gonna become a commonplace, you know. PathfindEHR is gonna be part of the Lexicon when talking diagnosis and diagnosing patients. The amount of education that can occur through this is phenomenal. The tools are all there. We're using data that's there, pre-existing systems that are already there. The scalability here is immense. We have experience not just in the US, but also ex US. So, you know, we've worked in Saudi Arabia, the UK, you know, Singapore, like other countries as well. And, it's amazing. The sky is really the limit here on that side of it. You'll see us going through, I'm sure, a clinical trial in the short term. That part is up and coming. We're already in the process of you know, interviewing some of the regulatory folks and things like that to have our plan in place. Once that happens, you know, we've already been accepted into the AWS startup sphere. So that has been tremendous. We've also been accepted into NVIDIA's startup program. And we are now an Epic vendor as well. So, those are all huge milestones for such a small little company like ours. But you know, we just keep moving forward. So at some point what you'll see is you know, we will start expanding as well. So you'll start to see employees being hired, sales teams being deployed, technical teams being deployed. So, you know, really the growth here is gonna be pretty exceptional in the short term. David Filby: That's awesome. Raymond, genuinely I think it's a really exciting addition to the industry, regardless of what angle you look at it from. Whether you're a patient, whether you're a clinician, whether you're pharma whether you're a diagnostics company, I think it's something that and I think it goes back to the point that ultimately anything that increases awareness and adoption. We should be super excited about it. But it's so much more than that, it's so much more robust. And I think that that's that's really exciting. Raymond, thank you for coming on and sharing the story behind it, but also, you know, in depth the purpose of the tool and how it works. I genuinely think it's something that the industry should be really excited about. So thank you for coming on and sharing that. Raymond Tarr: Yeah, I appreciate the offer to jump on and share this with everyone. I always appreciate your, interest and curiosity and I think that that's where everything should start. So I appreciate your time as well, David.