AI for Rx | Dave Billiter

Modern medicine has changed, so it seems rather odd that our processes in medicine, for the most part, haven't. For our founder David Billiter, this was a problem he wanted to solve. 

In a revealing interview with UpTech's Alexander Ferguson, Dave explores the rationale of why Deep Lens is vital in seeing the development of our clinical trial processes. He tells us his personal story that led to the creation of Deep Lens and the unique challenges of implementing technology into the workflow of healthcare professionals.

For many patients, the need for care is immediate, and many miss the small window of opportunity to enter a potentially life-saving trial. With Deep Lens, this problem is solved. 



Transcript.

Alex: Dave, I'm excited to hear more about Deep Lens and the unique solution of the technology that you're bringing. If I were to ask you to describe your company in five seconds in a very brief format, what would you say?

Dave: We're a digital company helping care teams match the right patient, to the right clinical trial, at the right time. 

Alex: Love it so simple; right patient, right trial, right time. What year did this begin, this organization?

Dave: It was late 2017, and that was more on paper, and putting the company together. 2018 was really when we really kicked off with the company and really started to advance our technology, and start putting the technology at work and the problems that we're trying to solve.

Alex: This is the first organization that you've led, you've probably managed and directed them, but it's the first one, correct?

Dave: That's correct.

Alex: You were in Cardinal Health before, and you saw the problem firsthand that led to this type of solution?

Dave: Yeah. It wasn't just my time at Cardinal Health. I think it was a culmination of problems that I was trying to solve when I was the director of informatics at Nationwide Children's Hospital. And then I saw another angle of the problem when I was running data strategy for the specialty unit at Cardinal Health.

Alex: So let's dig into the problem. Is the problem that you saw the one you ended up trying to solve?

Dave: Now, Alex, I appreciate this question. I would say it's a complicated problem. And I'll also say that's why we started the company. You know, we wanted to dig in and try to solve this complicated problem. Still, the problem at its highest description is too many patients are being missed in the healthcare setting and not getting an opportunity to potentially get on a life saving clinical trial, being supported by the pharmaceutical and biotech companies that are out there running these trials. It's a known problem. And again it is a complicated aspect when you start digging into why.

Alex: And this complexity is a problem of why it hasn't been solved. Give me a use case example and tell me how your technology can help solve it?

Dave: Yeah, I think when you look at clinical trials, whether they're being run in a big Comprehensive Cancer Centre, or they're being run in hospitals that are in an integrated delivery network. You have individuals like clinical research coordinators, that may be in charge of, you know, it's just one clinical research coordinator, and they're in charge of sometimes 10, 15, 20 different clinical trials. Their role is to try to identify and produce a screening process to see if those patients are eligible for that specific trial. Well, when you start breaking that down, you have one individual trying to manage multiple different trials and the complexities of those trials with the inclusion/exclusion criteria. It's absolutely overwhelming.

Alex: And this almost prohibits them from being able to see all the opportunities that could be there?

Dave: That's exactly right, and these individuals that are in that role are very talented and work extremely hard. When you look at Deep Lens and what we're trying to do is, in essence, augment, not replace a CRC, but it's augment and help optimize that entire process allowing them to do more. And then, it enables them to communicate. You know with specialists like oncologists and pathologists, to make sure that that specific patient, right in that small window can be matched and screened to get a roll on that clinical trial.

Alex: We're getting to a world where it's bringing individualized health options. And this type of technology that you are bringing is trying to facilitate that?

Dave: That's right. I appreciate how you frame that because it gets into, you hear a lot on precision medicine, you hear a lot on personalized medicine, and that is true. So the clinical trials that are being designed and developed by your big pharma companies and your biotechs that what's exciting is they are getting more to that precision-based. What it also does it creates a challenge because with being precise, you need a lot of tools and support and resources to make sure that precision is realized within a healthcare setting, to get that patient in that window. Again, I talked about that window because the precision-based trials support that precision-based aspect. And that's where our technology is enabling the care team to make that match.

Alex: So the current situation is these pharma companies, they need patients for clinical trials, and it can take a long process because that CRC is just inundated and trying to make all the matches, so technology is coming in here to speed up the entire process. That's what you're trying to solve?

Dave: That's exactly right. I think that's what gets us excited. The reason why I, and my partners, and those that are a part of Deep Lens get out of bed is because our platform as a solution is solving two sides of the problem. What we see within the hospital systems, and those providers; are these challenges to identify patients and screen and get them on trials. And on the other side, the sponsors who are sponsoring those clinical trials, they're trying to do everything they can to get the numbers of patients to enrol in their trials so that they can get that drug to market so that more patients have the opportunities to benefit from that drug. That's where the excitement comes from, from the plans is seeing both sides of the problem. And our technology enabling that on both sides because in the end, the patient benefits.

Alex: Digging into the technology a bit more - can you describe how does it work? How does it speed up the process of formation and data that has been provided?

Dave: So, when we break it down, Viper is the name of our platform. Viper integrates data from three primary source systems, it's the electronic medical record—the laboratory information system. And then there's genomic results that come in those three data sources. We ingest all three of those data sources and think of it as we harmonize and normalize that into the backend database that supports Viper. And then what we've done is we've developed some very, very smart logic and AI techniques that allow us in real-time to take the data that we're receiving from those source systems to programmatically match that to inclusion/exclusion criteria for the trials. That can be a very challenging process for clinical research coordinators, so that's where we talk about trying to provide, being an assistant to them and those challenges to try to manage all those trials. So it's a combination, I think when you look at the technology, but it's also the process. We combine some advanced AI techniques and logic engines, as well as a process that we implement with our collaborators, our partners at the hospital systems and cancer centres, to embed that into a workflow that matches what they're doing on a daily basis. So, that's really where that combination of technology and process comes into play.

Alex: If you're not getting the data in, the hospitals aren't providing it. It doesn't solve anything, so hence the importance of the process. Now, the hospitals are not paying for this, it's the Big Pharma that is?

Dave: That's correct. I think that this is another aspect of our company, and even our approach, that I get pretty excited about is when we started Deep Lens. You know, I say this, we didn't start the company to try to squeeze dollars out of the health systems. They're already burdened enough. So, even though we're solving significant problems and providing some advanced technology and techniques - it was not our goal to go in and try to sell it and gain and monetize from the provider side. What we wanted to do, knowing that we are a business, we wanted to look at the other side of the challenge knowing that your big pharma companies, your sponsors, as we allude to; the pharma sponsors and those that are supporting those clinical trials we look to collaborate and partner with them. And that's really where the dollars come from - the sponsors to help support them to try to move their trials faster, to get that drug to the market.

Alex: Got it. There's data being transferred here, we're in an age of data privacy concerns. How do you address that and to the effect of, does the patient have any control, who has control, and how is it being protected?

Dave: Yeah, so the way I look at it, the patient is always in control. And I think that you know the patient looks to the health systems and the providers, as the honest broker. That partnership is really what enables it, but it's still a patient-centric model and approach to solve the problem. It's the pharma sponsor side that we look to from a business perspective; those dollars come from them to help support the entire model.

Alex: Yeah, the whole ecosystem. I had another conversation with another tech company that has the same focus. The future is, we all have important data that other companies and people want. And so, we shouldn't be the ones having to pay to provide our data rather paying to get it right.

Dave: Right, and even to the data aspect, and to HIPAA and privacy concerns. So, this is something that we spent a lot of time, energy and dollars on at the very beginning, to make sure that we were building, part of our technology is making sure that we have all the right techniques and security and regulatory components. We spent a lot of time upfront to do that because we're managing data, and the data is the triggers. So, we spend a lot of time and energy upfront to make sure we're HIPAA and GDPR compliant on the way our structure works. But, it also helps facilitate that collaboration and partnership that we have with our provider partners in solving that big problem, even with the sponsors.

Alex: Okay, so I see the power of this system comes into play for patients and for then pharma companies needing those clinical trials. How far along are you? I see you said only about 2017, about 2 to 3 years ago on paper. How many hospitals and patients are you able to be seeing now, and what's the projection?

Dave: Yeah. So, I think right now we're still at the beginning stages. It's really what we refer to as our lighthouse initiatives. We want everyone to take advantage of this. And when we say everyone, we're talking about all the providers, and sponsors that are running trials. But you know what we're doing right now is those individual groups providers and sponsors that are coming to the table that we can enable them at the very beginning to realize the technology. And then we're going to continue to look to expand within even your integrated delivery networks, and with your big comprehensive Cancer Centres. So, you know, numbers change every day. Because we're bringing on new institutions, within each institution we're continuing to add trials that are configured in the platform. So, it's not static, it's continuing to grow; which we're excited about.

Alex: Can you share roughly how many patients or stuff that is data, just any kind of number that shows the progress?

Dave: Yeah, so we have over 35 different trials running right now. Patients are being identified in the hundreds. Just even from an identification and screening perspective. And those can be broken down even on a per-trial basis. And, we're looking to expand even from those numbers at institutions, even on a ratio of upwards to three to four different institutions across multiple months.

Alex: That's fantastic. Looking forward from here, where do you see the company and in five years from now?

Dave: Yeah, I get excited about answering that question. I see Deep Lens, and the Viper platform, becoming that de facto system and enabling care teams. As well as, the communication between the providers and the pharma sponsors - really being that enabler. And when folks turn to a system, or a technology or a process that wants to facilitate optimizing how their patients are getting on clinical trials, and then even on the sponsor side, being able to increase their drug to market: Deep Lens is who they turn to. And that's really where I see us going in five years. Depending on who you're talking to, whether you're on the provider side or the sponsor side, Deep Lens is the platform and the company that you turn to really help facilitate those activities.

Alex: I'm excited to see that vision. Where can folks go to learn more and what's a good first step for them to take?

Dave: Yeah, the very first step is we're very heavy in the social world, even through LinkedIn. You can search up Deep Lens Facebook. You name it we have multiple outlets because we want to inform that we're out there and want to make sure the community, whether you're a patient, whether you're an oncologist or a pathologist, a sponsor that's running trials; we just want to awareness and letting folks know we exist, and we're solving a big problem. So, those social outlets. You can search up Deep Lens and find us, as well as our website. You can go to any of those. And then that'll help facilitate connecting to our team members. 

 

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