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FutureHealth Podcast Series

THE COWEN INSIGHT

Cowen explores the convergence of health care, technology, and consumerism and how it changes the way we look at health care at our annual FutureHealth Conference. We bring together thought-leaders, innovators and investors across sectors to get the most up-to-date views on the current landscape.

In conjunction with this year’s conference, our analysts speak with several leaders in the space. We share these conversations in a six-part podcast series.

Episode 1: Welldoc – Anand Iyer, Chief Strategy Officer

Cowen Host: Charles Rhyee, Health Care Services Analyst

Digital therapeutics hold the potential for a new class of drugs with software as the therapeutic agent. In this podcast, we speak with Anand Iyer, Chief Strategy Officer of Welldoc. Mr. Ieyer played a key role in the development of Welldoc’s BlueStar, the first FDA-cleared mobile prescription therapy for adults with type 2 diabetes. 

They discuss the adoption of digital therapeutics, challenges to achieving a successful commercial model, and COVID-19’s impact on consumer and physician readiness to adopt telehealth and digital care.

Press play below to listen to their conversation.

Transcript

Speaker 1:                       Welcome to Cowen Insights, a space that brings leading thinkers together to share insights and ideas shaping the world around us. Join us as we converse with the top minds who are influencing our global sectors.

Charles Rhyee:                Welcome to the Cowen FutureHealth Podcast, [00:00:30] a part of Cowen’s 5th Annual FutureHealth Conference held virtually this year on June 24th and 25th 2020. Over the past five years, the Cowen FutureHealth Conference brought together thought leaders, innovators and investors to discuss how the convergence of healthcare, technology and consumerism, is changing the way we look at health, healthcare and the healthcare system.

                                         My name is Charles Rhyee and I’m Cowen’s healthcare services analyst and one of my areas of focus over the past several years, has been in digital therapeutics, which will have the potential of a new class of drugs and software as the therapeutic agent. And in this episode of [00:01:00] the podcast here to discuss the topic, I’m pleased to have joined me Anand Lyer, Chief Strategy Officer of Welldoc and someone who played a key role in the development of BlueStar, the first FDA cleared mobile prescription therapy for adults with type 2 diabetes. Welcome Anand.

Anand Lyer:                     Good morning, Charles.

Charles Rhyee:                So Anand, why don’t we start with what is Welldoc and what does the company do?

Anand Lyer:                     So Welldoc, we’re a digital health and digital therapeutics company that uses automated AI driven digital software, [00:01:30] to help support both the patient and the provider in the management of their chronic condition. Whilst we started our journey in type 2 diabetes, we’ve expanded to include other forms of diabetes type 1 and soon to be gestational, along with the comorbid conditions of diabetes, namely hypertension, weight management, and heart failure.

                                         And the reason for being for our product, is to A, provide real time coaching for a patient [00:02:00] at the point of care. So that when they enter any parameter, could be a glucose parameter, could be a medication parameter, could be a social determinants of health parameter, what they ate, how they exercised, to provide them real time coaching and feedback at that point of their care, but to secondly provide them with the longitudinal insights, to not just tell them how they did say at the end of the day, end of the week, end of the month, but rather to tell them the correlative insights on how [00:02:30] they did. “Hey, your glucose was high here and here because of this violating meal, or because of the skip medication.” So you have the ability to teach them over time.

                                         We also support what we call clinical decision support for the healthcare provider. And that is, how do you take all the data for a patient and run it through evidence-based algorithms and software and provide to their doctor, their nurse, their certified diabetes educator, a view of A, where they were, say three months ago, [00:03:00] where they are today, what’s changed and what evidence suggests they should do.

                                         And when you provide those two pieces to support the patient and to support the provider, we’ve seen a tremendous shift in hemoglobin A1cs, we’ve seen a tremendous shift in costs that the patient incurs through the healthcare system, and we’ve seen a tremendous engagement on the part of both the provider and the patient. So you’re kind of knocking off that quadruple aim set of objectives. That’s what we do at Welldoc.

Charles Rhyee:                That’s great. [00:03:30] And maybe talk a little bit more about BlueStar in particular, can you talk about the results and outcomes that you’re actually seeing in your patients?

Anand Lyer:                     Yeah, one of the things we decided earlier on was that, did we want to be an app for an app sake or did we actually want to be a something of more clinical value. And in the early days, we worked with University of Maryland in the Department of Epidemiology, Dr. Charlene Quinn, who helped run randomized control studies. These were first in the industry, [00:04:00] nobody had ever done a randomized control study on an app, they typically do RCTs on medical devices and drugs. And we had shown in this randomized control study, on average 2.A1c reduction for patients who used our product.

                                         We’ve replicated that in a third randomized control study that we did in the Province of Ontario, and with over 45 peer reviewed journals and posters, and real world studies. So on average, we see that [00:04:30] hemoglobin A1c shift by two points. What we have also noted Charles is that, the shift is also pronounced in slightly higher when they start with a higher A1c, so there’s a disproportional effect of BlueStar for patients who start with higher A1cs.

                                         We’ve seen for example on average, 60% of our patients who start with an A1c above nine have dropped center an excess of three points just which is very significant. And just compare that to what the FDA requires for a new [00:05:00] drug, a new drug to be cleared by the FDA requires A1c to be dropped in a clinical trial by 0.5. So you’re talking about four to six to 7X what the FDA requires declare a new drug, and so that’s very important.

                                         And lastly, I’ll say that we were very fortunate to work with IBM Watson Health, formerly Truven Analytics, on understanding the economic impacts associated with those types of A1c shifts. And on average, on average, when a patient shifts their A1c by their [00:05:30] two points, it’s about a $3,100 per patient, per year total cost savings for the employer or for the health insurer to support that patient.

                                         And so we’re seeing a large part of those through reductions in acute utilization, emergency room, hospital admission, doctor’s office visits, but also in the supplies and meds that they consume. And of course, the comorbid complications that they have. So you actually see tremendous health outcomes in the numerator and cost outcomes in the denominator.

Charles Rhyee:                [00:06:00] And by that you mean less medication utilization?

Anand Lyer:                     For many patients, yes. And for many patients, you may actually get them to a higher correct dose of their meds. But in doing so, you may have knocked out one or two unnecessary hospitalizations, which is clearly a larger cost than the addition of say, an additional dose of a medication.

Charles Rhyee:                It seems though, I mean three and a half point decrease coming down from nine, [00:06:30] isn’t it right to see that if you drop below, was it five and a half or so, you’re not really considered diabetic? I mean, is it possible to put somebody through to almost provision for reversal?

Anand Lyer:                     So it’s a great question. It’s a great question. No, just the genetics of diabetes, nobody’s figured out that cure just yet. And so the key word here is average. So if a patient who starts on average with an A1c above nine, which can be nine, 10, 11, 12 as high as 18 or 20, [00:07:00] has drops in excess of three points, we typically see in the bell curve, there’s a huge band of patients whose A1cs are between nine and 10 and a half and 11, if you would, and that’s really the band you want to go after, where you’re bringing those people down to goal.

                                         And of course, we’ve seen very significant drops for people whose A1cs are 14, 15, we’ve seen six, seven point drops. And the idea here is that, seven is the goal as [00:07:30] established by the American Diabetes Association. If you have an A1c between six and seven, you’re considered diabetic, but extremely well controlled. Of course if you have an A1c less than six, typically five and a half to six is that pre-diabetic range, and typically less than five and a half means you don’t have diabetes. So I think the net effect is to try to bring these people down to that goal of seven or less than seven and keep them there overtime.

Charles Rhyee:                Touching on that then, how do you guys see this working better [00:08:00] than the status quo? So maybe, it would be helpful to compare what BlueStar does and what Welldoc is doing to, what is the current standard of care though?

Anand Lyer:                     So if I, I’ll personalize it Charles. As many of the folks in the industry know, I’m a type 2 diabetes patient myself, so let’s just use me as the example. I have to manage my glucose, I have a blood glucose meter, I have several of them, one in my car, one at home, one in my bag, et cetera. [00:08:30] And I have to monitor my glucose levels at various times throughout the day, because there’s a different meaning of what it means to wake up, say, with a low blood glucose value versus have a high blood glucose value after a meal, that tells you something about the number of carbohydrates perhaps, that you ate at that meal.

                                         So I have to manage my blood glucose, but at the same time, I have to manage my food intake, I have to manage my exercise, I have to manage my sleep, all of the vectors if you would, that support [00:09:00] diabetes patients overall wellness. And there’s this little thing called life that tends to get in the way every now and then, right? There is no blame. People try to do what they do, but they have the reality of the things that they need to do and they can’t just live their life around their disease. It’s quite the opposite, they almost want to put the disease in the background.

                                         At the same time, I am encouraged to see my doctor four times a year predominantly to measure my A1c, my hemoglobin A1c and it’s measured, the standard of care says, [00:09:30] measure it every three months. And so I diligently try to write down everything in the current standard of care model and take it into my doctor, but what’s the doctor going to do in a five minute office visit? And it’s actually funny Charles, when I go to my doctor’s office here in Maryland, I see other diabetes patients furiously writing down on a napkin in their glucose results from the last three weeks or what they ate, and I don’t remember what happened yesterday, let alone three weeks ago.

                                         And so it’s a little bit of garbage [00:10:00] in and garbage out. And so the standard of care today, whilst the rules we think about it Charles, diabetes is probably one of the best codified diseases, right? There is a rule and a guideline for almost everything. A, American Diabetes Association, the American Association of Diabetes Educators. I mean, it is a well understood, well quantified and well documented disease. And yet, we’re stuck in this current paradigm where people aren’t doing the things that they should and there’s [00:10:30] no way to translate, if you would the data, should they gather it to information, knowledge, action, and therefore outcomes.

                                         So that’s the snapshot of how it’s working today. It’s a little bit of haphazard, and you almost want to turn that equation upside down and say, is there a way technology can actually support both the patient and the provider? So can they stand on technology shoulders and reach higher and can technology help first, [00:11:00] auto sense and grab this data? So you start to think about connected devices, connected blood glucose meters, connected blood pressure, cuffs, weight skills, things like that.

                                         Can we take information from the patient’s existing treatment pathway like their medication regimen from their pharmacy or their lab values from their EHR? Can we bring these in and can we use these values along with their daily inputs, to judiciously provide them coaching that’s scientifically driven, cleared [00:11:30] by the Food and Drug Administration, the FDA. So these are clinically validated feedback that are coming to these patients telling them what to do at that point in time. And then can we provide and use AI driven software to just isolate the things that the provider needs to talk to the patient about?

                                         So rather than me going to my doctor, and he looks at me and says, “Okay, tell me how the last three months has gone?” “I don’t know.” If he sees a high glucose value, he says, “Did you eat too much?” “I [00:12:00] don’t remember.” “Did you skip your med?” “It could have been.” Instead of that kind of wasted time in that scarce five minute visits that I have with my doctor, can you actually look at this report and say, “Hmm, it looks like there’s three things we need to focus on. So by the way, great job here, here, and here, but let’s focus on these items.”

                                         And so you’re actually using data to illuminate the pathway forward to optimize the treatment pathways. And so it’s a stark difference Charles, between the desired vision and certainly what we’re doing at Welldoc, and what status [00:12:30] quo is sitting, if that makes sense.

Charles Rhyee:                As we think more broadly about digital therapeutics themselves, so you were one of the first to get approval. Maybe help our listeners here understand a bit more than, how you’re defining digital therapeutics and let’s compare that because you just made the comparison to the digital health or to just a health app that I might have on my iPhone or a Galaxy phone.

Anand Lyer:                     So if you were to think of the universe of apps and if you were to think [00:13:00] of a Venn diagram is probably the best way to describe this, you have apps, the largest circle. Within apps, you have a subset of those apps called digital health apps. So those that focus on health. They could be tracking your weight, they could be tracking the number of steps that you take. It could be recording symptoms, things like that. And then you have a subset of the digital health circle, which is digital therapeutics.

                                         So what defines that innermost circle? A couple of things, and these things for the interested folks who want to go and check up on it, [00:13:30] Welldoc, along with four other digital therapeutics companies, co-founded what’s known as the Digital Therapeutics Alliance, the DTs Alliance.org is the website. And we did that because we wanted to help the industry understand what rigor is required, around the development and delivery and support and maintenance of this class of product, these digital therapeutics products, that are required.

                                         And [00:14:00] so one requirement we’ve discussed, multiple randomized control studies that actually demonstrate in peer reviewed published journals, that you have an outcome. Second is, clearance by the regulatory authorities as a suitable class of medical device. And again, it’s the judgment of a third party, a non-biased party that says “Yes, your product is safe to use. It doesn’t induce any risk or you’ve sufficiently managed risk in your product. [00:14:30] And we have audited your process to build the product and we’ve established that there’s GMP or good manufacturing processes associated with that.”

                                         Third, it does meet all the cyber security requirements. And you think about cyber here, things like SOC 2 and HITRUST certification and Privacy HIPAA. You think about privacy in a stronger sense in the EU for example, with GDPR, it has to meet these requirements. Fourth, it actually [00:15:00] has to connect back into the clinical workflow and care team. And what’s really distinguishing a digital therapeutic from any digital health or even telehealth Charles? A digital therapeutic solution will connect the patient back to their own health care provider, and that’s important, because there’s a trust factor associated with the patient and the provider.

                                         When you contrast that with telehealth, I could be connected to a telehealth doctor. And when you look at what’s happening with COVID-19 and the fact that [00:15:30] state laws have been relaxed where doctors in Oregon can see a patient in Maryland, I don’t know who this doctor is, they don’t know what my fears, beliefs, struggles are and yet, they’re the ones who I’ve been connected to. So it has to connect with the patient’s own, if you would.

                                         And like that, there’s several criteria that have actually been listed out by the DTx Alliance. Again, the website is DTx Alliance.org. But [00:16:00] really to summarize these, is there’s a higher level of rigor associated with the development, with the testing, with putting it through randomized control studies to show that it actually works, to getting it cleared, and then to supporting it and maintaining it with the proper SLAs and things like that in place, really, that differentiate a digital therapeutic from a digital health or another health app solution.

Charles Rhyee:                So Anand, obviously all that makes sense. And if we think about the [00:16:30] adoption of digital therapeutics then with your product on the market, Pear Therapeutics with their FDA approved solution for substance abuse treatment, the uptake has probably not been as large as I think some people had initially expected and which suggests that there’s a bit of a learning curve here. Can you speak to sort of the challenges and hurdles in commercializing a digital therapeutic. Where are some of the big roadblocks [00:17:00] in getting people to understand sort of what digital therapeutics can really offer?

Anand Lyer:                     So you brought up a couple of great examples Charles. Pear Therapeutics, in fact just yesterday or the day before yesterday, we got the announcement from the FDA that Akili, one of the co-founding members of the Digital Therapeutics Alliance, received their first FDA clearance and congratulations to the entire Akili team for that accomplishment. What we’re learning and what we’ve learned [00:17:30] is that, there is an adoption curve.

                                         And what we’ve learned is that the analogy perhaps Charles is, how do you open a door that has say three keys that have to be simultaneously turned and so what are the keys to success here literally? One is, you have to have a mechanism for payment, and those mechanisms can be many. In one pathway, you can have a mechanism that’s [00:18:00] tied to a prescription, right? So you can think of the dispensation of a digital therapeutic along the lines of an RX. And that’s for example, the pathway that Pear Therapeutics has chosen.

                                         It’s one of the early pathways that we had as well. And since then we’ve broadened to include others, which I’ll talk about in a second. And in that pathway, you have to then ensure that you’re listed on, say a database, that you’re on [00:18:30] someone’s formulary, and that somebody is covering you as a benefit. And just think about the complexity of what’s involved, that means you have to more than likely have an agreement with the PBM, you more than likely have to have the PBM market this to their payers in a favorable position on their formulary, and you then have to have pull through to ensure that not only is it on the shelf, but people are actually buying it off the shelf, so to speak.

                                         So it’s a fairly complex model that is going to [00:19:00] take time because at its core, it requires a doctor today to actually know about the fact that “Hey, I can actually prescribe something that’s not a pill or an injectable, or a topical ointment that the patient can use to help manage their condition. So there’s a great deal of awareness and industry adoption at the grassroots level. That’ll take time to manifest if you would.

                                         At the same time, there are other payment [00:19:30] mechanisms where you can go directly to an enterprise if you have the regulatory clearance as we do, as we both have the RX and OTC clearances for our BlueStar product, that says can you go directly to an enterprise which could be a payer, a self-insured employer, say a large clinic, IDN and things like that, and have a software licensing model, whether it’s a per user, whether it’s a per site, whether it’s a PMPM. There’s so many different models that exist.

                                         And so I think the first thing for commercial success, is you have [00:20:00] to have a business model, that has to be well understood. And once you have the business model, you then have to execute what is known or what we call the digital therapeutics engagement chain, which is, how do you actually target the right patients? And once you’ve targeted them, how do you outreach to them? Do you outreach in person?

                                         So is it in a clinic for example, the doctor says, “Hey, Charles, I think this can help you walk across the hall and my nurse is going to [00:20:30] get you started.” Is it done through an email? Is it done through an SMS campaign, other social media campaign, a letter, posters, things like that? So how do you outreach, and then how do you activate? Is the activation assisted with a human? Is the activation self?

                                         You start to think about some of the things we’re doing with deep link technology where a single link that sent to the patient’s text, message inbox. When they click on that single link, it actually performs multiple functions, not the least of which is [00:21:00] downloading the app, but then pulling all the relevant information and their current labs, first name, last name, et cetera, from the EMR and pre-populating their profile in the digital therapeutics such that you’ve taken friction out of that activity.

                                         So now it’s frictionless activation. And then once you’ve activated, how do you get them to engage? And that’s the billion dollar question that everybody’s asking, right? How do you actually get them to engage and engagement in and of itself, has to be [00:21:30] taken into consideration with the outcomes that are achieved, I’ll tell you why. The last thing a payer would want, is to continue to pay for years for a product that doesn’t improve somebody’s health. But that’s the worst of both worlds. A, they’re paying and B, people aren’t getting healthier.

                                         So what you actually want, is you want engagement in the context of outcomes. And so I think the summary response is, there has to be a business model in place, but then there has to be this value chain, is what we call the engagement [00:22:00] chain, that identifies the right target, that figures out the right mechanism or mechanisms for outreach, for activation, for engagement. And then of course on the back end of that, you have the typical support and report functions.

                                         It’s that collection of things that needs to happen in order to have a successful commercial model. The lessons learned for us and certainly for others in the industry is that, you can’t bet [00:22:30] on just one, you have to have multiple pathways that’ll create success. And I recall a recent panel that I was on with Chris Hogue, who is with Propeller, another one of the co-founding members of the Digital Therapeutics Alliance.

                                         And there was a very interesting comment that Chris made, which is, “We’re on the fourth iteration of our first business model.” And this was right around the time when they were acquired [00:23:00] by ResMed. And just think of what he just said, right? “We’re on the fourth iteration of our first business model,” which means there’s a learning and there’s an adaptive nature of this. It’s almost like you’re doing it in sprints if I were to use the software development analogy.

                                         And so I think it’s important for people to realize that there may not just be one pathway for success, there could be multiple pathways for success that may differ as you sell to different customer [00:23:30] types, as you sell in different geographies, et cetera.

Charles Rhyee:                No, that makes a lot of sense, and I think that example you talked about, the fourth iteration of the first business model, it speaks to having to adapt to all the other parties involved, right? You talked earlier in the RS model, that you have to engage with potentially payers, PBMs, physicians. How much of this do you think then is [00:24:00] an education process particularly, let’s say providers, and I use that because when you think about a lot of the digital therapeutic companies that are coming, let’s talk about Akili for example as well and Pear.

                                         A lot of you are walking down a path, you’d look into, in some ways mimic the traditional drug that is prescribed by a provider. And in this case though, pharma companies have obviously big market machines and [00:24:30] traditional means of marketing drugs to physicians, obviously used to be in person, maybe more detailing now. What is the challenge then for a new class of therapeutics that physicians just aren’t familiar with. What’s that going to look like and how do you overcome that?

Anand Lyer:                     So if the provider is a part of your go to market model, which in digital therapeutics, the likelihood of that is fairly high, there’s many answers to that. [00:25:00] So one is, do you directly reach out to the providers, i.e, to a certain effect, you become a pharma like company, where you have a direct salesforce that’s calling on and detailing if that’s the right word, physicians, right? Instead of putting samples of drugs on their shelf, you’re putting sample codes of digital therapeutic solutions.

                                         So the analogy is actually quite powerful and it’s literally the same as you become a Merck or a Pfizer or a GSK. [00:25:30] And that’s a very, very resource capital intensive process, as you can imagine, but one that actually goes straight to the grassroots. At the same time, can you partner with a pharmaceutical company that may actually then leverage a part of its sales distribution force to actually do that for you.

                                         So you start to look at the likes of some of the digital therapeutics partnerships in the industry, along the lines of click and sign a fee, or what formerly was [00:26:00] Sandoz and Pear with the intent of, if you would leverage that field force to actually get. So the digital therapeutics companies has a multiplier effect, because they’re using somebody else’s resources to get if you would, to those individuals.

                                         And then you have of course, professional organizations that you can work with. The American Medical Association, the American Association of Clinical Endocrinologists, in our case for diabetes, et cetera. [00:26:30] So there are pathways where you can go through a middleman if you would, you can go through a third party that then brings if you would scale, just really what we’re after here is, how do you actually drive scalability?

                                         And so you’re leveraging a third party’s presence to reach out in a cost effective, scalable way, each of these providers, either that’s kind of one answer. There’s another answer that says, over time, [00:27:00] we’re just going to see inevitability of a physician’s ability to either know that the digital therapeutic solution exists in a certain disease domain, and that there’s a certain familiarity and trust associated with the use of a digital therapeutic.

                                         So I’ll be a little general here, Charles. But when you think about it, we’re now in 2020. The iPhone was first introduced in 2007 if memory serves me correct, [00:27:30] and your first generation of iPhone kids, are going to be going to college in the next five years. And arguably, within the next five to eight years, you’re going to see the first generation of medical school entrance, who are iPhone generation users. And do you think that they’re not going to expect that there’s a digital solution component to the delivery of healthcare in the science of medicine? Of course, they will, because digital has pervaded every [00:28:00] other aspects of their life, why not medicine?

                                         And so when you step back at it and look at it that way, I use the word inevitability because I do believe, we’re not going to call it digital health or digital therapeutics five years from now, we’re just going to call it health and therapeutics, and the digital will have to be an implicit and inherent component of it.

                                         And if not, you won’t be a player, which is why you see whether it’s a payer, whether it’s a pharmaceutical company, whether it’s an IDN, [00:28:30] whether it’s a self-insured employer, everybody wants to pilot and try and learn, how do we incorporate a digital aspect of our care solutions? How do we incorporate digital into that fundamental fabric of delivering care? That’s something that they’re all interested in.

                                         I think, going forward, we won’t use this, it’s the same way nobody calls it e-banking anymore, right? They just call it banking, they’ve dropped the prefix. I think we’ll see the same effect. And so I think there’s different ways to get to the provider direct, [00:29:00] and then there’s the second pathway that says it’s just going to happen, and it’ll happen organically in the next five to eight years.

Charles Rhyee:                That’s great. I want to ask you, COVID 19 obviously, is impacting us all right now and the environment is very fluid in some ways. But one of the outcomes of all of this has been really not only quick reaction lesson from the regulators, but a really quick reaction for the market [00:29:30] to sort of embrace virtual care, particularly, let’s say telehealth is the big example. We’ve seen huge upsurge in the use of telehealth. Two questions really, how to interpret the surgeon utilization. And in particular, what does that say about consumer and/or provider readiness to embrace digital? And then the second question is, what do you think that this means for the progress of digital therapeutics itself?

Anand Lyer:                     So COVID-19, has actually uncovered [00:30:00] so many structural flaws in our healthcare system. And in fact, in our societal system at large Charles. I live here in Maryland, and I have a 10th grader. And when kids were sent home from school, we were thinking great, open up a couple of Zoom windows, and get teachers to jump on and lecture in real time and call it a day. [00:30:30] And very quickly, you learn of the socio economic disparities within even well to do counties, where not every child has access to either high speed internet access, or an appropriate laptop that allows them to conduct a WebEx Zoom like encounter.

                                         And you’re like, “Huh, I didn’t expect that. Okay, well, we better get laptops to every child, and we better ensure that everybody has high speed internet access, because [00:31:00] otherwise it’s not going to work.” So now, all of a sudden, doctor’s offices are empty, because those primary care doctors who may not have been deemed essential emergency if you would, think about a doctor’s office in COVID-19, where they’re not providing emergency services and they’ve told their patients not to come or they’ve been instructed to tell their patients not to come unless it’s an emergency.

                                         So by and large, you have empty doctors offices. And overnight, [00:31:30] they too in a fee-for-service model, need to see patients, that’s the only way they’re going to make money. And so they embrace immediately the Zoom like platforms, and they pay specific attention to some of these emergent telemedicine codes. And overnight, what we’ve seen, is that there’s just a huge influx of telemedicine calls.

                                         My wife’s a dermatologist, [00:32:00] and literally within a week, she had shifted almost her entire practice over to telemedicine calls. And when you think about that effect, even post COVID-19, after COVID-19, the decay curve has gone away and hopefully it’ll go away soon, the convenience associated with a tele visit, the inherent interruption [00:32:30] factor if you would to a family, who has to take their child for a follow up visit, that interruption factor is so much less.

                                         It’s so much easier to just do it over a tele consult, and I think there’s going to be a large part of telemedicine that just persists beyond this first tale of COVID-19. Now, interstage left into this discussion, chronic diseases and digital therapeutics. So was it just day before yesterday, perhaps that the CDC issued a new report [00:33:00] that said of the COVID-19 patients tested in the US, 30% of them had diabetes. 30% Charles, that’s two and a half times the incidence of diabetes in the United States.

                                         So there’s a disproportional effect of COVID-19 on those with diabetes, and it’s well known. The news covers this every day that you’re at more risk, you’re more vulnerable if you have an underlying condition like congestive [00:33:30] heart failure, diabetes, asthma, et cetera. And in the case of COVID-19, where you can’t see your doctor, you can’t interact with your doctor, the ability to have a digital therapeutic solution that actually allows you to have that continuity of care with your health care provider, not just any healthcare provider, is critical.

                                         And so I think the silver lining, if that’s the right way to say it of COVID-19 as it relates to digital therapeutics, is not only did it create [00:34:00] an uptick and surge in the number of telehealth consults and tele visits and telehealth in general, it’ll also create an uptick in demand for digital therapeutic solutions, because these solutions will be logical extensions of healthcare providers treatment pathway for a patient, in a manner that’s trusted, safe, secure, proven, all the things that we spoke of earlier on.

Charles Rhyee:                Yeah, that’s really interesting. And your thoughts here, [00:34:30] are you seeing that maybe then in demand for the BlueStar platform as the discussions with potential enterprise clients? Has this event changed the way their conversations have shifted with you?

Anand Lyer:                     We are Charles. We’re seeing an uptick in not just users, so enterprise customers and users, but we’re also seeing an uptick in usage. So just as an interesting tidbit, [00:35:00] I asked some of our data team, “Can you show me anything different in the months of March and April 2020?” The peak COVID time when the shutdown was occurring and people were quarantining at home. “Can you show me any difference in pattern of engagement?” And what we saw was about a 22% uptick in engagement, compared with engagement from say, the same people during the course of the six months prior.

                                         So there was a [00:35:30] market, 22% increase in engagement, and we dug underneath the covers to see what that uptick was, and primarily a couple of functions. One was, how they manage their activity and their glucose. One was certainly their food management, which is a huge one, and one was the measurement of glucose itself. And so what we saw that people were actually going to the app more, because it was a trusted source for them to actually help make smart food choices, ensure [00:36:00] that they’re exercising in a while they were quarantining at home. And so I think we did see that effect, and I think we’ll continue to see that effect, even post COVID-19 when the curve has decayed.

Charles Rhyee:                That’s interesting. And when you look at that cohort of patients, even as let’s say, states have opened up, are you able to maybe track some of those members? If they’re in a state that has opened up, let’s say, around Memorial Day, three weeks ago. Do you find that those numbers are still engaged or is that your expectation, [00:36:30] at least?

Anand Lyer:                     It’s our expectation, Charles, and I think that’s going to be part of what our journey is in the coming weeks and months is how do we actually look on a week by week basis and try to effect and correlate if you would, whether it’s with zip codes and counties, whether it’s correlating to people on different medication regimens, so more complex insulin regimens versus say more oral, simple, Metformin, Januvia like regimens, whether it’s a correlation between age groups, whether it’s a correlation [00:37:00] to, whether these people are heavy engagors in food management or activity management or sleep management.

                                         I think the correlative insights we’ll gain in the coming months, will teach us a lot about going back to that digital therapeutics engagement chain, how to target the right person with the right messaging at the right instance, and we’ll learn so much. It becomes in a way, a data driven strategy.

                                         You’ll actually use the data that you have, [00:37:30] to actually articulate and sharpen pencils on where to target patients, how to target and onboard patients, what features to promote to them, because you’ll have data that actually suggests that in a statistically significant way. And so I think the next several months for all of the digital therapeutics, companies are going to be critical to start to understand some of those data patterns.

Charles Rhyee:                So now then, maybe one last big picture question for you here then, [00:38:00] as you think about the opportunities that are before not only just Welldoc and Digital Therapeutics, but overall, as we see increasingly a greater shift to use digital tools. And obviously, COVID has opened I think the eyes of many people on the potential here, what do you think the biggest opportunities to improve healthcare are? The sort of big age and how important do you think the digital will be as a part of that?

Anand Lyer:                     [00:38:30] So I think digital will be a part of it to the earlier comment, we won’t call it digital therapeutics or digital health, we’ll just call it health. And inherently there’ll be some component of it, which is delivered over a digital medium. I think the future trend is going to be one that is going to be very data driven. So we will use data, even from say the first 30 or 60 days of patient engagement, to actually hone in [00:39:00] on an exact therapeutic pathway that makes sense at the unequals one level.

                                         So we’ll use, say data initially at a population level that will gather to then understand trends, patterns as it relates to the population, but we’ll zero in on cohorts and individuals to understand the patterns that are right for patient A versus patient B. And so I think what we’ll see, is not only a further embracing [00:39:30] of digital therapeutics and digital health going forward, but we’ll see the role of data, shine even more in its ability to actually hone in and provide the best therapeutic pathway for a physician and patient pair to help optimize their condition, bend their outcomes, curves and vendor clusters.

                                         So I think the role of data, will improve and it’ll improve almost quadratically, why? We’re collecting data at an amazing [00:40:00] rate. We’ll just think about how I’m collecting glucose data and activity data and medication data and sleep data, food data, et cetera. And to be able to harness the value. We speak of those, you’ve heard it before Charles, the 5 V’s of data. So just think about the variety of data we’re capturing. Think about the velocity by which it’s coming in, very high. Think about the variety of data that we’re capturing, thinking about the veracity. [00:40:30] These things are coming directly from sensors and whatnot, the trust is high. And then lastly, the value.

                                         So I think in many ways, these 5 V’s, paint an amazing picture of potential of what digital therapeutics will do that are data driven, illuminated by data insights if you would. I think that’s going to be a really important thing to watch out for going forward for all domains of disease for all classes of digital therapeutics, the data will help illuminate some of the most [00:41:00] interesting pathways forward for the adoption of these things in society.

Charles Rhyee:                Well, that’s I think all the time we have, and really, thank you Anand for joining us today. That was a really moving discussion and it was really exciting to see a lot of what’s coming down in the future and we look forward to hopefully speak with you again on the topic, as we see the world progresses as well as we see how the industry progresses.

Anand Lyer:                     Thanks, Charles and thanks Cowen for the participation and look forward to doing this again in the future.

Charles Rhyee:                Great, thank you.

Speaker 1:                       Thanks for joining us. Stay [00:41:30] tuned for the next episode of Cowen Insights.

Episode 2: Click Therapeutics – David Klein, Co-Founder and CEO

Cowen Host: Charles Rhyee, Health Care Services Analyst

In this episode, we continue the discussion around digital therapeutics with David Klein, Co-Founder and CEO of Click Therapeutics. Click Therapeutics develops software for mobile phones that uses cognitive and neurobehavioral mechanisms for medical treatment. 

They discuss partnerships, the effect of regulators and payer reimbursement on the market, and paths to commercialization.

Press play below to listen to their conversation.

Transcript

Speaker 1:                         Welcome to Cowen Insights, a space that brings leading thinkers together to share insights and ideas, shaping the world around us. Join us as we converse with the top minds who are influencing our global sectors.

Charles Rhyee:                Welcome to the Cowen FutureHealth Podcast. A part of Cowen’s [00:00:30] 5th Annual FutureHealth Conference held virtually this year on June 24th and 25th, 2020. Over the past five years, the Cowen FutureHealth Conference has brought together thought leaders, innovators, and investors to discuss how the convergence of healthcare technology and consumerism is changing the way we look at health, healthcare and the health care system. My name is Charles Rhyee and I’m Cowen’s healthcare services analyst. And in this episode, we talk about data. The explosion of data in the digital age has changed just about how we do everything. And the same is true in healthcare. The biopharma industry, which has [00:01:00] always valued and sought out new forms of data has increasingly started looking outside the controlled environment of clinical trials, to find data from the real world. While newer form of real world evidence is everyday behavior data. And to help us explore this topic, I’m joined by Deborah Kilpatrick, CEO of Evidation Health, a new kind of health and measurement company that focuses on capturing and measuring everyday behavior data, which is proven to be an exceptionally powerful lens on health. Welcome Deb.

Deborah Kilpatr…:          Good morning from California, Charles. Thanks for having me.

Charles Rhyee:                Great. Thanks for being here. Why [00:01:30] don’t we start out with a little of your background and how you found yourself at Evidation?

Deborah Kilpatr…:          Sure. My background is, I like to say I’m a researcher and a true technology nerd at heart. I did my PhD in mechanical engineering with a focus in bioengineering and ended up in California after that and was really very, very focused initially my career in the med tech sector, did a lot of work in the implantables space, drug delivery [00:02:00] devices. I worked at Guidant Corporation for about a decade and ended up helping to run the internal incubator for the vascular business. At the time we were acquired by Boston Scientific and Abbott. And at that time I was very, very interested in information that was coming on new to the scene in healthcare, which at the time was genomics. So I did a stint in a Kleiner Perkins genomics company for awhile and really tried to understand how are the business model of how new [00:02:30] information can fundamentally change diagnosis and therapy and ultimately patient management.

                                         Come 2014. I was really thinking about what would be next. And I met the co-founder and president Evidation Christine Lemke, whose background is about as orthogonal for mine as you could get. She came from the tech sector from big data before big data was cool. She started her career at Microsoft X-Box and we really had a common vision for measurement of health that [00:03:00] would rely on direct connections to people, permission to data and using “Everyday data, data streams,” really to measure health and disease very differently. And here we are six years later still doing it together. So we’re super excited.

Charles Rhyee:                That’s exciting. And you just touched on it a little bit right there. Tell us more about Evidation itself and what does Evidation do here?

Deborah Kilpatr…:          Charles, I like to say that Evidation measures health in everyday life. And when we do that, [00:03:30] it’s in direct contrast to how we’ve always measured health, which is stuck in the brick and mortar walls of the clinic setting. We also are doing that by enabling everyone to participate in groundbreaking research and programs that involve or yield that measurement. We do this by directly connecting to them in their daily lives and this trusted privacy and permission safe way, which I’m sure we’ll talk about. And we partner with the world’s leading healthcare [00:04:00] companies in this relationship to understanding health and disease, to help them better understand and measure in a really quantifiable way. Who’s benefiting from the products that they’re putting on the market and how are they benefiting? When are they benefiting, what populations are benefiting more than others?

                                         We’ve learned along the way that research participation is actually a major activator for people on their own health journey. And so longer term, we believe that this fundamental [00:04:30] phase of business of understanding how to better measure health through very decentralized broad research, that actually is a process that can bring people individualized, proactive and accessible health to their own lives faster. And at any scale. The key for us is that we have to have an underlying evidence generation engine that is involving everybody, everywhere anytime. And that’s what Evidation is all about.

Charles Rhyee:                You talked about how [00:05:00] patients and direct connection with patients and being trusted and the fact that patients are active participants in this. Can you talk about the importance of that distinction?

Deborah Kilpatr…:          Yeah, we took an early stance on privacy in terms of consent and reconsent for data use of permission to data streams. That’s a lot of P words in there. Privacy safe, being fundamental, [00:05:30] a lot of discussion about that, but I think what people are not talking enough about is the permissioning of data, not just for collection, but for use and reuse over time. That’s something that I like to think of Evidation in terms of our approach as having been one of the pioneers of honestly, in terms of how to actually make it real. This is incredibly important in an era where data can be streaming and is streaming all the time. It means that there are an infinite [00:06:00] number of data slices that can be pulled from different points in time, over different points in time, in different periods of time for use, for reuse, for analysis, for re-analysis, essentially on an ongoing basis.

                                         And for people that are participating in the Evidation ecosystem, I want them to know that that permission is not just going to be a one-time thing. We’re going to be asking them to repermission data streams for use and reuse and analysis and reuse [00:06:30] the different studies perhaps ongoing, it gives them a chance to have greater than just one time participation, but it also gives them the trust that, “You know what? We’re going to ask them. We’re going to ask you what you want done with your data.” And if any one point in time you don’t want to participate or you want to drop out or withdraw consent from that particular program of study, it’s simple to do. And it’s our job to make sure that it’s simple for them to do on demand in the context of their participation. It’s up to them.

Charles Rhyee:                That’s interesting that you talk about. So [00:07:00] it’s almost like a different type of re-engagement or constant engagement with your members. And mentioned earlier about research participation being a big activator in their engagement with their own health. And if their data, if it was just one time, they might’ve just forgotten about it. But the fact that you keep coming back to them because somebody else wants to look at it in a different way, keeps them continuously engaged with their health.

Deborah Kilpatr…:          That’s a really fascinating concept. I haven’t quite thought about a metric of engagement [00:07:30] on the basis of that, Charles, but yes, I 100% agree with you. And I think that a lot of the discussion in the ecosystem is rightfully so about privacy and consent, but I still believe that most of that discussion is just focusing on the collection of data and this idea that you and I are discussing right now, this idea that there can be a difference between the point in time of collection and the point time of use for analysis especially in a world where the data [00:08:00] streams never end, it’s fundamental. And we’re pretty vocal about this. We’ve taken a really strong stance on this. We’ve spoken at the Department of Health and Human Services about this. And it’s something that not just can be done or it’s something that should be done. This is the architecture systems this way, this is doable. And I think that for individuals participating in their health as part of a bigger population participating in health, we should demand this. [00:08:30] It’s okay to demand it.

Charles Rhyee:                Yeah, absolutely. Maybe let’s talk about where are you getting data from, you talk about getting members on there directly involved. Maybe talk a little bit about how you actually get the data, where is it coming from?

Deborah Kilpatr…:          Sure. I like to first start by saying there’s the foundation of the people that we’re connected to right now, we’re connected close to 4 million Americans from all 50 states in about [00:09:00] nine out of 10 zip codes. So we are everywhere. We’re connected to people that are everywhere. At any one point in time, those people are turning on data streams through our product called Achievement and the Achievement platform we like to say the portal by which you can have the world’s largest virtual site for research, and you can go to the iOS or Android app store. You can see Achievement as powered by Evidation. You can directly connect to us [00:09:30] through Achievement, and you will see how you can turn on or turn off or leave off individual data streams. Those data streams are from different types of wearables, whether it’s your smartwatch or your phone or different trialed mobile apps on your watch, your phone, or it can also be from connected devices like in your home, whether it’s like a Bluetooth scale or even a clinical grade APIs and devices like continuous glucose meters and monitors.

                                         So there are many different types of flowing data, but for us, the common denominator is [00:10:00] it’s permissioned and turn on or off by the person themselves through Achievement in the products that are associated with human.

Charles Rhyee:                That’s great. It sounds still intuitive when you say it like that, it’s interesting. Activity trackers, they’ve been around for awhile Bluetooth scales, et cetera. We’ve had things like personal health records for years. I guess two questions, why do you think pharma never really thought about this before, and then maybe secondly, [00:10:30] and when did it become apparent to you that this data was clinically relevant?

Deborah Kilpatr…:          I think if we broaden it to say, when did the industry sector of healthcare start thinking about the idea that data would be flowing all the time? I like to say it’s the first time that somebody had a remote monitor bedside controller for their pacemaker. And by the way, that was in 2005. So that was 15 years ago. And that was in the med tech sector. Pharma is different. [00:11:00] Pharma needed the consumer world to come into it’s own for the purposes of allowing people to have information or data flow in their consumer life that they could make relevant to the measurement of health for pharma, because pharma doesn’t make devices that are in use, pharma makes pills or pharma makes biotech injectables.

                                         So I think there’s a fundamental difference between the way the med tech sector is thought about it and the way the pharma sectors thought about it. I like to say that these data streams they’ve always been [00:11:30] clinically relevant, but it took industry of another type to make them clinically useful. And that’s why we created this company. Why is it hard? Look, these are really complex, continuously flowing large-scale data streams. They’re messy, they’re pan frequency, they’re in “Free living conditions.” Everybody makes them differently. They’re not coming from one company. It’s hard. That’s why it’s hard. [00:12:00] I think that it’s not that pharma hadn’t known in my experience that this type of new types of information would be relevant. It’s that, unless you’re an expert in how to deal with the underlying technology part of this, or the underlying data science part of this, that’s not your business.

                                         And so I’m not going to be able to make biotech injectables or pills. It’s not my business. And I certainly would defer all expertise of that part of what Evidation does to our partners. [00:12:30] And I hope that likewise, our partners are trusting us for the parts that they are not experts in, which is the management, the ingestion and management and making sense of this very complex real world everyday flowing data that we’re now finding has so much utility.

Charles Rhyee:                Yeah. And then that makes a lot of sense. I guess one question that I would ask here is what is differentiated about the way the [00:13:00] achievement platform works versus if we think about everyone uses the words big data and clearly if you look at some very large companies out there in the traditional tech world, you would intuitively naturally think that that’s something they could do as well. What is it about Achievement that really differentiates it and makes it really purpose-built here for healthcare?

Deborah Kilpatr…:          The data platform that is the central core for the technology engine, you know what? All of the achievers [00:13:30] and their data streams and their permission and consented data as part of trials is where it’s all going? It’s going into this data of platform core of Evidation. That data platform is custom built and custom developed to leak these very, very messy data streams we’ve been discussing to relevant measures of health, even traditional health outcomes. And so much like when the human genome was unleashed upon the world, there were many, many [00:14:00] what we would now think of as data platform companies, but they were called that back then that needed to really leak these biological pathways which were linked to the fundamental genome, elements of the genome with relevant pathways of disease and how disease actually happen.

                                         And so there was a whole area of computation in data science that was born on the basis of that. This is no different in many ways. There’s a whole new world of linking these types of data streams to [00:14:30] relevant measures of health, to relevant measures of disease status. And in many ways, it’s very analogous to what happened during post-human genome. And so I think we’re very much in the phase now where the computational platforms are built. The data is being ingested in lo and behold we’re beginning to see a lot of things that link together, and a lot of what we think of as computed feature libraries that underlie the actual algorithms or products that result or insights that result like [00:15:00] those things are being built. And they’re being built at a remarkable pace because the sampling frequency here is so fast, it’s instantaneous.

                                         It’s the second that someone turns on and permissions data streams, we’re now sampling. That’s never been possible before in healthcare. The sample always required you to go to a doctor or go get a blood test taken et cetera, et cetera. And so we’re just in a very different world where a lot of the underlying computational concepts are very similar, but the material [00:15:30] and the sampling frequency of that material that will drive the signal are just orders of magnitude faster to acquire and make sense of.

Charles Rhyee:                Yeah. And to your point. And now at a point where it can be useful to pharma versus knowing that it was, but not knowing how to get to it.

Deborah Kilpatr…:          Correct.

Charles Rhyee:                Yeah. And I do want to talk about your partnerships. You have some great ones out there but maybe before jump into it, maybe touch briefly, tell us how the business model then works here for Evidation when you work [00:16:00] with your pharma partners?

Deborah Kilpatr…:          The business model for Evidation is very much a B2B software and technology enabled service model. We’re really focused on the world’s most innovative global healthcare companies in the pharma and med tech sectors. And we also focus on the tech sector, where partners in that sector are really focused on putting their platforms into a healthcare context and understanding how they’re affecting and measurably [00:16:30] affecting health and disease. Those sectors for us are maniacal focus. We’ve worked really hard to attain triple digit year over year growth, across many commercial metrics over the last few years, while focusing largely on the farm and tech sectors. We work with nearly all of the top 10 global pharma companies today. And our goal is to be working with a significant majority of the top 50 by the end of 2022.

                                         You’ll also see us making [00:17:00] announcements about international activity and growth later this year. So we feel like Evidation is having a moment, digital health is having a moment, healthcare in general, I hope is having a moment where we’re seeing things that have been talked about for a long time, actually come into real clinical practice in our case, real evidence, generation practice at a scale that we really could hardly imagine before. It’s really exciting, really exciting time right now.

Charles Rhyee:                Yeah. That sounds pretty amazing. And touching on [00:17:30] working with many of the top global pharma companies in the world, I can easily name off a bunch, a couple that come to mind, Santa Fe, J&J, Eli Lilly, these are great partners of yours. How do you see them, or when they come to you with question, what are some of the questions they’re trying to answer in their work process?

Deborah Kilpatr…:          Yeah. I’ll first say we’re really thrilled to be working with [00:18:00] the likes of these companies, I’ve been in healthcare for my entire career. And so it’s really gratifying to be able to partner with these globally impactful companies as Evidation as a 200 person company. I like to say that I believe they’re trying to better understand the lived experience of human disease in real life and how their products can help individuals, period. Pragmatically, they’re trying to understand who benefits [00:18:30] from those products and how much they benefit. If I look back across programs and use cases over the last two to three years, we see really high concentration in therapeutic areas like central nervous system, neurodegenerative conditions, chronic respiratory diseases and cardiometabolic diseases.

                                         There’s a long tail on the therapeutic areas in Evidation’s work, but those are examples where we see a lot of focus. Coming into it’s own, on the horizon we’re doing a lot more work in oncology. We see [00:19:00] a lot working in oncology, coming on the horizon, especially in the area of survivorship, quantifying the lived experience and being cancer survivors, which now is something that we couldn’t have even dreamt about 20 years ago, having large populations of people living decades after their oncology event. And I like to think of it like these are all situations where objective quantitative measurement of status is poor period. Or these are conditions for patients don’t usually [00:19:30] experience the condition within clinic walls so much as this is just a part of their daily lives. It should be measured there.

                                         Those are where we really, really, really thrive. And the trick is then back to the earlier point of why it’s so hard, now you’re in free-living conditions where things are not controlled and you’re dealing with very large scale data streams in often very large heterogeneous populations. So the power of scale is your friend because [00:20:00] you can tolerate more noise and more messiness in those situations, but I am excited about the breadth of the therapeutic areas that we’re working in, because what that signals to me is that what we’re doing at Evidation and what companies out there in this space are doing are horizontally applicable, we’re not talking about just isolated applicability for one disease or another, we’re talking about a really horizontal applicability to how healthcare [00:20:30] is measured across the board. And that’s really exciting to me into the people on my team.

Charles Rhyee:                Yeah. And I can imagine it’s an easy way to understand how you’ve experienced the growth that you have so far. And when you think about trying to get into, let’s say be part of the top 50 biopharma companies in the world, when I look at the list of your partners today a lot of them are easy to understand. They’re generally known as some of the more progressive pharma companies out there [00:21:00] at the cutting edge of things. Sometimes there’s a perception, particularly, maybe in pharma, some of them are a little bit more conservative. Are you finding those walls falling pretty quickly at this point?

Deborah Kilpatr…:          Well, I think having been on the side of very heavily regulated med tech sector part of the industry, I understand why companies are conservative. I lived that, I really do. I mean, part of the conservatism and conservative stance I think is coming also [00:21:30] from cues from regulatory receptivity. And so I think it’s helpful to look at what the FDA has been signaling or saying in this area as a surrogate measure for how fast the top 50 will come around and not just the top 10. And as I look at it, I think the FDA has been quite vocal about let’s say first real-world evidence and it’s role in regulatory decision-making moving forward. And it’s not new that stakeholders in [00:22:00] D.C. at the FDA and beyond for years have an amplifying their call to action for more patients in our trials in general.

                                         And so I think that our approach where patient generator health data from the everyday lives of people really sits at the intersection of those two tailwinds and in those two megatrends. I think that this is inevitably going to be an important component of the evidence generation scenario for [00:22:30] real world evidence and ultimately regulatory decision-making. First in the post-market setting around label expansion, but I think it’s going to have a role certainly in clinical development. If you look at the crowdsource library of digital end points that curated by the digital medicine society, and you can find their website pretty easily through a Google Search, you’ll notice that there’s not hundreds in that crowd source library of digital end points that are being used in regulatory [00:23:00] grade studies or regulatories in multiple studies, but it soon will be.

                                         And the phase of clinical development or research they’re being used in is all over the board. Some of them are phase IIA, some of them are phase three, some of them are phase IV. And I think that the regulatory purposes that they’re reportedly being used for are also quite broad. And so I look at all of these things as signals in the ecosystem of the importance of this new data source and making sense of this new data source [00:23:30] in the measurement of health. And it’s just a matter of time before, again, it’s not just horizontal across therapeutic areas, it’s horizontal across all sectors of the pharma channel.

Charles Rhyee:                That’s helpful. And I get what your point is obviously pharma has to be careful in taking their cues from the FDA and you make a good point that the agency has been very vocal and in support of digital health in general, I would imagine, I think, was it something from CDRH earlier this week, and it made a vocal support for digital therapeutics. [00:24:00] And I imagine in general, these cues are positive signals for pharma to push further for them faster. Maybe it gets more of them on board?

Deborah Kilpatr…:          Oh, you bet they are. And let’s not forget that before Evidation, does any work with any of these large companies, these very heavily regulated companies, they’re coming in and they’re extensively looking under the hood at everything at Evidation, whether it’s audits for regulatory and quality system compliance, [00:24:30] audits for cybersecurity and privacy safe handling of data, or whether it’s audits for good clinical practice and the way that we conduct our research. You can bet that they’re ensuring compliance and appropriate measurements of those types of concerns for their own needs beyond just needing to vet us. And so I welcome that, it’s something that we’ve been prepared for from day one at Evidation. We’re routinely [00:25:00] going through audits because new audits for us mean new customers. And so we’re probably one of the few companies in the world that gets excited to audits.

Charles Rhyee:                You might be. Putting a lot of this together, particularly as we talk about patients being engaged in their own health, being at the center of a new way for a pharma to push forward. I think a great example of maybe seeing the synthesis is the Apple Heart Watch Study that [00:25:30] I guess now about a year and change ago, and all the signs there was interesting. I remember hosting another panel where one of the and this guy, he’s a researcher and he runs clinical trials down at Duke and he said, “It would take us months to even get a few 100 patients and hear applicants what 100 and something thousand people in a short period of time.” Is that poster child for what the [00:26:00] future could be?

Deborah Kilpatr…:          I mean, I think it is, and I’m biased because I’m making the Kool-Aid not just asking people to drink it, but I believe that we are looking at snapshots of the future when we look at the Heartline trial, when we look at the Apple Heart Study that’s been done and the other efforts that was going on. I feel very strongly that this is not just a flash in the pan. This is a [00:26:30] glimpse into how things are going to be done on a regular basis. I mean, just during the flu season, Evidation has been very active in government grants in flu and now in COVID, but we’re also very active in the antiviral space, working with our pharma and biotech partners during the flu season and measurement of prediction and measurement of different infectious disease patterns and responses to vaccine interventions and responses to therapy in those populations.

                                         When you stand back from [00:27:00] that, you quickly realize that these are not 500 person trials, they are tens of thousands into the hundreds of thousands, and they need to be able to be done anywhere, anytime quickly. And in fact, our recent announcements about our work in COVID, you can see that as being it’s representative of the ability to go anywhere, anytime and steady to these very big, broad population problems. And [00:27:30] so when I say that looking at things like the Heartline trial or the other studies have been done at that scale, I don’t see a day where we’re going to go back to accepting subsets of 1,000 people when you can go out and get 100,000 and get a better answer.

                                         And so I think that we are now at the phase where we have to start looking beyond just the population scale and answering the call to making sure that those populations also [00:28:00] are appropriately representative of the population in this case, the United States. Such that we’re matching socioeconomic differentiation, we’re matching racial and ethnicity differentiation. We’re not just looking at population scale, which was the fundamental problem in the first order. We’re tackling that now we’ve got to go one step further. And so I think that’s the next thing that you’ll start to see is you’ll really start to see technology enabling better representation in these very large scale studies, which could also [00:28:30] not have been contemplated probably even five years ago without imagining how we were going to solve the 10,000 person problem or 100,000 problem.

Charles Rhyee:                Yeah, I can imagine. You mentioned COVID and I do want to get to that in a second here, but just getting back to when we talk about these populations scale studies but, why do you think it was so successful this Apple Watch Study in getting people to sign up versus the traditional clinical trial enrollment process?

Deborah Kilpatr…:          Yeah. I mean, [00:29:00] I don’t mean to oversimplify it, but when you show up to individuals in their daily lives and bring them something to do, versus asking them to come into an ecosystem that does not feel much like their daily lives at all, you’d be amazed at what can get done. And so when we’re showing up to people in a mode of interaction and interactability that they’re used to having in their daily lives, which is with their phones and their watches and the other things in their IOT world as a consumer, [00:29:30] as a person living their life and saying, “You know what, we’re just going to now integrate one additional layer of context and activity around research into that fabric.” That’s very, very different than the inverse of that. And I’m not at all faulting brick and mortar clinical trials.

                                         My Lord, I spent more than half of my career in health care involved in them. But I think that we now are at a time where we have to look at which portion of clinical research [00:30:00] really has to be stuck in brick and mortar for good reason and needs to be handled there versus what parts of the research journey can be actually done virtually in a de-centralized way, in a way that’s very centered around the person and the devices and the technologies and the applications that they’re used to using in their lives. That’s the way we get inclusivity, that’s the way we get differentiation of populations for participate in research. And because back [00:30:30] to my earlier point, we believe so strongly Evidation that research is an activator for people on their health journey. It’s essential that we think about it that way where we’ve got to bring an ecosystem to everybody, not ask everybody to come into one. That’s just just really populated across the country.

Charles Rhyee:                Yeah, that makes a lot of sense and obviously maybe more important than ever given the world we live in with COVID and you had mentioned it just earlier. You talked about the work you [00:31:00] did in flu, but clearly over the last few months, we’ve all been dealing with this pandemic. You’ve made some interesting announcements over the last month, a month and a half, working with a couple of different groups here, maybe talk about some of the work you’re doing here with COVID and how Evidation is uniquely positioned to help in this?

Deborah Kilpatr…:          Sure. I think Charles you’re probably referring to an announcement that we made in May about a collaboration with the New York City [00:31:30] Department of Health and Mental Hygiene in conjunction also with Mount Sinai’s School of Medicine in New York. And so part of the COVID fight is a battle against mental health and the mental health impacts of the entire situation from suffering in quarantine with symptoms to just being in quarantine or being in a sheltering in place situation and isolated from your regular life and your regular interaction with the rest of humanity. And so the New York City Department [00:32:00] of Health and Mental Hygiene and Evidation sought to launch a nationwide study that seeks to understand and uncover COVID-19 symptoms and the mental health impact of the pandemic, looked at very holistically. And so at Mount Sinai School of Medicine was also involved in the design of this so that we’re making sure we’re considering the caregiver aspect of this and the healthcare system aspect of this.

                                         And so we call it our COVID-19 Experience Study capital E [00:32:30] capital S. And it’s going to collect self-reported symptoms and healthcare interactions, as well as movement, data, sleep data, heart rate data from permissioned data strings from health trackers in smartphones. It’s going to involve tens of thousands of individuals across the entire country. And I like to come back down to what are we trying to do? What are we trying to help with? We’re trying to help in this case, the City of New York in particular with better measurement and understanding of the anxiety, the grief and the strain that this [00:33:00] pandemic is causing and continues to cause so they can provide the right support for people throughout the five boroughs. If we can help them do that, then I’m very confident that we have a role to play in helping do this across the U.S. with the same kind of information. So we’re really proud to partner with the City of New York and Mount Sinai on this.

Charles Rhyee:                Any idea when we might be able to see some of the data coming out of this, how long is this study going on [00:33:30] for? And what’s the time period?

Deborah Kilpatr…:          Well, this is going to go on for some time because we need to be able to capture the full, people talk about the wave and the curve, so we’re capturing data throughout the wave and the curve. Even if they’re in, especially including if there is more than one. One of the things you can do is if you go to evidation.com, you’ll see what’s called the COVID-19 Pulse. And COVID-19 Pulse is a series of insights and data releases from our own studies of [00:34:00] the pandemic and our own observational registry data capture over time in different populations across the U.S. For those particular types of insights, you can get those on a fairly regular basis. And if you go to our website or even our Twitter stream, you can see where we’ve released those over time, where we’re reporting on nationwide and geographic specific changes in for example, activity levels.

                                         Well, that’s actually quite important because we know that activity levels signal both are [00:34:30] surrogates of relative states of health, both mentally and physically, but they also are semblances of reflections of disease when you are having symptoms and when you are sick. So something as fundamental as being able to track and measure activity levels continuously as part of the pandemic is actually quite important. And so then there are many other data streams that we’re capturing as part of that, but that’s an example where releasing our own data and our own findings and opening up in a really open source [00:35:00] way, what we’re doing to the rest of the research ecosystem, and asking for partners to come to us and work with us on this. If they’d like to.

Charles Rhyee:                That’s interesting and people should go definitely take a look there. I think a couple of weeks back, you also made an announcement trying to develop an early warning algorithm to detect symptoms of COVID and understand susceptibility to infection. Maybe talk about it. I think you’re working with HHS here and maybe give a little more detail.

Deborah Kilpatr…:          Right. So earlier [00:35:30] in June, we announced a new effort to develop an early warning algorithm to detect symptoms of COVID-19 and understand overall susceptibility in the population to infection. This is being funded in collaboration with BARDA as part of the Department of Health and Human Services and the Bill and Melinda Gates foundation, which we’re also really excited to work with on a number of other things, and are really excited that they’re helping us with this. So this initiative will use different types of novel [00:36:00] behavioral and physiological data to more effectively identify when and where people may contract COVID-19 and when to really enable real-time interventions to limit the spread in the population. So ultimately monitoring safety and efficacy signals of therapeutic strategies and the population on the other side of that as well. So we’re using de-identified data generated by self-reporting and permission data stream from wearables devices, wearables and phones to track symptoms of COVID-19 [00:36:30] and people that are particularly at high risk, especially in including healthcare workers and other first responder groups to try and better understand susceptibility to infection.

                                         And as we said, a major aim is ultimately to develop an early warning algorithm to help individuals better understand and monitor their own symptoms, and then take precautions against the spread. This is building on a lot of the work that we’ve done over the years in flu. That’s also been funded both by DARPA [00:37:00] and BARDA over the years where we really have pioneered the use of looking at large-scale wearables data in large populations, as a means of identifying patterns of infection, as a means of identifying latency periods as visible in the physiologic signals. Prior to someone “Knowing that they’re sick.” That becomes incredibly important because you want to activate vaccination around that person once you sense that happening.

                                         So this is just [00:37:30] work that we’ve been really proud of over the years. It’s very motivating for our employees, even when we were “Just doing it for flu.” But when COVID-19 came along, I saw a lot of employees Evidation just completely jumped to action to try and understand how we could quickly use those learnings and those methodologies in the battle against COVID. And we’re really thrilled that the Gates Foundation and Health and Human Services are working with us on this.

Charles Rhyee:                Yeah, and it seems like [00:38:00] it’s almost like a purpose-built situation for Evidation here. And you mentioned at the start that the period that we’re in now seems, I don’t know if influxion point is the right word, but it’s a moment for digital health. It’s a moment in time for Evidation. Where do you think we go here from here now? Because I don’t want to say the time has come that might be too definitive, but it seems like we [00:38:30] are in a moment here where people are recognizing the benefit and the potential of virtual and digital in healthcare. And certainly the use of telehealth has been a great example of that more directly, but in general it seems like an increasing awareness of it. Your thoughts there?

Deborah Kilpatr…:          I think, if I go way back to Q4 of 2019, which seems like a really long time ago now, [00:39:00] it was already clear based on our own commercial momentum and those of our peers in the real-world evidence space, for example, that pharma’s receptivity to novel data sources and person generated health data for the purposes of understanding product benefit, their receptivity, the doors got blown off of it in 2019, and we really saw that in the market. I think what blew the doors of receptivity often to everyone and everywhere in every part of our lives [00:39:30] was COVID-19. And it’s not just clear to the market that the ability to conduct decentralized evidence generation is important. It’s clear to anyone on the street. I think that it’s important to do that and that de-centralized virtualized health and research being a part of that, it’s not an if anymore, and it’s not even a when, it’s now. They don’t need it five years from now. We [00:40:00] need it now.

                                         The global pandemic battle is involved in this as we just talked about, and I don’t see it going back. We’ve really felt strongly that this should be part of the way that 21st century healthcare works. Nobody knew that it was going to be a critical part of the way that 2020 healthcare works in the battle against a pandemic, but that’s where we are. And speaking as a human I’m thankful, speaking as a patient, I’m ready to participate, and speaking as an [00:40:30] employee at Evidation, I couldn’t be more motivated.

Charles Rhyee:                Yeah, it sounds great. And it sounds amazing what you guys are doing here and maybe just to close out, what’s next for Evidation here? What should listeners look out for from you guys and any milestones we should be looking out for, for more news from you guys?

Deborah Kilpatr…:          We’re very excited to continue making some announcements in the next couple of months about our partnerships [00:41:00] in this space that are going to allow us to have even bigger impact in the real world evidence space and in our work with pharma. And as I mentioned, look you’re going to see us be more than just a U.S. company. You’re going to see us have impact internationally. And you’ll see that sooner than later, and we’ll look forward to making some announcements about that later in the year.

Charles Rhyee:                Great. I’m looking forward to it, certainly. I think we’ll wrap it up here and Deb, as always, thanks so much for joining us, I really enjoyed our discussion today. I [00:41:30] thought it was really interesting. And a lot of the points you brought up make I think hopefully people who listen think about how technology is changing our lives, not in the future, but right now. Thanks again for joining us and hope to have you on again, at some point in the future.

Deborah Kilpatr…:          Thank you, Charles. And I look forward to seeing you and shaking your hand when we do that again.

Charles Rhyee:                Absolutely.

Deborah Kilpatr…:          All right. Take care.

Charles Rhyee:                All right. Take care. Thank you.

Speaker 1:                       Thanks for joining us. Stay tuned for the next episode of Cowen [00:42:00] Insights.

Episode 3: Evidation Health – Deborah Kipatrick, CEO

Cowen Host: Charles Rhyee, Health Care Services Analyst

In this episode, we talk about data. The biopharma industry, which has always valued and sought out new forms of data has increasingly started looking outside the controlled environment of clinical trials to find data from the real world. One newer form of real-world evidence is everyday behavior data.

We’re joined by Deborah Kilpatrick, CEO of Evidation Health to help us explore this topic. Evidation is a new kind of health and measurement company that focuses on capturing and measuring everyday behavior data, which is proving to be an exceptionally powerful lens on health. 

They discuss privacy and permission for use of data streams, partnerships in pharma, medtech and technology, and how Evidation is helping research the impact of and susceptibility to COVID-19.

Press play below to listen to their conversation.

Transcript

Speaker 1:                       Welcome to Cowen Insights, a space that brings leading thinkers together to share insights and ideas, shaping the world around us. Join us as we converse with the top minds who are influencing our global sectors.

Charles Rhyee:                Welcome to the Cowen FutureHealth Podcast. A part of Cowen’s [00:00:30] 5th Annual FutureHealth Conference held virtually this year on June 24th and 25th, 2020. Over the past five years, the Cowen FutureHealth Conference has brought together thought leaders, innovators, and investors to discuss how the convergence of healthcare technology and consumerism is changing the way we look at health, healthcare and the health care system. My name is Charles Rhyee and I’m Cowen’s healthcare services analyst. And in this episode, we talk about data. The explosion of data in the digital age has changed just about how we do everything. And the same is true in healthcare. The biopharma industry, which has [00:01:00] always valued and sought out new forms of data has increasingly started looking outside the controlled environment of clinical trials, to find data from the real world. While newer form of real world evidence is everyday behavior data. And to help us explore this topic, I’m joined by Deborah Kilpatrick, CEO of Evidation Health, a new kind of health and measurement company that focuses on capturing and measuring everyday behavior data, which is proven to be an exceptionally powerful lens on health. Welcome Deb.

Deborah Kilpatr…:          Good morning from California, Charles. Thanks for having me.

Charles Rhyee:                Great. Thanks for being here. Why [00:01:30] don’t we start out with a little of your background and how you found yourself at Evidation?

Deborah Kilpatr…:          Sure. My background is, I like to say I’m a researcher and a true technology nerd at heart. I did my PhD in mechanical engineering with a focus in bioengineering and ended up in California after that and was really very, very focused initially my career in the med tech sector, did a lot of work in the implantables space, drug delivery [00:02:00] devices. I worked at Guidant Corporation for about a decade and ended up helping to run the internal incubator for the vascular business. At the time we were acquired by Boston Scientific and Abbott. And at that time I was very, very interested in information that was coming on new to the scene in healthcare, which at the time was genomics. So I did a stint in a Kleiner Perkins genomics company for awhile and really tried to understand how are the business model of how new [00:02:30] information can fundamentally change diagnosis and therapy and ultimately patient management.

                                         Come 2014. I was really thinking about what would be next. And I met the co-founder and president Evidation Christine Lemke, whose background is about as orthogonal for mine as you could get. She came from the tech sector from big data before big data was cool. She started her career at Microsoft X-Box and we really had a common vision for measurement of health that [00:03:00] would rely on direct connections to people, permission to data and using “Everyday data, data streams,” really to measure health and disease very differently. And here we are six years later still doing it together. So we’re super excited.

Charles Rhyee:                That’s exciting. And you just touched on it a little bit right there. Tell us more about Evidation itself and what does Evidation do here?

Deborah Kilpatr…:          Charles, I like to say that Evidation measures health in everyday life. And when we do that, [00:03:30] it’s in direct contrast to how we’ve always measured health, which is stuck in the brick and mortar walls of the clinic setting. We also are doing that by enabling everyone to participate in groundbreaking research and programs that involve or yield that measurement. We do this by directly connecting to them in their daily lives and this trusted privacy and permission safe way, which I’m sure we’ll talk about. And we partner with the world’s leading healthcare [00:04:00] companies in this relationship to understanding health and disease, to help them better understand and measure in a really quantifiable way. Who’s benefiting from the products that they’re putting on the market and how are they benefiting? When are they benefiting, what populations are benefiting more than others?

                                         We’ve learned along the way that research participation is actually a major activator for people on their own health journey. And so longer term, we believe that this fundamental [00:04:30] phase of business of understanding how to better measure health through very decentralized broad research, that actually is a process that can bring people individualized, proactive and accessible health to their own lives faster. And at any scale. The key for us is that we have to have an underlying evidence generation engine that is involving everybody, everywhere anytime. And that’s what Evidation is all about.

Charles Rhyee:                You talked about how [00:05:00] patients and direct connection with patients and being trusted and the fact that patients are active participants in this. Can you talk about the importance of that distinction?

Deborah Kilpatr…:          Yeah, we took an early stance on privacy in terms of consent and reconsent for data use of permission to data streams. That’s a lot of P words in there. Privacy safe, being fundamental, [00:05:30] a lot of discussion about that, but I think what people are not talking enough about is the permissioning of data, not just for collection, but for use and reuse over time. That’s something that I like to think of Evidation in terms of our approach as having been one of the pioneers of honestly, in terms of how to actually make it real. This is incredibly important in an era where data can be streaming and is streaming all the time. It means that there are an infinite [00:06:00] number of data slices that can be pulled from different points in time, over different points in time, in different periods of time for use, for reuse, for analysis, for re-analysis, essentially on an ongoing basis.

                                         And for people that are participating in the Evidation ecosystem, I want them to know that that permission is not just going to be a one-time thing. We’re going to be asking them to repermission data streams for use and reuse and analysis and reuse [00:06:30] the different studies perhaps ongoing, it gives them a chance to have greater than just one time participation, but it also gives them the trust that, “You know what? We’re going to ask them. We’re going to ask you what you want done with your data.” And if any one point in time you don’t want to participate or you want to drop out or withdraw consent from that particular program of study, it’s simple to do. And it’s our job to make sure that it’s simple for them to do on demand in the context of their participation. It’s up to them.

Charles Rhyee:                That’s interesting that you talk about. So [00:07:00] it’s almost like a different type of re-engagement or constant engagement with your members. And mentioned earlier about research participation being a big activator in their engagement with their own health. And if their data, if it was just one time, they might’ve just forgotten about it. But the fact that you keep coming back to them because somebody else wants to look at it in a different way, keeps them continuously engaged with their health.

Deborah Kilpatr…:          That’s a really fascinating concept. I haven’t quite thought about a metric of engagement [00:07:30] on the basis of that, Charles, but yes, I 100% agree with you. And I think that a lot of the discussion in the ecosystem is rightfully so about privacy and consent, but I still believe that most of that discussion is just focusing on the collection of data and this idea that you and I are discussing right now, this idea that there can be a difference between the point in time of collection and the point time of use for analysis especially in a world where the data [00:08:00] streams never end, it’s fundamental. And we’re pretty vocal about this. We’ve taken a really strong stance on this. We’ve spoken at the Department of Health and Human Services about this. And it’s something that not just can be done or it’s something that should be done. This is the architecture systems this way, this is doable. And I think that for individuals participating in their health as part of a bigger population participating in health, we should demand this. [00:08:30] It’s okay to demand it.

Charles Rhyee:                Yeah, absolutely. Maybe let’s talk about where are you getting data from, you talk about getting members on there directly involved. Maybe talk a little bit about how you actually get the data, where is it coming from?

Deborah Kilpatr…:          Sure. I like to first start by saying there’s the foundation of the people that we’re connected to right now, we’re connected close to 4 million Americans from all 50 states in about [00:09:00] nine out of 10 zip codes. So we are everywhere. We’re connected to people that are everywhere. At any one point in time, those people are turning on data streams through our product called Achievement and the Achievement platform we like to say the portal by which you can have the world’s largest virtual site for research, and you can go to the iOS or Android app store. You can see Achievement as powered by Evidation. You can directly connect to us [00:09:30] through Achievement, and you will see how you can turn on or turn off or leave off individual data streams. Those data streams are from different types of wearables, whether it’s your smartwatch or your phone or different trialed mobile apps on your watch, your phone, or it can also be from connected devices like in your home, whether it’s like a Bluetooth scale or even a clinical grade APIs and devices like continuous glucose meters and monitors.

                                         So there are many different types of flowing data, but for us, the common denominator is [00:10:00] it’s permissioned and turn on or off by the person themselves through Achievement in the products that are associated with human.

Charles Rhyee:                That’s great. It sounds still intuitive when you say it like that, it’s interesting. Activity trackers, they’ve been around for awhile Bluetooth scales, et cetera. We’ve had things like personal health records for years. I guess two questions, why do you think pharma never really thought about this before, and then maybe secondly, [00:10:30] and when did it become apparent to you that this data was clinically relevant?

Deborah Kilpatr…:          I think if we broaden it to say, when did the industry sector of healthcare start thinking about the idea that data would be flowing all the time? I like to say it’s the first time that somebody had a remote monitor bedside controller for their pacemaker. And by the way, that was in 2005. So that was 15 years ago. And that was in the med tech sector. Pharma is different. [00:11:00] Pharma needed the consumer world to come into it’s own for the purposes of allowing people to have information or data flow in their consumer life that they could make relevant to the measurement of health for pharma, because pharma doesn’t make devices that are in use, pharma makes pills or pharma makes biotech injectables.

                                         So I think there’s a fundamental difference between the way the med tech sector is thought about it and the way the pharma sectors thought about it. I like to say that these data streams they’ve always been [00:11:30] clinically relevant, but it took industry of another type to make them clinically useful. And that’s why we created this company. Why is it hard? Look, these are really complex, continuously flowing large-scale data streams. They’re messy, they’re pan frequency, they’re in “Free living conditions.” Everybody makes them differently. They’re not coming from one company. It’s hard. That’s why it’s hard. [00:12:00] I think that it’s not that pharma hadn’t known in my experience that this type of new types of information would be relevant. It’s that, unless you’re an expert in how to deal with the underlying technology part of this, or the underlying data science part of this, that’s not your business.

                                         And so I’m not going to be able to make biotech injectables or pills. It’s not my business. And I certainly would defer all expertise of that part of what Evidation does to our partners. [00:12:30] And I hope that likewise, our partners are trusting us for the parts that they are not experts in, which is the management, the ingestion and management and making sense of this very complex real world everyday flowing data that we’re now finding has so much utility.

Charles Rhyee:                Yeah. And then that makes a lot of sense. I guess one question that I would ask here is what is differentiated about the way the [00:13:00] achievement platform works versus if we think about everyone uses the words big data and clearly if you look at some very large companies out there in the traditional tech world, you would intuitively naturally think that that’s something they could do as well. What is it about Achievement that really differentiates it and makes it really purpose-built here for healthcare?

Deborah Kilpatr…:          The data platform that is the central core for the technology engine, you know what? All of the achievers [00:13:30] and their data streams and their permission and consented data as part of trials is where it’s all going? It’s going into this data of platform core of Evidation. That data platform is custom built and custom developed to leak these very, very messy data streams we’ve been discussing to relevant measures of health, even traditional health outcomes. And so much like when the human genome was unleashed upon the world, there were many, many [00:14:00] what we would now think of as data platform companies, but they were called that back then that needed to really leak these biological pathways which were linked to the fundamental genome, elements of the genome with relevant pathways of disease and how disease actually happen.

                                         And so there was a whole area of computation in data science that was born on the basis of that. This is no different in many ways. There’s a whole new world of linking these types of data streams to [00:14:30] relevant measures of health, to relevant measures of disease status. And in many ways, it’s very analogous to what happened during post-human genome. And so I think we’re very much in the phase now where the computational platforms are built. The data is being ingested in lo and behold we’re beginning to see a lot of things that link together, and a lot of what we think of as computed feature libraries that underlie the actual algorithms or products that result or insights that result like [00:15:00] those things are being built. And they’re being built at a remarkable pace because the sampling frequency here is so fast, it’s instantaneous.

                                         It’s the second that someone turns on and permissions data streams, we’re now sampling. That’s never been possible before in healthcare. The sample always required you to go to a doctor or go get a blood test taken et cetera, et cetera. And so we’re just in a very different world where a lot of the underlying computational concepts are very similar, but the material [00:15:30] and the sampling frequency of that material that will drive the signal are just orders of magnitude faster to acquire and make sense of.

Charles Rhyee:                Yeah. And to your point. And now at a point where it can be useful to pharma versus knowing that it was, but not knowing how to get to it.

Deborah Kilpatr…:          Correct.

Charles Rhyee:                Yeah. And I do want to talk about your partnerships. You have some great ones out there but maybe before jump into it, maybe touch briefly, tell us how the business model then works here for Evidation when you work [00:16:00] with your pharma partners?

Deborah Kilpatr…:          The business model for Evidation is very much a B2B software and technology enabled service model. We’re really focused on the world’s most innovative global healthcare companies in the pharma and med tech sectors. And we also focus on the tech sector, where partners in that sector are really focused on putting their platforms into a healthcare context and understanding how they’re affecting and measurably [00:16:30] affecting health and disease. Those sectors for us are maniacal focus. We’ve worked really hard to attain triple digit year over year growth, across many commercial metrics over the last few years, while focusing largely on the farm and tech sectors. We work with nearly all of the top 10 global pharma companies today. And our goal is to be working with a significant majority of the top 50 by the end of 2022.

                                         You’ll also see us making [00:17:00] announcements about international activity and growth later this year. So we feel like Evidation is having a moment, digital health is having a moment, healthcare in general, I hope is having a moment where we’re seeing things that have been talked about for a long time, actually come into real clinical practice in our case, real evidence, generation practice at a scale that we really could hardly imagine before. It’s really exciting, really exciting time right now.

Charles Rhyee:                Yeah. That sounds pretty amazing. And touching on [00:17:30] working with many of the top global pharma companies in the world, I can easily name off a bunch, a couple that come to mind, Santa Fe, J&J, Eli Lilly, these are great partners of yours. How do you see them, or when they come to you with question, what are some of the questions they’re trying to answer in their work process?

Deborah Kilpatr…:          Yeah. I’ll first say we’re really thrilled to be working with [00:18:00] the likes of these companies, I’ve been in healthcare for my entire career. And so it’s really gratifying to be able to partner with these globally impactful companies as Evidation as a 200 person company. I like to say that I believe they’re trying to better understand the lived experience of human disease in real life and how their products can help individuals, period. Pragmatically, they’re trying to understand who benefits [00:18:30] from those products and how much they benefit. If I look back across programs and use cases over the last two to three years, we see really high concentration in therapeutic areas like central nervous system, neurodegenerative conditions, chronic respiratory diseases and cardiometabolic diseases.

                                         There’s a long tail on the therapeutic areas in Evidation’s work, but those are examples where we see a lot of focus. Coming into it’s own, on the horizon we’re doing a lot more work in oncology. We see [00:19:00] a lot working in oncology, coming on the horizon, especially in the area of survivorship, quantifying the lived experience and being cancer survivors, which now is something that we couldn’t have even dreamt about 20 years ago, having large populations of people living decades after their oncology event. And I like to think of it like these are all situations where objective quantitative measurement of status is poor period. Or these are conditions for patients don’t usually [00:19:30] experience the condition within clinic walls so much as this is just a part of their daily lives. It should be measured there.

                                         Those are where we really, really, really thrive. And the trick is then back to the earlier point of why it’s so hard, now you’re in free-living conditions where things are not controlled and you’re dealing with very large scale data streams in often very large heterogeneous populations. So the power of scale is your friend because [00:20:00] you can tolerate more noise and more messiness in those situations, but I am excited about the breadth of the therapeutic areas that we’re working in, because what that signals to me is that what we’re doing at Evidation and what companies out there in this space are doing are horizontally applicable, we’re not talking about just isolated applicability for one disease or another, we’re talking about a really horizontal applicability to how healthcare [00:20:30] is measured across the board. And that’s really exciting to me into the people on my team.

Charles Rhyee:                Yeah. And I can imagine it’s an easy way to understand how you’ve experienced the growth that you have so far. And when you think about trying to get into, let’s say be part of the top 50 biopharma companies in the world, when I look at the list of your partners today a lot of them are easy to understand. They’re generally known as some of the more progressive pharma companies out there [00:21:00] at the cutting edge of things. Sometimes there’s a perception, particularly, maybe in pharma, some of them are a little bit more conservative. Are you finding those walls falling pretty quickly at this point?

Deborah Kilpatr…:          Well, I think having been on the side of very heavily regulated med tech sector part of the industry, I understand why companies are conservative. I lived that, I really do. I mean, part of the conservatism and conservative stance I think is coming also [00:21:30] from cues from regulatory receptivity. And so I think it’s helpful to look at what the FDA has been signaling or saying in this area as a surrogate measure for how fast the top 50 will come around and not just the top 10. And as I look at it, I think the FDA has been quite vocal about let’s say first real-world evidence and it’s role in regulatory decision-making moving forward. And it’s not new that stakeholders in [00:22:00] D.C. at the FDA and beyond for years have an amplifying their call to action for more patients in our trials in general.

                                         And so I think that our approach where patient generator health data from the everyday lives of people really sits at the intersection of those two tailwinds and in those two megatrends. I think that this is inevitably going to be an important component of the evidence generation scenario for [00:22:30] real world evidence and ultimately regulatory decision-making. First in the post-market setting around label expansion, but I think it’s going to have a role certainly in clinical development. If you look at the crowdsource library of digital end points that curated by the digital medicine society, and you can find their website pretty easily through a Google Search, you’ll notice that there’s not hundreds in that crowd source library of digital end points that are being used in regulatory [00:23:00] grade studies or regulatories in multiple studies, but it soon will be.

                                         And the phase of clinical development or research they’re being used in is all over the board. Some of them are phase IIA, some of them are phase three, some of them are phase IV. And I think that the regulatory purposes that they’re reportedly being used for are also quite broad. And so I look at all of these things as signals in the ecosystem of the importance of this new data source and making sense of this new data source [00:23:30] in the measurement of health. And it’s just a matter of time before, again, it’s not just horizontal across therapeutic areas, it’s horizontal across all sectors of the pharma channel.

Charles Rhyee:                That’s helpful. And I get what your point is obviously pharma has to be careful in taking their cues from the FDA and you make a good point that the agency has been very vocal and in support of digital health in general, I would imagine, I think, was it something from CDRH earlier this week, and it made a vocal support for digital therapeutics. [00:24:00] And I imagine in general, these cues are positive signals for pharma to push further for them faster. Maybe it gets more of them on board?

Deborah Kilpatr…:          Oh, you bet they are. And let’s not forget that before Evidation, does any work with any of these large companies, these very heavily regulated companies, they’re coming in and they’re extensively looking under the hood at everything at Evidation, whether it’s audits for regulatory and quality system compliance, [00:24:30] audits for cybersecurity and privacy safe handling of data, or whether it’s audits for good clinical practice and the way that we conduct our research. You can bet that they’re ensuring compliance and appropriate measurements of those types of concerns for their own needs beyond just needing to vet us. And so I welcome that, it’s something that we’ve been prepared for from day one at Evidation. We’re routinely [00:25:00] going through audits because new audits for us mean new customers. And so we’re probably one of the few companies in the world that gets excited to audits.

Charles Rhyee:                You might be. Putting a lot of this together, particularly as we talk about patients being engaged in their own health, being at the center of a new way for a pharma to push forward. I think a great example of maybe seeing the synthesis is the Apple Heart Watch Study that [00:25:30] I guess now about a year and change ago, and all the signs there was interesting. I remember hosting another panel where one of the and this guy, he’s a researcher and he runs clinical trials down at Duke and he said, “It would take us months to even get a few 100 patients and hear applicants what 100 and something thousand people in a short period of time.” Is that poster child for what the [00:26:00] future could be?

Deborah Kilpatr…:          I mean, I think it is, and I’m biased because I’m making the Kool-Aid not just asking people to drink it, but I believe that we are looking at snapshots of the future when we look at the Heartline trial, when we look at the Apple Heart Study that’s been done and the other efforts that was going on. I feel very strongly that this is not just a flash in the pan. This is a [00:26:30] glimpse into how things are going to be done on a regular basis. I mean, just during the flu season, Evidation has been very active in government grants in flu and now in COVID, but we’re also very active in the antiviral space, working with our pharma and biotech partners during the flu season and measurement of prediction and measurement of different infectious disease patterns and responses to vaccine interventions and responses to therapy in those populations.

                                         When you stand back from [00:27:00] that, you quickly realize that these are not 500 person trials, they are tens of thousands into the hundreds of thousands, and they need to be able to be done anywhere, anytime quickly. And in fact, our recent announcements about our work in COVID, you can see that as being it’s representative of the ability to go anywhere, anytime and steady to these very big, broad population problems. And [00:27:30] so when I say that looking at things like the Heartline trial or the other studies have been done at that scale, I don’t see a day where we’re going to go back to accepting subsets of 1,000 people when you can go out and get 100,000 and get a better answer.

                                         And so I think that we are now at the phase where we have to start looking beyond just the population scale and answering the call to making sure that those populations also [00:28:00] are appropriately representative of the population in this case, the United States. Such that we’re matching socioeconomic differentiation, we’re matching racial and ethnicity differentiation. We’re not just looking at population scale, which was the fundamental problem in the first order. We’re tackling that now we’ve got to go one step further. And so I think that’s the next thing that you’ll start to see is you’ll really start to see technology enabling better representation in these very large scale studies, which could also [00:28:30] not have been contemplated probably even five years ago without imagining how we were going to solve the 10,000 person problem or 100,000 problem.

Charles Rhyee:                Yeah, I can imagine. You mentioned COVID and I do want to get to that in a second here, but just getting back to when we talk about these populations scale studies but, why do you think it was so successful this Apple Watch Study in getting people to sign up versus the traditional clinical trial enrollment process?

Deborah Kilpatr…:          Yeah. I mean, [00:29:00] I don’t mean to oversimplify it, but when you show up to individuals in their daily lives and bring them something to do, versus asking them to come into an ecosystem that does not feel much like their daily lives at all, you’d be amazed at what can get done. And so when we’re showing up to people in a mode of interaction and interactability that they’re used to having in their daily lives, which is with their phones and their watches and the other things in their IOT world as a consumer, [00:29:30] as a person living their life and saying, “You know what, we’re just going to now integrate one additional layer of context and activity around research into that fabric.” That’s very, very different than the inverse of that. And I’m not at all faulting brick and mortar clinical trials.

                                         My Lord, I spent more than half of my career in health care involved in them. But I think that we now are at a time where we have to look at which portion of clinical research [00:30:00] really has to be stuck in brick and mortar for good reason and needs to be handled there versus what parts of the research journey can be actually done virtually in a de-centralized way, in a way that’s very centered around the person and the devices and the technologies and the applications that they’re used to using in their lives. That’s the way we get inclusivity, that’s the way we get differentiation of populations for participate in research. And because back [00:30:30] to my earlier point, we believe so strongly Evidation that research is an activator for people on their health journey. It’s essential that we think about it that way where we’ve got to bring an ecosystem to everybody, not ask everybody to come into one. That’s just just really populated across the country.

Charles Rhyee:                Yeah, that makes a lot of sense and obviously maybe more important than ever given the world we live in with COVID and you had mentioned it just earlier. You talked about the work you [00:31:00] did in flu, but clearly over the last few months, we’ve all been dealing with this pandemic. You’ve made some interesting announcements over the last month, a month and a half, working with a couple of different groups here, maybe talk about some of the work you’re doing here with COVID and how Evidation is uniquely positioned to help in this?

Deborah Kilpatr…:          Sure. I think Charles you’re probably referring to an announcement that we made in May about a collaboration with the New York City [00:31:30] Department of Health and Mental Hygiene in conjunction also with Mount Sinai’s School of Medicine in New York. And so part of the COVID fight is a battle against mental health and the mental health impacts of the entire situation from suffering in quarantine with symptoms to just being in quarantine or being in a sheltering in place situation and isolated from your regular life and your regular interaction with the rest of humanity. And so the New York City Department [00:32:00] of Health and Mental Hygiene and Evidation sought to launch a nationwide study that seeks to understand and uncover COVID-19 symptoms and the mental health impact of the pandemic, looked at very holistically. And so at Mount Sinai School of Medicine was also involved in the design of this so that we’re making sure we’re considering the caregiver aspect of this and the healthcare system aspect of this.

                                         And so we call it our COVID-19 Experience Study capital E [00:32:30] capital S. And it’s going to collect self-reported symptoms and healthcare interactions, as well as movement, data, sleep data, heart rate data from permissioned data strings from health trackers in smartphones. It’s going to involve tens of thousands of individuals across the entire country. And I like to come back down to what are we trying to do? What are we trying to help with? We’re trying to help in this case, the City of New York in particular with better measurement and understanding of the anxiety, the grief and the strain that this [00:33:00] pandemic is causing and continues to cause so they can provide the right support for people throughout the five boroughs. If we can help them do that, then I’m very confident that we have a role to play in helping do this across the U.S. with the same kind of information. So we’re really proud to partner with the City of New York and Mount Sinai on this.

Charles Rhyee:                Any idea when we might be able to see some of the data coming out of this, how long is this study going on [00:33:30] for? And what’s the time period?

Deborah Kilpatr…:          Well, this is going to go on for some time because we need to be able to capture the full, people talk about the wave and the curve, so we’re capturing data throughout the wave and the curve. Even if they’re in, especially including if there is more than one. One of the things you can do is if you go to evidation.com, you’ll see what’s called the COVID-19 Pulse. And COVID-19 Pulse is a series of insights and data releases from our own studies of [00:34:00] the pandemic and our own observational registry data capture over time in different populations across the U.S. For those particular types of insights, you can get those on a fairly regular basis. And if you go to our website or even our Twitter stream, you can see where we’ve released those over time, where we’re reporting on nationwide and geographic specific changes in for example, activity levels.

                                         Well, that’s actually quite important because we know that activity levels signal both are [00:34:30] surrogates of relative states of health, both mentally and physically, but they also are semblances of reflections of disease when you are having symptoms and when you are sick. So something as fundamental as being able to track and measure activity levels continuously as part of the pandemic is actually quite important. And so then there are many other data streams that we’re capturing as part of that, but that’s an example where releasing our own data and our own findings and opening up in a really open source [00:35:00] way, what we’re doing to the rest of the research ecosystem, and asking for partners to come to us and work with us on this. If they’d like to.

Charles Rhyee:                That’s interesting and people should go definitely take a look there. I think a couple of weeks back, you also made an announcement trying to develop an early warning algorithm to detect symptoms of COVID and understand susceptibility to infection. Maybe talk about it. I think you’re working with HHS here and maybe give a little more detail.

Deborah Kilpatr…:          Right. So earlier [00:35:30] in June, we announced a new effort to develop an early warning algorithm to detect symptoms of COVID-19 and understand overall susceptibility in the population to infection. This is being funded in collaboration with BARDA as part of the Department of Health and Human Services and the Bill and Melinda Gates foundation, which we’re also really excited to work with on a number of other things, and are really excited that they’re helping us with this. So this initiative will use different types of novel [00:36:00] behavioral and physiological data to more effectively identify when and where people may contract COVID-19 and when to really enable real-time interventions to limit the spread in the population. So ultimately monitoring safety and efficacy signals of therapeutic strategies and the population on the other side of that as well. So we’re using de-identified data generated by self-reporting and permission data stream from wearables devices, wearables and phones to track symptoms of COVID-19 [00:36:30] and people that are particularly at high risk, especially in including healthcare workers and other first responder groups to try and better understand susceptibility to infection.

                                         And as we said, a major aim is ultimately to develop an early warning algorithm to help individuals better understand and monitor their own symptoms, and then take precautions against the spread. This is building on a lot of the work that we’ve done over the years in flu. That’s also been funded both by DARPA [00:37:00] and BARDA over the years where we really have pioneered the use of looking at large-scale wearables data in large populations, as a means of identifying patterns of infection, as a means of identifying latency periods as visible in the physiologic signals. Prior to someone “Knowing that they’re sick.” That becomes incredibly important because you want to activate vaccination around that person once you sense that happening.

                                         So this is just [00:37:30] work that we’ve been really proud of over the years. It’s very motivating for our employees, even when we were “Just doing it for flu.” But when COVID-19 came along, I saw a lot of employees Evidation just completely jumped to action to try and understand how we could quickly use those learnings and those methodologies in the battle against COVID. And we’re really thrilled that the Gates Foundation and Health and Human Services are working with us on this.

Charles Rhyee:                Yeah, and it seems like [00:38:00] it’s almost like a purpose-built situation for Evidation here. And you mentioned at the start that the period that we’re in now seems, I don’t know if influxion point is the right word, but it’s a moment for digital health. It’s a moment in time for Evidation. Where do you think we go here from here now? Because I don’t want to say the time has come that might be too definitive, but it seems like we [00:38:30] are in a moment here where people are recognizing the benefit and the potential of virtual and digital in healthcare. And certainly the use of telehealth has been a great example of that more directly, but in general it seems like an increasing awareness of it. Your thoughts there?

Deborah Kilpatr…:          I think, if I go way back to Q4 of 2019, which seems like a really long time ago now, [00:39:00] it was already clear based on our own commercial momentum and those of our peers in the real-world evidence space, for example, that pharma’s receptivity to novel data sources and person generated health data for the purposes of understanding product benefit, their receptivity, the doors got blown off of it in 2019, and we really saw that in the market. I think what blew the doors of receptivity often to everyone and everywhere in every part of our lives [00:39:30] was COVID-19. And it’s not just clear to the market that the ability to conduct decentralized evidence generation is important. It’s clear to anyone on the street. I think that it’s important to do that and that de-centralized virtualized health and research being a part of that, it’s not an if anymore, and it’s not even a when, it’s now. They don’t need it five years from now. We [00:40:00] need it now.

                                         The global pandemic battle is involved in this as we just talked about, and I don’t see it going back. We’ve really felt strongly that this should be part of the way that 21st century healthcare works. Nobody knew that it was going to be a critical part of the way that 2020 healthcare works in the battle against a pandemic, but that’s where we are. And speaking as a human I’m thankful, speaking as a patient, I’m ready to participate, and speaking as an [00:40:30] employee at Evidation, I couldn’t be more motivated.

Charles Rhyee:                Yeah, it sounds great. And it sounds amazing what you guys are doing here and maybe just to close out, what’s next for Evidation here? What should listeners look out for from you guys and any milestones we should be looking out for, for more news from you guys?

Deborah Kilpatr…:          We’re very excited to continue making some announcements in the next couple of months about our partnerships [00:41:00] in this space that are going to allow us to have even bigger impact in the real world evidence space and in our work with pharma. And as I mentioned, look you’re going to see us be more than just a U.S. company. You’re going to see us have impact internationally. And you’ll see that sooner than later, and we’ll look forward to making some announcements about that later in the year.

Charles Rhyee:                Great. I’m looking forward to it, certainly. I think we’ll wrap it up here and Deb, as always, thanks so much for joining us, I really enjoyed our discussion today. I [00:41:30] thought it was really interesting. And a lot of the points you brought up make I think hopefully people who listen think about how technology is changing our lives, not in the future, but right now. Thanks again for joining us and hope to have you on again, at some point in the future.

Deborah Kilpatr…:          Thank you, Charles. And I look forward to seeing you and shaking your hand when we do that again.

Charles Rhyee:                Absolutely.

Deborah Kilpatr…:          All right. Take care.

Charles Rhyee:                All right. Take care. Thank you.

Speaker 1:                       Thanks for joining us. Stay tuned for the next episode of Cowen [00:42:00] Insights.

Episode 4: Glooko – Russ Johannesson, CEO

Cowen Host: Ryan Blicker, Life Science & Diagnostic Tools Analyst

Diabetes devices is an industry with exciting long term secular growth. To help us discuss the future of digital diabetes care, we’re joined by Russ Johannesson, CEO of Glooko.

Glooko is a SaaS software for diabetes management, enabling seamless aggregation/management of data from various diabetes devices, and increasingly, providing adjacent services to physicians.

They discuss market opportunity and penetration, evolution of the product offering, the competitive landscape, and how partnerships help with Glooko’s long term vision.

Press play below to listen to their conversation.

Transcript

Speaker 1:                       Welcome to Cowen Insights, a space that brings leading thinkers together to share insights and ideas shaping the world around us. Join us as we converse with the top minds who are influencing our global sectors.

Ryan Booker:                   Welcome to the Cowen Future Health podcast, a part of Cowen’s fifth [00:00:30] annual Future Health conference held virtually this year on June 24th and 25th of 2020. Over the past five years, the Cowen Future Health Conference has brought together thought leaders, innovators, and investors to discuss how the convergence of healthcare technology and consumerism is changing the way we look at healthcare and the healthcare system. My name is Ryan Booker, and I’m an analyst at Cowen covering diabetes devices, an industry with exciting long-term secular growth. In this episode of the podcast, here to discuss the future of digital diabetes [00:01:00] care, I’m pleased to have the CEO of Glooko, Russ Johannesson. Welcome, Russ.

Russ Johannesso…:         Thanks, Ryan. Appreciate you having me.

Ryan Booker:                   Thank you for coming on. Maybe before we jump into the detailed questions, it would be great to start with your background. What was your history prior to joining Glooko and what brought you to join the company in 2018?

Russ Johannesso…:         Sure. Well, I’ve really spent my career at the intersection of healthcare [00:01:30] and consumer engagement. I started out in healthcare consulting, mostly strategy and operations consulting, and then over time moved into technology consulting and digital health roles. The last couple of roles before I came to Glooko included five years as chief operating officer of Sharecare, a digital health business based out of Atlanta. And prior to that, I spent five years as the chief client officer of Optum Health, which is part of UnitedHealth [00:02:00] Group. And there I was running all sales, marketing, client-side operations for that Optum Health business.

                                         I joined Glooko in early 2018 as I was really wanting to spend this next phase of my career working on some of the more important and more challenging issues in healthcare. I wanted a chance to leverage my skills and my experience in growing and scaling businesses. And it really was just was one of those [00:02:30] in the right place at the right time opportunities. I see it and have seen it really as a chance to make a real difference in a huge and growing problem in the industry. Despite the fact that there’s been a lot of money and technology and innovation being thrown at this problem in many ways, it continues to get worse globally by a number of measures. And so really excited to join Glooko a couple of years ago, [00:03:00] and it has not let me down. It’s been quite an exciting ride so far, and I think we’ve got a lot of great potential ahead of us.

Ryan Booker:                   Excellent. Maybe picking up on one of your points on overall care, can you talk a bit about what Glooko brings to the table to improve diabetes care today both from a patient perspective as well as a physician perspective?

Russ Johannesso…:         Sure. Yeah. Glooko really works to simplify [00:03:30] a very complex disease state for patients and for physicians, and a little more recently, even for clinical researchers. There are hundreds of devices, multiple treatment options that range from insulin pumps and connected insulin pens to CGMs and blood glucose meters. From a therapy perspective, there’s insulins, long and short acting, there’s oral medications, and then there’s other lifestyle type therapies where [00:04:00] folks are managing diet and activity and exercise to try to manage the problem. So it’s a complex condition. It’s exacerbated by the fact that it is a chronic and progressive disease, and it really does impact every area of the life of a person with diabetes. And it is often difficult to manage. So we help physicians manage this complexity by being the single, universal, and interoperable [00:04:30] solution that brings all of this data together from all of these devices into one single user interface.

                                         And especially during this time of the COVID-19 pandemic, we’re also able to support diabetes care and clinical research that can be done 100% remotely without patients having to come into a clinic setting in order to be treated or in order to participate in the clinical trial. And so this is [00:05:00] having a lot of impact in the market right now. But overall, our solution has been in play for a number of years, and we’re really the only global, universal, device-agnostic data management solution out there in the market today. And it’s been widely accepted across 26 countries, 15 languages. It is deep in the workflow of these clinical practices and leveraging the connection between that clinical workflow solution and the mobile application [00:05:30] that we offer for free to anyone, and we connect those two to leverage telehealth and remote patient monitoring and the sharing of data, again, outside of a clinic visit if need be.

Ryan Booker:                   Got it. Maybe on that point about being global, the merger of Glooko and Diasend in 2016, I believe put Glooko ahead of any other digital diabetes tool by number of patients and physician offices, certainly at that time. There was a lot of other companies [00:06:00] with high patient numbers, but you clearly have the most scale and penetration within physician offices in the industry. How do you think about your market opportunity? Is increasing penetration of physician offices the primary driver to future growth? And if so, how far along are you within this opportunity today?

Russ Johannesso…:         Yeah. We really see three strategic growth pillars for us going forward. Certainly, one of them, and maybe the most fundamental to support the rest of [00:06:30] our strategies, is this continued focus on aggressively growing and expanding the clinical footprint you just described. Like I said before, we’re currently in 26 countries. We’ll be in more than 30 by the end of the year. But there is still a lot of room for growth. Our footprint today is concentrated in North America and Europe, a little bit in the Middle East, Australia, New Zealand, a little bit in South Africa, but there are very large global regions with a very high prevalence [00:07:00] of diabetes where we have not yet entered. Think all of Latin America, India, China, Japan, major markets with a high prevalence of diabetes where we think we can have a big impact. And those will be part of our growth trajectory over the next couple of years. We’re currently exploring a couple of those markets with partners to enter into those.

                                         So that first pillar around the continued expansion of our clinical footprint also includes deeper penetration within the existing countries that we serve today. [00:07:30] Today, we are penetrated in the US to the extent that we’re in about 65% of the specialty endocrinology clinics in the US. In a couple of countries in Europe, in particular in the UK and Sweden and Norway, we’re in nearly 100% of the specialty clinics in those markets and expanding pretty aggressively into primary care clinics in those markets as well. So we continue to expand that footprint because it really gives us the ability to leverage the value [00:08:00] for the rest of what we do. The second of our growth pillars is really around enabling telehealth. We’ve been offering remote patient monitoring and telehealth solutions for a number of years as is true pretty much globally. The adoption of those solutions has been slower than I think anyone would have liked.

                                         With COVID-19 coming on, actually, the adoption has [00:08:30] accelerated so rapidly literally over the last couple of months. And we do believe that that is more of a paradigm shift that will continue to stay at higher levels going forward. It won’t stay at that level it’s been at these last several weeks, but it will come down to a new normal level, which I think will be much higher than it has been historically. So given the nature of our platform and the fact that we’ve continued to invest in these additional capabilities, it’s put [00:09:00] us in a really strong position to enable telehealth and remote monitoring from a diabetes perspective globally. In many countries, including the US, UK, France, Germany, they’ve really leaned into creating new reimbursement channels for these types of capabilities, which has made it a much different value proposition for providers and health systems. And now, we’re able to be viewed by the market as a way to expand the business side of these health systems and clinics.

                                         We actually have now [00:09:30] the conversation has shifted to our ability to support reimbursement and new revenue streams versus being an expense item for what historically might’ve been viewed more as a data management or workflow efficiency solution. So that enablement of telehealth has really helped boost our business and give us some tailwinds through this.

                                         The third piece of our third growth pillar is really around enabling clinical research. We’ve got over 13,000 [00:10:00] clinical locations around the world, and we have this ready, connected ecosystem of clinics and patients that can help researchers conduct prospective and retrospective clinical research. We’ve seen a big uptick in the interest by CROs and study sponsors, especially since the beginning of the pandemic, as they’re able to run, or in some cases actually rescue trials in a virtual and remote fashion.

                                         We’ve done [00:10:30] clinical research for a number of years. Last year, we started to see a lot more interest, and we spent the time and focus and money to invest in our platform and make it CFR Part 11 compliant so we can do more research. And then with the shift to the need to support research from a virtual perspective happening so quickly between mid-March and today, the demand [00:11:00] for those services has really gone through the roof. So those are really the three key pillars for our growth and our expansion over the next couple of years. It’s expansion of that clinical footprint, it’s the enablement to telehealth, and the enablement of the clinical research side.

Ryan Booker:                   Interesting. Yeah. That’s an interesting point you mentioned on tele-health and the incremental potential revenue streams that could open up over time for the company. Can you talk a bit about how you monetize [00:11:30] across those three pillars today both currently, and how you think about the long-term opportunity?

Russ Johannesso…:         Sure. Historically, we have leveraged a SaaS subscription-based model to our core solution for clinics and health systems. And then a big part of our business has been really a number of different business models, but leveraging strategic partnerships with pharmaceutical companies, medical device companies, et cetera. So we do have several [00:12:00] different revenue streams, including what we’re really leaning into now in support of these types of telehealth solutions is really a per participant per month charge to health systems and clinics and license fees for using our clinical research platform to conduct trials or real-world data studies. The strategic partnerships that we have, in some cases, we private label parts of our solution for pharmaceutical and device companies as well. So it’s [00:12:30] a mixed bag. The piece that has really shifted more recently for us is over the past two years since I’ve been on board, we’ve taken a more enterprise approach to selling at the health system level versus clinic by clinic, and we wrap other services around that, including EHR integrations and digital therapeutics and more advanced analytics and the remote patient monitoring solutions.

                                         And now, with the shift in the opening up of reimbursement in the US and frankly [00:13:00] globally, we’re really being viewed much more, as I said before, as an ability to generate new revenue streams through the reimbursement for CPT codes related to remote data management as well as telehealth visits. And so we’re seeing that per person per month business model really helping to drive that piece, which is overall a better win-win for our alignment with clinics and health systems anyway.

Ryan Booker:                   Interesting. Yes. [00:13:30] It’s fascinating to me how much the product offering has evolved over the past five years. Five years ago, I would’ve thought of Glooko as a company on a mission to liberate the data and remove the friction from all these devices and the friction from downloading that data during patient and physician interactions. Increasingly, you’re moving into other value-added solutions like analytics for providers, the intuitive new insulin dosing tool that you’ve [00:14:00] launched over the, I believe the past year or two. Can you talk a little bit more about the evolution of the product offering and where you see the most opportunity across those different verticals over the next three to five years? What’s the next major area of product innovation from Glooko?

Russ Johannesso…:         Yeah. I think it really does come back to sort of those three pillars we were just talking about. You’re right. Historically, we were viewed as a workflow [00:14:30] efficiency data management solution, and there’s nothing wrong with that. And we were building a great SaaS model business going after that and creating that value. I think what we’ve come to realize, and really where the focus has been, is that that’s a great value and a great benefit, but from a scale perspective, leveraging that large clinic footprint, leveraging the data and the data rights related to that, coming out of that and putting it to higher value uses is really where [00:15:00] the real value is going to be driven over the next few years. So as we look out the next couple of years, we’re going to continue to invest in the platform and in clinical decision support and digital therapeutics, you had mentioned our insulin dosing tool.

                                         We did create an FDA Class II cleared digital therapeutic called MIDS. Stands for Mobile Insulin Dosing System. And it’s really an algorithm [00:15:30] to support clinicians in onboarding Type 2 patients to basal insulin. Very effective way. Again, leveraging really remote patient monitoring and telehealth solutions, looking at the data in between visits to help get them titrated on their basal insulin as they onboard very quickly. It keeps them in range, gets them in range very quickly, avoids hyper and hypo events. It’s just a much more effective and better health outcome using that.

                                         We’ve also used our platform, continue to use it, to allow other [00:16:00] digital therapeutics and algorithms to essentially ride on the chassis of our platform into the clinical footprint so that we can create this treatment hub and allow clinicians and care teams to select the best options for their patient population in terms of digital therapeutics and algorithms. We’re not going to create them all. We’ve got a partnership with a company called [Driamed 00:16:21] who’s got a Type 1 algorithm for insulin pump setting adjustments in between visits as well. Also leveraging that same remote patient [00:16:30] monitoring technology.

                                         In addition, we’re going to continue to invest in our capabilities around enabling telehealth and remote patient monitoring. We aren’t looking to create a unique standalone tele-health solution where we cover everything from end to end, including the support for a video conference between a patient and a provider. We really want to enable all of the telehealth platforms and all of the remote care platforms that are [00:17:00] out there regardless of what the mode of communications you’re using. We are the data management solution underneath that that allows that data to be shared remotely by a patient from their insulin pump, their CGM, or BGM their activity data, everything else shared with a physician either asynchronously, or they can share it remotely from home, or they can share it as part of a real-time visit that’s happening.

                                         In addition, we will continue [00:17:30] to invest in our ability to support clinical research similar to our tele-health approach. We’re not looking to be a competitive CRO. We’re actually the data acquisition, in some cases, patient recruitment mechanism to get patients for really all kinds of metabolic studies, engaged remotely if need be, but also in-clinic, because we do have the solution from a clinical footprint in a wide number of countries and the amount of patients running through the platform. So that’s really where we’re going to continue [00:18:00] to innovate and drive the solution going forward. And in many ways, it’s about the connectivity between patients and providers, and it’s about the data that gets generated through those to be able to leverage those for decision support, for population health analytics, for business intelligence purposes as well.

Ryan Booker:                   On that point for decision support, you talked about internationally moving beyond specialty endocrinologist [00:18:30] clinics and moving into primary care. Is that an opportunity in the United States over time as well? And along those lines, do you see an opportunity to provide medication recommendations for the broader Type 2 patient population prior to initiating long-acting insulin?

Russ Johannesso…:         Sure. We do. And today we have a good portion of our patient population is Type 2. [00:19:00] It’s not just a Type 1 population. And as you know, more and more, the growth is really heavy in the Type 2 population. If you think about the spectrum of diabetes, our value proposition definitely resonates the most and is strongest at the most intensive end of that spectrum, which would be certainly the Type 1 patient. And a lot of data generated there leveraging myriad of devices there, but also on the insulin-dependent end of the Type [00:19:30] 2 spectrum. Clearly, that’s another one that we see a lot of usage of our solution and our product. Much of that care at that end of the spectrum is happening in primary care clinics. And we think, for example, in the US, we’re in roughly 30% of the primary care clinics, especially the big ones that treat a lot of people with diabetes.

                                         Our mobile solution actually does have value for anyone with diabetes, even if they’re not on insulin therapy. The ability to just track and manage your [00:20:00] blood glucose levels, look at the data and insights that we push around the intersection of the data points that come in through the combination of your carb intake, your activity tracking, your medication adherence, even if it’s oral medication and not insulin therapies, the ability to look at that data, to look at it retrospectively, look at trends in those different data sets is really valuable to anyone who’s managing their blood glucose levels on a somewhat regular basis. So we do see that piece of [00:20:30] it.

                                         And again, our value proposition resonates the most at that more intensive end, and frankly more expensive from a medical expense end of the spectrum, but there is value that gets [inaudible 00:20:42] in the earlier stages. We’re working today in creating some educational components to our platform. We’re working on something with the NHS in the UK right now, starting first with education of healthcare providers. And the second phase of that will be education of patients. So [00:21:00] once that educational content component starts to get in there as well, that will also be something that helps us span and bridge into earlier stages of Type 2 diagnosis for diabetes as well.

Ryan Booker:                   Interesting. Yeah. Maybe along those lines, just thinking about continuous glucose monitoring, CGM use today and where that’s going over time, specifically within non-intensive Type 2 [00:21:30] patients, do you believe that over the next five to 10 years, the vast majority of those patients are going to be using CGM in some form or fashion, and does having that incremental CGM data maybe provide more of an opportunity for you to add value on the decision support side for physicians?

Russ Johannesso…:         Yeah, absolutely. And I do think that the increase in CGM usage will continue to happen. I think it will continue to [00:22:00] proliferate in the Type 2 population as well. Likely not Type 2 patients wearing a CGM full-time, but maybe more periodically for a couple of weeks at a time to get some consistent data for review by their physician, but not necessarily wearing them all the time. But I think that will continue to happen, especially as the price point and the feature function [00:22:30] set around CGMs, the price point comes down, I think we’ll continue to see that proliferating. And it does have an impact for us. In one very tangible way, the volume of data that gets generated and created when you shift from traditional leverage of a blood glucose meter to measure a few times a day to getting readings every five minutes has really driven just the size of our [00:23:00] real-world evidence database exponentially.

                                         I mean, we’re at 20 billion data points and growing all the time because there was so much data coming through. And it does create a different view and the ability for clinicians to have a much, I think, sharper view of what they can do to manage this complex condition. And it does allow you to start to look at data that can measure what’s happening in your everyday life, [00:23:30] and then align that with what is happening in your episodic delivery of care world as well and marrying that episodic and every day so that you can find out what’s really driving the condition. It’s a complex condition. In many ways, it works differently for different people. And really, the more data that you have, and you can align that with everyday activity data, et cetera, you can really get a good sense of what it takes to manage for any individual patient going forward. So we do think that’s going to happen. We think it will continue to [00:24:00] proliferate. And we think creating more value and I think more precision around managing outcomes for patients.

Ryan Booker:                   Fascinating. Maybe moving to competition. How do you think about competition long-term? In our conversations with investors, I think people frequently compare you to other chronic disease management vendors, although I think of you a bit differently as a lot of those companies, [00:24:30] like the Livongos, Omadas, Onduos of the world are often outside of the traditional care infrastructure, while Glooko is directly integrated with physicians. Who do you think of as your primary competitors? And would you include the device vendors who are also on your platform, but also are increasingly investing in their own software offerings over time, such as Dexcom with its CLARITY software?

Russ Johannesso…:         Yeah. I think it’s a great question. It’s one that we get all the time, and I think [00:25:00] you’ve hit it on the head that it’s a space that is frequently misunderstood. Because of our deep integration into the workflow of the physician practices and in the patient’s day-to-day management of their disease, we do have a different position in the whole cardio-metabolic digital health space. We view those other companies that you had mentioned, the Livongos, the Omadas, the Onduos, [00:25:30] we’re very supportive. This is a big problem, a big complex problem, and I think none of us individually are going to be able to solve it. We view our solution, frankly, as quite complementary to what those solutions are delivering. They’re very focused on helping equip patients to do better self-management. To your point, not really connected back into the clinical delivery system.

                                         We think it’s very important to be able to do both of those [00:26:00] things. And the more interoperability, the more connectivity, the more sharing of data between those two types of solutions, whether you’re managing employees or health plan members versus patients in the clinical system, those are the same people. They’re at work and they’re managing their diabetes, in many cases with the help of coaches who are giving them the appropriate feedback and nudges around lifestyle [00:26:30] behavior change, those types of things. But they are seeing a clinician, and the ability to share that data back and forth we think is really important. And again, our differentiation, our value proposition is really in managing that patient-to-provider connection. So we think that’s really important.

                                         And in some ways, we’ve done the work and we have a unique position in the industry where we do have great partnerships with the device companies. They see the value in [00:27:00] being a part of our universal platform. It creates a lot of value for the clinics and the clinicians, and then they’re willing to sign a device integration agreement with us and data license agreements with us to be able to create that value for clinics and for patients.

                                         And their proprietary solutions have a lot of value as well. Most of them, not all of them, choose to create that and offer that to clinics as well to support their device, but it does become somewhat unwieldy for a clinic to be able to manage all [00:27:30] those different pieces of proprietary software, to be able to see the data from those devices, somewhat in a silo and not integrated with a bunch of other data that includes multiple device data if folks are using different devices from different manufacturers as well as activity, lifestyle type behavior that we can bring in. And then the data insights that we push to them as well based on the intersection of those data points.

                                         So in a sense they’re competitive, but we see in more cases, in pretty much all cases, that [00:28:00] both coexist quite easily in the marketplace. And so we think that’s valuable. I do think over time, it will make sense in terms of advancing the ability to really manage the condition for patients, to see more integration, more data interoperability, sharing between device companies, payers, data management platforms like ourselves, coaching programs that are helping patients self-manage [00:28:30] in between office visits. The more [inaudible 00:28:34] patient you can have, all of those players pulling in the same direction sharing data, I think the better off we’ll be for helping them manage their condition.

Ryan Booker:                   Interesting. That makes a ton of sense. So on those large industry partners that you start deals with both as investors and for commercial collaborations, companies in the med tech space like Insulet [00:29:00] and Medtronic, on the pharma side, Novo Nordisk. Can you talk a bit about how these partnerships have helped you scale and how do they help you work towards your long-term vision?

Russ Johannesso…:         Sure. Yeah. No. We do enjoy great relationships with nearly all of the device companies and pharmaceutical companies that are key players in the diabetes space. And so as you’ve mentioned, [00:29:30] several of those folks are investors in our business, and of course, that’s helpful for us just to capitalize the business. But also, they drive really valuable commercial partnerships for us. They help us go-to-market and they help us get into global expansion that the countries we wouldn’t necessarily have otherwise been in there, and they help promote the solution as they launch their devices, their solutions, their [00:30:00] therapies into new markets, since we support that, and it brings our business into those different markets as well. So they’re really an important part of our go-to-market strategy and they help us grow much more quickly.

                                         If you think about, for example, our relationship with Insulet, their field sales force helps put the Glooko solution in many health systems and clinics around the globe, and that’s certainly a much bigger field sales organization than we could field are on our own. We have a small direct sales force, but being able to [00:30:30] leverage the Insulet team as well is very valuable for us and the expansion. It’s helped us get to this large global clinical footprint that we have today.

                                         So our partners, they’re working with us to really think about how we can make progress on the treatment of the disease, and we work jointly on clinical research opportunities. And so it’s really been very rewarding, not just financially, commercially, but also in terms of having an impact and driving value [00:31:00] in the market to be able to work with these great partners.

Ryan Booker:                   Got it. Maybe moving to a financial question. Can you talk a little bit about the capitalization of the company today? Anything you’d be willing to provide on the financial performance of the company over whatever timeframe you’d feel comfortable on and how you’re thinking about funding needed and your path to cash flow breakeven over the next several years?

Russ Johannesso…:         [00:31:30] Sure, absolutely. So we are a business. I came in a little more than two years ago and with really the mandate to start to grow and scale this business. And we’ve put in place… We spent the first little chunk of time getting the product and platform ready to grow and scale at an enterprise level, getting the internal infrastructure and processes ready to scale, and maybe most importantly, getting the [00:32:00] right leadership team on the field to help grow and scale this business. And we’ve started to see the benefit of that. We grew over 30% on the top line from last year to this year. Despite disruptions from COVID-19, we’ll grow more than 30% on the top line again this year, and our expectation is we’ll be growing at north of 50% in ’21 and ’22 as we go forward. So we’re really starting to turn that growth curve as well.

                                         At the same time, we’ve tried to be [00:32:30] good stewards of the capital that we do have in the business. We are on a path to cashflow positive, and we should hit that on a run rate basis. End of Q3 of next year is the trajectory that we’re on right now. We’re in the middle of a capital raise right now that gives us the capital we need to get that runway. We closed… We broke it into two pieces on this extension round. We did an insider [00:33:00] round that we closed back in July, and we’re open right now with a round for new equity investors coming in, and we’re trying to get closed up here over the next couple of months.

                                         And so as you’d referenced before, we’ve got a great group of investors, some really supportive and great venture capital investors in Canaan partners and Georgian partners, and a great group of strategic investors, many of which you’ve mentioned, Nova Nordisk, Medtronic, Insulet, [00:33:30] Samsung, Mayo Clinic. Great investors both supportive of the business financially, and then some great commercial partnerships that help us drive growth in the business as well.

                                         So we’re feeling pretty good about where we are. The COVID-19 pandemic has disrupted a lot of things in the industry, but in many ways, some strong tailwinds for us going forward as well.

Ryan Booker:                   Fantastic. Yeah, it’s an impressive acceleration off of an already pretty fast [00:34:00] to top line growth rate. Is that increasing adoption of telehealth the primary driver? And maybe to finish up, can you provide a little more detail on that transition you referenced earlier of moving, instead of being a cost center for these physician offices, providing incremental revenue opportunities?

Russ Johannesso…:         Yeah. Certainly. And if you think about the long-term [00:34:30] trajectory of a business like our… the good success and continue to have good success selling in a SaaS model into the provider side of the healthcare world, and that made up about 50% of our revenue stream. But over time, that is a very margin-sensitive and pressured part of the healthcare system. And maybe particularly now post-pandemic as the financial situation on many of those hospitals [00:35:00] and health systems is not in a great spot, shut down for a while. So it’ll take a little time to recover that. We much prefer to be in a spot to have aligned incentives around helping them grow and drive new revenue from new reimbursement opportunities that are out there. So we think that’s a great opportunity both for them to create sustainable revenue streams and for us to share in that rather than to be an expense item. They win, we win in those situations. And [00:35:30] while no one would’ve wished for something like a global pandemic, it has actually accelerated our growth in a number of ways.

                                         When the pandemic broke, the first thing we did really was lean into the issue. And we deployed a free remote care version of our product globally. We allowed any health system, hospital, clinic around the globe to sign up and leverage our remote care solution, no charge. And the real idea [00:36:00] around that was to be able to help continue to provide support for people with diabetes when they could not come in for a physician visit. All [inaudible 00:36:09] visits got shut down immediately then, and this is not a condition that can wait. This isn’t elective medical care. This is something that has to be managed. And so we made that offer free. Immediately got a lot of great uptake on it. Continue to get uptake on it. Over 100 hospitals and health systems around the globe have [00:36:30] taken us up, and they continue to come in.

                                         And we think eventually, once the pandemic dies down, we’ll be able to convert those folks to a paying version of our solution that has all the features in it, et cetera, but that’s really not the primary objective. It was to be able to make sure that we could meet the need and demand in the market to keep these patients safe. Because while people with diabetes are more likely to catch COVID-19, [00:37:00] if they do get it, the complications can be much worse. And so we wanted to make sure we could keep those folks safe. The way that solution works is that the patients are able to… We can sign up a new clinic in 10 minutes and they’re able to invite their patients to download the Glooko app. They connect their account to the clinic. The patients then can sync their device with Glooko and share that data with the physician and leverage… The patient themselves can see the same data and analytics. [00:37:30] And via telehealth, we can support those conversations directly with the patient in between.

                                         We had a really good response, and we really are glad to be able to do our part on that. Our remote sinking across all our sites has really increased by over 1,000% since this pandemic hit. And with the temporary relaxation of global regulations, it has made it easier to [00:38:00] give and to receive and have paid for remote care, telehealth, et cetera, and we think that’s going to be more permanent, as I’ve mentioned earlier. And we continue to just track that legislation and the positive reimbursement dynamics around the world. And we think that’ll be a great boost for the whole community of people with diabetes. And we think that also is going to be a strong benefit for us as those things continue to happen.

                                         So it’s accelerated us a lot. We think the [00:38:30] acceleration around the adoption of telehealth in general has probably accelerated five to 10 years in the last 10 weeks. So in that way, we really do think that this has given us a lot of strong tailwinds. We had a really strong 2019. We were enjoying a really strong start to 2020 when the pandemic hit, and it did cause us to step back and really reassess the business and try to understand what was going to be the [00:39:00] impact for our customers, for our markets. We took some very proactive measures to tighten our belts and make sure we could preserve capital in an uncertain environment, but we’re actually seeing a lot of positive tailwinds as we get through this.

Ryan Booker:                   Excellent. I think we’re bumping up at the end of time here, but I want to thank you again for coming on. Russ, we really appreciate it.

Russ Johannesso…:         Thanks, Ryan. Appreciate you having me.

Speaker 1:                       [00:39:30] Thanks for joining us. Stay tuned for the next episode of Cowen Insights.