Evidation Health – Deborah Kipatrick, CEO

Speaker 1 (00:06):
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 (00:27):
Welcome to the Cowen FutureHealth Podcast. 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 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 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 Kilpatrick (01:24):
Good morning from California, Charles. Thanks for having me.
Charles Rhyee (01:28):
Great. Thanks for being here. Why don't we start out with a little of your background and how you found yourself at Evidation?
Deborah Kilpatrick (01:35):
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 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 information can fundamentally change diagnosis and therapy and ultimately patient management.
(02:36):
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 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 (03:16):
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 Kilpatrick (03:24):
Charles, I like to say that Evidation measures health in everyday life. And when we do that, 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 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?
(04:18):
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 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 (04:58):
You talked about how 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 Kilpatrick (05:12):
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, 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 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.
(06:13):
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 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 (06:58):
That's interesting that you talk about. So 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 Kilpatrick (07:26):
That's a really fascinating concept. I haven't quite thought about a metric of engagement 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 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. It's okay to demand it.
Charles Rhyee (08:31):
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 Kilpatrick (08:47):
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 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 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.
(09:54):
So there are many different types of flowing data, but for us, the common denominator is it's permissioned and turn on or off by the person themselves through Achievement in the products that are associated with human.
Charles Rhyee (10:08):
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, and when did it become apparent to you that this data was clinically relevant?
Deborah Kilpatrick (10:35):
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. 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.
(11:22):
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 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. 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.
(12:16):
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. 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 (12:50):
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 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 Kilpatrick (13:20):
The data platform that is the central core for the technology engine, you know what? All of the achievers 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 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.
(14:17):
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 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 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.
(15:07):
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 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 (15:39):
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 Kilpatrick (15:46):
Correct.
Charles Rhyee (15:47):
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 with your pharma partners?
Deborah Kilpatrick (16:02):
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 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.
(16:59):
You'll also see us making 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 (17:26):
Yeah. That sounds pretty amazing. And touching on 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 Kilpatrick (17:55):
Yeah. I'll first say we're really thrilled to be working with 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 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.
(18:47):
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 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 experience the condition within clinic walls so much as this is just a part of their daily lives. It should be measured there.
(19:36):
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 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 is measured across the board. And that's really exciting to me into the people on my team.
Charles Rhyee (20:37):
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 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 Kilpatrick (21:11):
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 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 D.C. at the FDA and beyond for years have an amplifying their call to action for more patients in our trials in general.
(22:08):
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 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 grade studies or regulatories in multiple studies, but it soon will be.
(23:04):
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 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 (23:39):
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. 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 Kilpatrick (24:08):
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, 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 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 (25:09):
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 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 future could be?
Deborah Kilpatrick (26:02):
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 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.
(26:58):
When you stand back from 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 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.
(27:49):
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 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 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 (28:37):
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 Kilpatrick (28:58):
Yeah. I mean, 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, 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.
(29:48):
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 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 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 (30:48):
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 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 Kilpatrick (31:22):
Sure. I think Charles you're probably referring to an announcement that we made in May about a collaboration with the New York City 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 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.
(32:25):
And so we call it our COVID-19 Experience Study capital E 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 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 (33:20):
Any idea when we might be able to see some of the data coming out of this, how long is this study going on for? And what's the time period?
Deborah Kilpatrick (33:32):
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 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.
(34:24):
Well, that's actually quite important because we know that activity levels signal both are 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 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 (35:08):
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 Kilpatrick (35:28):
Right. So earlier 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 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 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.
(36:41):
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 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.
(37:29):
So this is just 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 (37:57):
Yeah, and it seems like 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 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 Kilpatrick (38:50):
I think, if I go way back to Q4 of 2019, which seems like a really long time ago now, 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 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 need it now.
(40:00):
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 employee at Evidation, I couldn't be more motivated.
Charles Rhyee (40:33):
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 Kilpatrick (40:52):
We're very excited to continue making some announcements in the next couple of months about our partnerships 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 (41:20):
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 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 Kilpatrick (41:48):
Thank you, Charles. And I look forward to seeing you and shaking your hand when we do that again.
Charles Rhyee (41:52):
Absolutely.
Deborah Kilpatrick (41:53):
All right. Take care.
Charles Rhyee (41:54):
All right. Take care. Thank you.
Speaker 1 (41:56):
Thanks for joining us. Stay tuned for the next episode of Cowen Insights.

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