About this Webinar:

Komodo Health captures 15 million patient encounters with the healthcare system daily to provide a real-time picture of patients and their various encounters. With this canonical view of US healthcare, we can begin to understand the patient populations at each stage and severity of disease, leading to better guidance of treatment development and outcomes.

• Establish the ground truth of US health care to accurately track longitudinal patient journeys

• Examine provider networks, equitability issues and disparities in access to novel therapies

• Leverage AI/ML for predictive modeling of rare diseases to drive early detection, testing, and adoption of treatments

• Applications of real-world data for evidence generation, accelerating clinical trials, and decision making

Webinar transcript:

00:04 Speaker 1: Welcome back, everybody to MASS East day three. We are very excited to bring you our next speaker. Komodo Health will be presenting on their, 'Improving Lives by Harnessing the Power of Patient Journey with Complete Encounters'. So, for today's presentation, we have Aswin Chandrakantan. He's the chief medical officer and the senior vice president of corporate development at Komodo Health. So, prior to Komodo Health, he was a senior leader with Google's global operations and strategy group, where he was responsible for the implementation of Google's ad products. He has in-depth experience in healthcare and analytics, and previously worked at McKinsey, who produces some of my favorite white papers on medical affairs. He was... Led pay reform in over a dozen states, revenue cycle management at top IBNs, and also has led strategic initiatives for polio eradication strategies in Nigeria. And with that, I'll turn it over. We're very excited for your presentation.

01:09 Aswin Chandrakantan: Alright. Thank you. Good morning, everyone. Super-excited to chat today from Komodo Health. I wanted to chat with the team around how we can improve lives today by harnessing the power of complete patient data. Just briefly about myself, given that I had that warm introduction already. I'm the chief medical officer at Komodo Health. I also, in the early days of Komodo, had a product, where I built our products and our platforms. Spent a lot of time in healthcare analytics at McKenzie, as well as a lot of product-facing work at Google, on their ad tech side. Today's agenda, so I wanted to talk through a little bit around shifting paradigms. So first is talking about medical engagement, and so the way things were and the sort of status quo that's begun to be disrupted over the last three to five years, and there's some focus on the events of the last six months, but there's been more seismic shifts. Then, on the right side, talking a little bit more around where these trends are taking us, and how medical affairs teams can be prepared in driving education of their therapies in the market in light of new norms.

02:29 AC: To talk a little bit about where we are as an industry, traditionally, medical affairs, for the past 25 years or so, there's been three ways of approaching provider education. First is there's a very strong emphasis around a bibliometric approach, which is who are the providers and the scientists and the researchers. They're, as I call them, the gray beards that are out at every single conference podium, talking to you about the work that they're doing in a super-narrow cohort. And they're the providers and the scientists and the quote 'KOLs' that everybody knows. But in a world of patient data, where there's both community and academic centers, where there's a lot of disease burden that is oftentimes shifting, you don't know where these patients are, you're trying to understand what severity of disease they have, you're looking to understand the providers and institutions where they see care, these bibliometric approaches are pretty blunt, to be candid. And so I wanna talk first as a megatrend around not only thinking about bibliometrics, but then also the evolution of the approach for medical affairs on a patient-centric, data-focused approach.

03:51 AC: The second is, in the world of COVID, and this is very, very near-term, but I believe it's gonna have longer-term implications for the industry, the norm has been face-to-face interactions. So you're sending out a note, you're saying, "Hey, let's meet at this specific time." You knock on their door. You answer any number of scientific questions that these providers might have. Maybe they're working on an investigator-initiated trial, and so you're starting to think about how to partner with them on that fund. And all of that is becoming virtual.

04:26 AC: So I'm gonna talk to you about virtual trends, not only as they relate to medical affairs, but also as it relates to the practice of medicine in the United States. And the third piece is to talk about what I would describe as being generic approaches around outreach. So you're talking to providers and saying, "Look, we know that you are the leading expert in MS or diffuse B-cell lymphoma in this particular institution. I would love to talk to you about our upcoming therapy." And I think the market largely has understood that, yes, there are a set of top 30 and top 50 folks that that approach absolutely works, but how do you think about the top 1000, the top 2000 that have the most disease burden and that actually require the most education to drive those patients to the best standards of care? And that's where thinking about deep segmentation and profiling to these providers and institutions using data center products can be extremely valuable. So, first, I wanna double-click on this patient-centric approach. So, starting in the upper left, A, there's a lot of data out there, and so the challenge is to say, "Well, how do we understand a patient's journey where they are, the providers and institutions where they see care, the therapies and interventions that they've received, the outcomes that relate to that?"

05:55 AC: And so all of that ties back to being able to anchor on a strong clinical signal to make sure that the population that the medical affairs teams are looking to understand and drive better standards of care around, that you actually know where those providers are that are in those hotbeds, both in the academic as well as the community setting. The second piece is around the scientific signal. So, yes, there's a bibliometric portion to this, but there's also a clinical trial portion to this, where you can now know that a particular provider or a particular institution has been doing clinical trials as well as publishing on a specific therapeutic area or a specific cohort of the population that the medical affairs teams are looking to drive better care standards around.

06:45 AC: Third, network signals, and this is incredibly important. So we're no longer in the world of thinking about, "Hey, let's just talk about breast cancer patients." Now, the cohort specificity is we need to think about metastatic breast cancer patients that have... That are triple receptor-negative, that have failed two lines of therapy. And now, on that specific cohort, you're looking to understand how they may start in a rural town in Missouri and make their way to the University of Saint Louis, how they may start in Idaho and maybe find the right standards of care out in Sacramento, California. And so, understanding how patients, from where they are in their disease journey, and then also understanding how the providers and institutions are interacting in terms of flow is incredibly important in the new world of medical affairs to focus your efforts on where to educate providers, institutions, and reduce disease burden.

07:47 AC: The fourth and final piece is industry signal. So, using Sunshine Act data and Open Payments data, Komodo Health has built proprietary algorithms in software that allow you to, A, slice and dice all the open payments and all the contractual engagements, like speaking, like consulting, and all the advisory boards that these providers sit on, so you can understand what are the existing contractual norms within a specific therapeutic area, understand who's influential, who might be talking on both sides of the house, so who might be providing a mixed message onto the market, we're serving three top 20s already, and so what are they gonna do for a smaller biotech. So that really allows the team to think about who are the fresh faces that can bring a fresh voice to the market.

08:42 AC: We have actually done an analysis on this, looking at the state of Florida, in the context of diabetes, and what we wanted to see was how does medical affairs contractual engagement, based on Sunshine Act data, mirror patient-level disease burden? So, are we... As an example, we know that diabetes is rampant in the... Say, in the south side of Chicago, but how many contractual... How much contractual engagement does the industry actually have with the South Side of Chicago? It's near zero. And so, we believe that there's a strong mismatch, and that's knowable through data, through software and analytics, and then how do we then build an engagement proxy that allows you to understand that mismatch, and then provide a guide point for life sciences, as an industry, to rethink a contractual engagement, and which providers and institutions they need to educate.

09:43 AC: So this slide is a little bit complex, but I'm gonna just walk you through it, left to right. On the left side, you see educational spend of life sciences companies, based on Sunshine Act data, relative to the cost index. On the upper side, you see the educational investment by county in the state of Florida, and this is all related to the diabetic population. And so, what you would expect to see here is a straight diagonal line, running from the left corner to the upper right. And what that would tell you would be that there is a perfect match between the amount of diabetes in the population, for each one of these counties, and the amount of pharmaceutical emphasis on the part of medical affairs teams around building those contractual engagements.

10:37 AC: But what we see here is just a random scatterplot, and this should immediately draw your eye to the fact that there is opportunity. So, on the upper right hand side, we have Miami, where there is a lot of contractual engagement on the part of life sciences companies and medical affairs teams to drive education around the standards of care for the diabetic population. And, on the lower left, there's a number of counties where there's actually a lot of Central Florida, but there's actually not a lot of diabetes there, and as a consequence, there's low pharmaceutical scientific engagement. But everything on the upper left and everything on the lower right should especially concern you.

11:18 AC: So let's take, for example, here, the county of Hillsborough, where there is a relatively low... There's a relatively high amount of patient... Sorry, there's a relatively high amount of patient burden, but there is a relatively low investment, on the part of life sciences companies, to drive the right standards of care. And so, this already highlights for us, using purely open data sets, and Komodo has a number of pair complete and patient journey complete data, but this is using all the data that's purely accessible by you and me today, already shows that life sciences and medical affairs teams are not going where the patients are. And this is imminently discoverable and understandable by looking at this simple analysis, focused on one therapy area, in one state.

12:19 AC: The second point that we talked about is how do we go from a world in which everything was in-person interactions to everything is now telemedicine? And so what this slide is meant to illustrate is that we see... Well, Komodo Health did an analysis, using our healthcare map, so the journey of 320 million patients in the US, which is census-level representation, the providers and institutions where they see care, the therapies and interventions they use to treat those conditions, the outcomes that relate to that, and we simply looked at the cross-section of the COVID phenomenon, and what we see coded as being telemedicine versus not. What's interesting here is, in the pre-COVID world, you'll see they're very light [13:08] ____, and it's super small on each one of these, you'll see that each one of these institutions, and we chose a right... Nice regionally-representative sample, we have this for every single institution in every single provider in the US pre-mapped, and that allows you to see what is the amount uptick of telemedicine, pre and post-COVID. So you'll see here that New York and UCSF probably have the largest jumps in terms of the amount of telemedicine use, but there's also significant jumps on... Both in the southern US around Miami, in the Baylor University Medical Center.

13:47 AC: And so this is illustrative of, A, there's a massive shift towards telemedicine, B, that this change is likely to be somewhat normative, and that you're gonna see an emphasis on telemedicine to reduce the risk of transmission of COVID, at least until the point of where we have a vaccine. And so what do we do between now and something that appears to be, if not months, years away. And so telemedicine closes that gap, and so Komodo can tell you immediately, based on this analysis, which providers and which institutions are doing telemedicine, so still seeing patients. And now you know which providers and institutions that you should focus your education around. It could be anything from oncology all the way to diabetes and hypertension. We have this built for the entire United States. One of the other pieces that we found that was somewhat alarming, and I believe that life sciences has a role to play, is that what you're seeing here is that in chronic care conditions like asthma, you see that there's a shelter in place order, and you saw that this is essentially the percentage of patients that had... The percentage of new patients, and you would also see the amount... You could see the amount of new patients essentially drop. And so it's not that patients are not getting asthma, just they're not being treated for asthma. So, A, there's a massive build up in unrecognized disease burden amongst the population.

15:30 AC: The second piece that we also superimposed here, and especially in New York, you see that, essentially, there are some states that are massively more impacted than others, so there's going to be a massive rebound effect that we're expecting on part of our analysis where, hey, there's all these deferred colonoscopies, there's all these patients that had malaise that might have some sort of lymphoma because they had diffused B-cell lymphoma years ago. There might be all these patients that are having respiratory distress. All of this volume is building up, and the patients are not getting diagnosed, and therefore they're not getting treatment, and so we expect a massive rebound. And the reason why this is important, especially for the medical affairs industry, is, A, when the rebound actually happens, these providers and these systems are gonna be completely overwhelmed, so it's incredibly important to continue your virtual engagement with these providers.

16:33 AC: So in Komodo Health's healthcare map, we have out-of-the-box, can spam-certified, opted-in email addresses for almost the entire provider system, pre-linked to provider profiles, and so that allows you to then reach out to these providers and focus on education around care standards even while COVID is happening. So, I think that's incredibly important because, A, as I showed you on the previous slide, there are still some providers that are seeing patients, and B, when the rebound impact actually happens, there's gonna be a very long multi-month period in which providers and systems are gonna be overwhelmed, and they're not gonna have any time for life sciences engagement. And so it's important that we're providing engagement consistently and also from a... Virtually, in the... Not only in the coming months, but probably in the coming years.

17:37 AC: And so this is just an emphasis around the point that I've been making, which is we see a massive reduction, everything from breast cancer, and I think Reuters as well as New York Times carry this article on part of Komodo, where we publish this analysis, where you see breast cancer and oncology conditions, as well as hemoglobin A1Cs, and mammograms, and cervical cytologies, and PAP smears all getting deferred in the reduction, in terms of the overall percentage of lab tests. And it's just important to recognize that patients are still getting the disease, and it's important that you probably have the opportunity where, right now, providers are likely less burdened, given that they're seeing fewer patients. And now there's actually an opportunity where they have a little bit more headspace to think about the better standards of care. Medical affairs teams need to be able to capitalize on that opportunity. The last piece that I wanted to highlight is thinking about a data-driven approach to engage providers, and so... Well, I wanted to give a case example here. So, right now, we're using Komodo's out-of-the-box software, which is called Aperture.

19:00 AC: We went into a renal cell carcinoma medical affairs team. They bought Aperture. They had a number of existing lists that were outdated, and based on a lot of qualitative factors, and so they were looking to understand, well, where is the disease burden in the market? And how do we map that to opportunity? And how do we immediately start thinking about our medical affairs strategy, around where we're gonna do our field force placement, and how... And which providers and institutions are we gonna engage? So, when you look at the original client roster, it was about a couple of hundred entities, and when you actually look them up in the Komodo dataset, they had clinical scores, which is a measure of influence that we have, built into our algorithms of... Largely in the 70s. So they're important, but there's probably some upside in the opportunity. And the average number of patients that they were seeing a specific therapeutic area, in this case, renal cell carcinoma, was about 50 patients. And on the scientific side, this is an indication of their publication as well as clinical trial activities, and they ranked in at a 74.

20:18 AC: Within 30 days of coming in and starting to use Aperture, they realized that there were about... There was an entire landscape of thousands of providers, so, in this case, 1800 providers that, on average, had a much higher clinical score, so they were seeing more patients that had renal cell carcinoma, they were looking at the referral patterns, and they were... Actually, the providers that were being referred to, both out in the community as well as the academic centers, and they had a number of connections, so the strength of their referral networks was ultra-strong. These were completely ignored or misunderstood by our clients, so it allowed them to reframe both how many field people do they need, and in this case, it was on the order of three to four X of footprint, that they were able to then go and get funding around. Secondly, they were able to, in a very data-driven way, say, "Well, now we understand who and why we're talking to, and rely less on just purely bibliometric or qualitative measures of influence." So, in this case, we got them to a place in which the average clinical score was 93%. And these were the providers that everyone was referring to, so they were clearly influencers in terms of standards of care. And even on the scientific side, we identified a number of providers that they were missing, that were actually, attitudinally, very involved in publications and clinical trials.

21:51 AC: And so massive velocity in terms of adoptions of care standards for this particular renal cell carcinoma team. So, just to close off this particular example, and open the questions up to the audience, bibliometric approaches, while good, need to be mirrored and complemented by this patient-level data, and Komodo has the leading software on this. So, to give you a sense, post-launch and severe asthma, our client subscribed to 12 months of Aperture, they were missing over 500 providers that were crucial to education, they were out there in the community, they're not that scientifically-active, and through de-profiling, they were able to find about 240 new emerging clinical leaders within three months. And the director there was like, "Literally, we've doubled the number of emerging leaders we were engaging because they were focused on the gray beards that are at every conference. And now they were focused on the providers and institutions that had the most disease burden. So it's really important to think about what are the opportunities that are missed when your team is not using a data-centric approach.

23:11 AC: So, just to close off our conversation here and open it up to the audience for questions, A, as clinical practice and data and technology evolve, it's really important that medical teams are starting to think about how do I align my efforts against disease burden. So you saw... In the state of Florida, you saw a massive mismatch between contractual educational commitments with providers versus disease burden. You also saw that on the asthma side in this last case example, alongside a client. The second piece is, is that right now is actually not a time for complacency in terms of medical affairs. This is the time to invest because providers are less burdened now, because they are actually seeing fewer patients through virtual channel, so, A, your engagement needs to be virtual and, B, you need to capitalize on the fact that they have a little bit more headroom before you see the rebound in volume. And third, you need to keep encouraging them to institute the standards of care, especially for at-risk populations, because what you risk here is essentially therapeutic inertia for a period of months or years, and that's extremely... That's a damaging blow for the populations and also for medical affairs teams, whose entire mission is around driving that better care standard.

24:33 AC: And the third piece is that companies like Komodo with out-of-the-box capabilities have... We'll be able to... We're the right partners to help you optimize your impact in this rapidly-reshaping market. So, with that, I'm going to pause, and would love to answer any questions that the audience might have.

24:57 S1: That was great. Thank you so much. I appreciate, specifically, just the idea of, as medical professionals, medical affairs professionals and scientists, really introducing some objectivity to these things that we have done with traditional and certainly less-rigorous methods for years. Our first question comes from Mario. What are your thoughts on reaching out to HCPs, rising KOLs and mid-level HCPs without a bibliometric approach?

25:27 AC: So, I think that is actually... It's a complementary approach. So, first of all, I am not arguing that we should not do bibliometrics, but bibliometrics tends to be a very blunt instrument. So that's the first piece. And so that the blunt instrument needs to be focused by understanding not only how many papers or how many clinical trials is this provider engaged in, but complemented with what is the disease burden in the population? What is the severity of those patients? And how many providers in that particular area are actually sending their patients to that particular provider? And so what you may get is essentially a scientific green light in terms of, oh, this is the greatest therapy in the market, but then you'll see very poor adoption of the therapy. And that's what we're trying to actually avoid, which is if you believe that it's the standard of care, you need to focus on providers that are seeing the highest disease burden so that you can get them to adopt the right care standards.

26:34 S1: Great. The next question comes from Aji, and says, "I assume you are using AI machine learning platforms for gaining clinical, scientific and network signals. Are there any commercially-available AI platforms which companies can use?"

26:52 AC: I mean, in short, I think Komodo is best in class. One of the pieces that I would highlight is, in a world in which you have a... You have narrower and narrower label indications, that requires a cohort specificity that only a company like Komodo Health that has a lot of payer-complete data assets, so we're seeing every encounter for those patients, starting all the way from the time they walked in with malaise, to the fact that they got a PET scan, to the fact that they tested positive for diffuse B-cell lymphoma, all the way through R-CHOP and radiation therapy. And so to be able to string that together and know that you're seeing the specific cohort that you're looking to focus your education around is incredibly important. And Komodo is, essentially, best in class with that. So I think that AI and machine learning has a lot of applications to this question. The thing that I would also say is I came from Google, and Google, everybody always says, "Oh my god, Google has the best AI and machine learning," and that's absolutely true, and that's because they have the best data. And so Komodo Health really focused on building the best, most comprehensive healthcare map, because when you don't have... When you don't know what happened yesterday, you should not be in the business of predicting what to do differently tomorrow.

28:14 S1: Absolutely. Thank you. I think we might have time for just one more question before we move to break, and we have one from Frederico. What use cases for Komodo typically yield the largest or fastest impact for a new pharma client that traditionally has not used data-driven tools? For example, finding potentially-undiagnosed patients or finding HCPs that treat patients but are not being engaged or educated?

28:41 AC: I think it's actually all of those things. Maybe if I were to just classify at high level, it would be around, A, being able to identify providers' and institutions' disease burden, and then focus on educating those providers around the right standard of care. B, it would be medical affairs strategy, which are telling you about the market landscape and being educated around what your competitors are doing in terms of engaging providers and institutions. And so how you develop the right messaging and the right conversation around why your therapies fits into a specific standard of care. And third, I would say, is around field force sizing as well as deep profiling. So the ability to click into any provider in your therapy area and understand how they stack up in terms of clinical and network signals, scientific signals, as well as industry contractual engagements. And all of that gives you a really strong longitudinal view of exactly how to unlock ROI and focus your efforts on the places that could benefit the most.

29:53 S1: That sounds great. Okay. So we do have a bit of a networking break right now, so I just wanted to remind everybody that we have a virtual exhibit hall. One of our other questions that we had received is actually looking for specific examples, and in specific therapeutic areas, and I'm sure Komodo Health would be glad to walk you through that. I have received a demo from them before, and really been impressed when you ask them to filter in for information that's interesting to you in your company. And of course, all the rest of our event sponsors are in the virtual exhibit hall. If you stop by all eight, and save assets from each to your virtual briefcase, you'll be entered into a drawing for $25 each day, in a [30:34] ____ gift card. And also, if you do it every day, you'll be entered in for a complimentary registration to MASS East 2020, when we will, once again, be live. So, that's it for this session. I look forward to seeing each of you at 11:45 for 'Leveraging Technology to Standardize your Medical Grants'. Thanks so much.

30:54 AC: Wonderful, thank you so much for this opportunity.