Clinical trials are notoriously slow, expensive, and inefficient, creating a major bottleneck that delays getting life-saving treatments to cancer patients. What if we could build a new research engine from the ground up, leveraging data and technology to run trials 6x faster and at a significantly lower cost? In this episode, we explore the groundbreaking work of the Flatiron Health clinical research unit, a team that is redefining what's possible in oncology research.
Joined by Alex Deyle, VP & General Manager of Clinical Research at Flatiron Health, we uncover the strategies and technologies they are deploying to fix the broken trial system. From their origins as a pioneer in real-world evidence to their acquisition by Roche, Flatiron has built a unique ecosystem founded on deep integrations with community oncology EHRs. Now, they're leveraging that foundation to tackle the biggest challenges in clinical research, from protocol design to final data submission. This conversation is a must-watch for anyone interested in the future of drug development, health tech, and the mission to get new treatments to patients faster.
This episode breaks down the new model for improving clinical trial efficiency. We explore Flatiron's three-pronged approach: designing smarter protocols by using real-world evidence in clinical trials to optimize eligibility criteria, accelerating clinical trial patient recruitment with AI-powered patient matching that reduces site screening effort by 95%, and lowering the massive data collection burden with innovative EHR to EDC solutions. Alex shares incredible real-world examples, including a partnership with Exact Sciences on a molecular residual disease (MRD) study that went from concept to first patient in just six months—a process that typically takes years. We also dive into their collaboration with NRG Oncology, one of the NCI's cooperative groups, to deploy their Flatiron ClinicalPipe™ technology and prove the value of a direct data pipeline from the EHR to the trial database (EDC). This integrated approach is generating compelling results, showing that their end-to-end model can enroll studies up to six times faster and at a 20-30% lower cost than traditional methods, paving the way for a new era of decentralized clinical trials.
About Our Guest:
Alex Deyle is VP & General Manager of the Clinical Research business unit at Flatiron Health. With a background as a biomedical engineer and a health-tech consultant, Alex was inspired by the multidisciplinary, problem-solving approach of MIT's Hacking Medicine. He joined Flatiron to be part of a team that brings together clinicians, engineers, and data scientists to solve healthcare's biggest challenges. He was instrumental in building Flatiron’s renowned real-world evidence business before leading the charge to transform clinical trials.
Introduction
Dr. Trevor Royce: Good to see you guys.
Dr. Tim Showalter: Hey guys.
Dr. Paul Gerrard: Good to see you.
Dr. Tim Showalter: I'm calling from Pittsburgh, Pennsylvania.
Dr. Trevor Royce: Pittsburgh.
Dr. Paul Gerrard: Home of NSABP.
Dr. Tim Showalter: Home of Duolingo too.
Dr. Paul Gerrard: Ah, interesting.
Dr. Tim Showalter: I think there's a lot of technology here. When I checked in the hotel, there was some loud technology salesperson yelling into some Zoom calls. So that was my first entry point to Pittsburgh.
Dr. Paul Gerrard: That sounds like a Zoom call.
Dr. Tim Showalter: We should just hop in.
Dr. Paul Gerrard: I hope this interview doesn't get too steamy talking Flatiron and all.
Dr. Trevor Royce: Oh, there it is.
Dr. Tim Showalter: I knew you had it in you. Let's get in it.
Dr. Trevor Royce: Welcome to Health Tech Remedy, the show where three physician leaders in health technology tell the stories of new and established companies and interview leaders from the industry. I'm Trevor Royce, radiation oncologist and researcher with experience in real-world evidence, informatics, and AI diagnostics.
Dr. Paul Gerrard: And I'm Paul Gerrard. I started off as a physical medicine and rehabilitation physician before focusing on reimbursement policy, molecular diagnostics, and market access for AI products.
Dr. Tim Showalter: And I'm Tim Showalter, a radiation oncologist and prior med device entrepreneur who is now focused on bringing AI advances to cancer patients.
From Real-World Evidence Pioneer to Clinical Research Innovator
Dr. Trevor Royce: This week, we're diving into Flatiron Health, a company that's been transforming cancer care and research through data-driven technology. Flatiron's story starts with oncology-specific EHRs, or electronic health records. But today, it's an end-to-end research platform that's accelerating things like clinical trials, advancing real-world evidence generation across the globe.
Dr. Trevor Royce: Pretty excited to talk about Flatiron Health today. Obviously, this is near and dear to our hearts, Tim, after spending some time there, and looking forward to seeing what Alex has to say later on the clinical research side of things.
Dr. Paul Gerrard: So, I am the only non-Flatiron person who's going to be on this call today, but I think Flatiron's a really exciting company with 280 cancer centers, top global pharma companies, and leading academic institutions are looking to them to help make oncology smarter, faster, and more personalized. And they've built a research engine that supports regulators, health systems, and developers of oncology therapeutics.
Dr. Paul Gerrard: And it sounds like their tools are really changing the game in clinical trials, speeding up enrollment, improving patient identification and candidacy for trials, and reducing trial costs through this better infrastructure. And I think we're going to talk with Alex about that infrastructure that they built.
Dr. Tim Showalter: What everyone knows about Flatiron Health is that the name is synonymous with real-world evidence. They're one of the most well-known examples in that space and have been considered the authority. And of course, it was a Google Ventures company and a famous story within health technology.
Dr. Tim Showalter: I'll also just say, like Trevor, I spent some time at Flatiron Health. I found it to be a group of really high quality, talented and mission driven people. And I think it's really where I learned how to work with teams that are blending healthcare expertise and technology to really innovate in this space. So really excited to feature their ongoing work and new areas like the clinical research business unit.
Dr. Trevor Royce: It was founded around 2012 and was acquired by Roche only six years later in 2018. And as you mentioned, Tim, kind of one of the real flagship success stories in health technology with a very large acquisition or exit with Roche in 2018. I think it was around $2 billion or something. And just a great story of entrepreneurial success from two, I believe, Penn graduates that went on to build this titan of data in oncology.
Dr. Trevor Royce: One thing that I appreciate from the researcher side is they've done a lot to push forward the definitions and methodologies behind real-world data and has helped in a lot of ways shape and define that industry and how these data can be used to improve outcomes for patients and have a better understanding of what cancer patients are going through in the real world, meaning in clinics throughout the U.S. And now they've expanded beyond with operations in the U.K. and Germany and Japan where they're extracting EHR data.
Dr. Trevor Royce: And the big picture, I think there's sort of two key features of Flatiron. One is the EHR side where they have this electronic health record that's directly in private practice, oncology clinics through the U.S., and direct integrations to those EHRs with pipelines that then flow into their data. And so they build these large, on the other side of the business, large-scale data sets that can be used for all sorts of use cases, obviously, including research. And they've been prolific publishers and collaborators with pharma, academicians, and everyone in between.
Dr. Trevor Royce: So as I mentioned, they have the EHR software, they have the real-world evidence and evidence generation and analytics. And more recently, and I think that's going to be a big focus of our discussion with Alex later, is on the clinical research side, how these data elements can make the clinical research infrastructure more efficient and better.
The Core Challenge: Unlocking Siloed Data in Clinical Research
Dr. Tim Showalter: For those listeners who may not be as familiar with the real-world data space and all of the systems involved, it's probably useful to step back a little bit and just think about the challenge of working with healthcare data. In oncology, the research has really been limited by outdated workflows and data entry in the clinical trial world. You start with source files, and ultimately someone's encoding that into a database and backing it up with source documentation.
Dr. Tim Showalter: On the research side, clinical trials are notoriously slow to enroll, so that advances are limited by that. And then the data itself is generally siloed in different places or it's living in unstructured data sources. And so getting the right evidence from the right patients at the right time has historically been just a huge barrier to moving discovery forward into the bedside.
Dr. Tim Showalter: And I think what's interesting about Flatiron is that I will say myself for following the story when I first heard about this many years ago now at this point, it seemed like the challenge of extracting data from the electronic health record back when Flatiron was starting to do this seemed like a Herculean task. And I think they did the first important work to demonstrate that you could gain important actual insights that was such high quality in terms of the evidence that you could make potentially regulatory decisions, for example, like label expansions with real-world data.
Dr. Tim Showalter: And at the time, they threw a lot of smart people at it and even showed that some of this work would require human abstraction. And then now, of course, as the technology has gotten better and better, now that work is done with enablement through technology and natural language processing and other tools. And so what they've done in the wave of technology innovation they've contributed to and led on the real world data side is pretty remarkable. And then, of course, they're expanding into new business areas. And that's what I'm most excited really to focus on.
Dr. Trevor Royce: Yeah, I'll just quickly chime in to say that it's been cool to see the evolution of AI and how it directly impacts someone like Flatiron Health. To your point, Flatiron is known traditionally as the best-in-class quality data sets. And it's hard to have quality data sets when you're extracting data from the EHR. It's messy data.
Dr. Trevor Royce: You have to have very rigorous methods to make sure the data is consistent across data sets and that the endpoints are well-defined, that you don't have missingness, which is often a problem when you're collecting EHR data. And a lot of that was done with humans because that was the only way to ensure with very rigorous protocols that you're defining your data elements correctly and having consistent data and now in the world with LLMs, clearly that model will be impacted by this. So it's just a very clear case where before you're using humans to abstract this data and now finally we're at the point where you can use LLMs essentially to abstract that data.
Improving Clinical Trial Patient Recruitment and Protocol Design
Dr. Paul Gerrard: I think one other exciting thing here is the opportunity for clinical trial enrollment. It's not just using real-world data or running clinical trials more efficiently. It's helping to find the patients for clinical trials. Running a clinical trial is itself a big operational bear to deal with. You have to go find patients. That can take a while. These drugs are under patent. That patent life is ticking. So the longer it takes to run the trial, the potential less time you have on the back end. So I think all of that is really exciting.
Dr. Paul Gerrard: And then the other thing too is we're entering the world of precision medicine. Well, I shouldn't say enter it. We've been in this world of precision medicine, particularly in cancer, where we're getting to narrower and narrower populations that can benefit from a particular drug. So how do you match those narrow populations that are getting harder and harder to find with the trial they could be eligible for? To me, having this solution where you already have a footprint in the marketplace, you're able to help identify patients, help to inform oncologists who are already seeing their patients about clinical trial eligibility is really exciting, not just from a business standpoint, but for furthering the knowledge base in medicine.
Dr. Tim Showalter: If you think about who can get research done quickly, and in terms of working with biopharma, make sure that research studies will be successful, the data resources and infrastructure that Flatiron have gives them a really huge right to win. In terms of one classic barrier for figuring out where to initiate a clinical trial, is whether or not the center will actually contribute patients to the study.
Dr. Tim Showalter: And I think certainly Flatiron has all the resources to be able to identify practices that see patients who may be eligible for the study, to confirm eligibility, to surface eligible patients to clinical staff, and maybe even to embed workflows that can help with both clinical trial enrollment and data collection directly. So you can't think of a better basic substrate for making an impact in this space than Flatiron.
Dr. Trevor Royce: Interesting how they're tackling this clinical research problem from so many different angles in their clinical research group that they've really put a lot of resources and spun up over the last couple of years. And as you mentioned, Tim, the traditional clinical trial process is very slow. So the bar is pretty low, I think, to cross. And I think they're already showing ways that they can speed up trials. The traditional CRO model is obviously slow and ineffective and inefficient. There's a ton of disruption being targeted towards this space.
Dr. Trevor Royce: There are things like protocol optimization. You have these traditional protocols that are copy forward. Can you, in a more intelligent way, optimize these protocols for the question at hand and the data that you're going to have access to? And I'll just put a plug in for some of our own work that we did when we were there, was the idea of eligibility criteria and how you can expand eligibility criteria to have more patients be eligible to enroll in your trial.
Dr. Trevor Royce: The trade-off is obviously toxicity, if you're including patients that have worse renal function and how that will impact the results of your trial and the design of that trial. But if you can show through real data that you can expand eligibility criteria, that the outcomes will be similar, then you can optimize these eligibility criteria for that given protocol. And they've done some good work publishing and looking at that where with traditional eligibility criteria, maybe less than 50% of the oncology patients would be eligible. When you broaden them with limited impact on those endpoints, you could have up to 75 patients eligible for the clinical trial.
Dr. Trevor Royce: So there is some pretty compelling data starting to support some of these approaches. And I think the next step is obviously to put it into action. And to be fair, the idea of broadening clinical trial eligibility criteria has been around for over decades. It's cool to see this applied very directly using these scaled data sets.
Dr. Tim Showalter: And ultimately, that's going to translate into getting trials completed faster and accelerating time to, say, drug approval or whatever the research question is. And I think there's also a representativeness aspect of this, which is that as clinicians, we always think about when we're counseling a patient for whether therapy is appropriate for them, whether or not this is a patient whose outcome or likelihood of benefiting from a therapy could be predicted by the existing clinical trial evidence. If you broaden the eligibility criteria, you're going to have more patients who are really represented in the evidence generated from that clinical trial, which I think is a good thing for all of our patients.
Dr. Trevor Royce: One thing like protocol optimization, they've also looked at things like site selection. They have this huge network across the U.S. Can they identify sites that are going to be the most successful chances at accruing patients for these trials? There's a lot of times in clinical trials where you open at a site and they can never accrue patients for many, many reasons that we've talked about on other podcasts here.
Dr. Trevor Royce: The other thing that's interesting is this EHR to EDC idea where you have a direct pipe from the EHR to your trial data set and then you can minimize the burden of data collection and increase the accuracy and the speed and all the rest. And they've really supported that number one with an acquisition a couple years of a company called ClinicalPipe that built this technology for EHR to EDC. And now I think recently I believe I saw a press release showing that that exact platform, I'm sure they've made improvements along the way, but will be partnered with NRG Oncology, these large nationwide cooperative groups sponsored by the NCI. So they're really putting this into effect.
Creating a New Model for Contract Research Organizations (CROs)
Dr. Tim Showalter: We've got our interview with Alex coming up, and I think we'll hear a lot about the clinical research business unit activities, as well as their recently announced partnerships with a variety of entities like NRG Oncology and Exact Sciences. So maybe let's just pause now and we can do a little bit of around the horn and get a little bit of high-level takeaways from each person.
Dr. Paul Gerrard: There's lots of little pieces here. They've got this footprint with the EHRs. They've put on top of that these various opportunities to use that data efficiently. When we talk about these various little pieces of things they're building, how do they put that all together into an offering for either clinicians or for potential investigators?
Dr. Trevor Royce: I'm just excited to see at the end of the day what metrics and outcomes they can truly improve in the clinical trial space. A lot of people have been trying to tackle these clinical trial issues for a long time. There's a ton of interest in it. It's a competitive space. There are a lot of startups now thinking of ways to improve on clinical trials using real-world data and other methods. Something that very clearly is unique and a strength to Flatiron is their direct access to patients through their EHR network across the U.S. And so I think they're in a really compelling position to demonstrate how this can be improved all the way to the patient.
Dr. Tim Showalter: I'm really excited. I think they're basically, with this clinical research business unit, creating a new model for what a CRO can look like. And I think it's really a broad platform that's deeply embedded within the EMR and the overall ecosystem for the centers that they work with. And they previously essentially defined for the industry what real-world evidence is. And I'm excited to see them define for the industry what CRO can be and what that acronym can mean. So interested to learn more about what's happening and what will unfold in the next few months.
Dr. Trevor Royce: Absolutely. And I think the impact at Flatiron, just as a final reflection in health technology, since this is a health technology podcast, goes beyond what they're working on today and the impact of clinical trial. They're in Flatiron 3.0, or I'm not sure what they'll call it these days, but they were a traditional startup, had a big success, a big exit, all before my time, obviously, then built out these other products and matured and now tackling on clinical research. And a lot of the alumni at Flatiron have gone on to found their own companies and been influential in health technology in their own right. So it's been a key player, the health technology ecosystem, certainly in oncology.
Dr. Tim Showalter: And some of the major alumni have gone on to found podcasts too.
Dr. Trevor Royce: The number one ranked health technology podcast in the world, I'm sure. That's great, guys. Anything else to add on this before we close out?
Dr. Tim Showalter: I think that's it. Looking forward to having our conversation with Alex Deyle, who's the general manager of the clinical research unit at Flatiron. So stay tuned.
Introducing Alex Deyle: A Journey to the Forefront of Health Tech
Dr. Paul Gerrard: Alex, as the only non-Flatiron person on this call, let me say it's great to meet you, great to have you on the podcast. We'd love to start with just getting to know your story, your background, what brought you to Flatiron, and then what attracted you to the clinical research side of cancer care? What was that opportunity that you saw?
Alex Deyle: My background actually originally starts, I was a biomedical engineer, and I worked very briefly as a biomedical engineer in drug development and early development of drug delivery devices in the healthcare space, but then moved pretty quickly into being a consultant at IMS Health, one of the precursors to IQVIA when they came together with Quintiles. And I worked in consulting for about a decade.
Alex Deyle: And I was starting to look for something new and different to do and wanted to get into a space where I felt like I could have more direct impact in healthcare and healthcare delivery. And I actually found at the time a group out of MIT called Hacking Medicine. It was a group that would organize these events where they'd bring together people from lots of different backgrounds and multidisciplinary backgrounds together for a weekend. And you would basically come together, form teams, identify problems in healthcare.
Alex Deyle: And by the end of the weekend, you would pitch business plans and ideally prototypes of things that you could launch or new businesses and you'd compete. And the thing that really struck me was MIT Hacking Medicine, bring together clinicians, patients, folks with a business background, engineers, all these different disciplines together to try to figure out and how to solve the most complex problems in healthcare. So that got me really excited to look beyond just consulting and into some place where I could actually go build and be part of a team building something. And it was right around the time that I actually found Flatiron Health.
Alex Deyle: And serendipitously, Flatiron had built their entire business all along that idea of bringing together multidisciplinary teams and the best of the best across oncology clinicians and nurses and engineers and product managers and business folks to tackle this problem of how do we learn from the experience of every patient with cancer. And so that's what brought me to Flatiron. It felt like an opportunity to take what I had learned at this MIT hacking medicine experience and then put it into my day-to-day and what I got to do every day at work.
Dr. Tim Showalter: And when you started at Flatiron, I'm curious to hear about your initial experiences there. And I know that you've had a very long tenure at Flatiron. How did it start in the very beginning in terms of your role and what you're really focused on?
Alex Deyle: Yeah, I've been at Flatiron now for about nine years. I first came in, I joined in April of 2016, right after Flatiron had raised its Series C. We were around 200 people or 200 employees at the time. And my first role coming into Flatiron was to help build out our real-world evidence research partnerships with biopharma companies.
Alex Deyle: And so, this was, I would say, it was interesting. In the real-world data space at that time, maybe typical of a Series C, there was pretty clear signals of product market fit in the real-world data space, but we were definitely still finding and honing our exact niche. At the time, we were working across commercial teams, HEOR teams, medical affairs teams to find where and how Flatiron's oncology real-world data sets could be most impactful.
Alex Deyle: And one of the things we learned through that in the early years was, and where we really ended up focusing a lot of our effort was more on the research side than on the commercial side, because we found that there was, given the depth of and high quality of data that Flatiron was generating, it unlocked a lot of really interesting use cases in the clinical development, market access side of the world, which was really exciting. And that's where I started my career at Flatiron.
The Mission: Making Clinical Trials More Efficient and Representative
Dr. Tim Showalter: Those who are familiar with the Flatiron story know that it's really grown into a central player in cancer data and technology and basically pioneered most of the use cases of real-world data, certainly in oncology. And I know that more recently, you've gotten intimately involved in the clinical research business unit and are really expanding the impact that Flatiron's making. How do you describe the mission and scope of that new business unit? Can you catch us up a little bit?
Alex Deyle: Clinical research at Flatiron is really focused. Our aspiration is to make clinical trials more efficient and more representative. And taking a step back in terms of, and Paul, you had kind of asked, what drove me into the clinical research space? From my end, I've always been motivated by this problem of how do we get more treatment options for more patients faster? I first started tackling that problem as a biomedical engineer, where I learned about the science of developing new drugs and protein folding and all the things that go into making biologics for cancer care.
Alex Deyle: I then spent a chunk of my career on the business side of it in a consulting role, helping pharma companies think through economics of drug development and thinking about how to prioritize which drugs go into phase two and phase three based on ROI and net present value analyses and this whole other suite of things beyond the science that influence which drugs get to market for patients. And one of the things that became clear was there was a whole nother operational set of burdens around running clinical trials.
Alex Deyle: And clinical trials have, oftentimes the operations of clinical trials have nothing to do with the science or the market size or market potential, but it's just this huge operational bottleneck that just is a main driver or a huge problem in getting new treatment options to patients faster. And so I was really excited when here at Flatiron, we made the decision to make a strategic investment to move beyond real-world data into the clinical research space because it just felt like such a massive component of the challenges associated with getting more treatments to more patients faster. So yeah, so Tim, the focus is on making trials more efficient, more representative. I think the idea is how do we generate more reliable evidence on which treatments work for which patients, while also lowering the burden on the ecosystem for conducting clinical research?
Dr. Trevor Royce: We spent a fair amount of time on this show talking about some of the challenges historically with clinical trials. They're slow, costly, limited access. And what Flatiron set out to do is pretty bold. This is an issue that's been around for decades, basically. And maybe before we get into some of the specifics of how you guys are going to tackle that, because I think Paul has some questions on the specifics level. Tell us a little bit about that moment at Flatiron. How do you even start up a new business unit that's going to tackle something like this? How do you know it's being successful? What's it like going almost zero to one in a company that already had a very successful product line?
Alex Deyle: Yeah, it's interesting. Stepping back, I actually remember when I first joined Flatiron in 2016, we had started making, what I would consider to be initial pilot hypothesis driven investments in aspects of clinical trials. So we had started thinking about how could we streamline patient recruitment by building software at the point of care for oncology practices that makes it easier to screen patients for clinical trials and match eligibility based on what's data is in their EHR. And that had started going all the way back to 2016, and it wasn't until about 2020 that we had started seeing enough, I would say two things.
Alex Deyle: One, we started seeing enough validation and proof points from some of the early hypothesis generating work that we had done and the investments we had made that there was a real opportunity for us to have an impact and that we really felt like we had a true advantage to drive change in some of these areas of clinical trials. And then two, I think the industry changed. I think with COVID, there was a huge disruption in how people thought about clinical trials. And there was a huge willingness to think differently about how to run clinical research.
Alex Deyle: And so I think it was really both an evolution of proof points we had seen, plus the evolution of the macro environment. And that coincided here at Flatiron with a refresh of our long-term strategy that, led us to making the decision to make clinical research a core pivotal part of what we were investing in and really expanding the opportunity for us to deliver on our mission beyond just real-world data and real-world evidence.
Alex Deyle: In terms of where we play and where we focus on in clinical research, the world of clinical trials, as you all know, is huge. There's a massive surface area to cover when it comes to running clinical trials more efficiently and making them more representative. And so we've really tried to focus on where are the areas that we think we as Flatiron as a company who owns and operates the leading EHR in community oncology, who has a decade plus of experience processing structured and unstructured data out of the EHRs and a network of sites that we partner closely with and build software for at the point of care, where we uniquely positioned to really drive impact in clinical research.
Flatiron's Three-Pronged Approach to Clinical Trial Transformation
Dr. Paul Gerrard: I talked about this in a number of ways, these clunky clinical trials. And you just talked about how Flatiron is well-positioned to solve some things in clinical trials. What's your perspective on why are clinical trials clunky? And then within this big universe of clinical trials, are there certain areas that you think Flatiron really is well-positioned to address?
Alex Deyle: I've heard this once described, this question of why are clinical trials so efficient in a way that has resonated with me. Think of the construction industry. The amount of effort that goes into building a new building or a stadium, let's use a stadium as an example. There's a huge amount of effort that goes into building a new stadium and setting up the infrastructure, laying the foundation, building the walls. But then that stadium gets used for lots of different things. You can host concerts there. You can host sporting events. You can host commencement speeches. You reuse that infrastructure to get ROI on that infrastructure that you build over lots and lots of use cases, events.
Alex Deyle: Clinical trials essentially are you're building buildings for a single clinical trial. You build all the infrastructure from the bottom up, the contracting, the sites, you do every, you build an EDC, you do all of this work, and then you basically tear it all down once the trial's over and rebuild it again every time you start a new trial. And so the idea is there's a massive amount of inefficiency that goes into clinical trial operations, and there's very little existing infrastructure that exists across the ecosystem that is reusable, that can be used to get trials up and running faster.
Dr. Paul Gerrard: That makes perfect sense to me.
Dr. Tim Showalter: That tracks.
Alex Deyle: The other part of the question was just where are we uniquely focused? So I think from our end, there are three areas that I think Flatiron is uniquely positioned to do and to drive transformation in clinical research. One, helping to design smarter trials. Thinking about reusability, this is actually maybe one place where there is some reusability because a lot of what happens today is sponsors copy and paste sections of old protocols for their next protocol. And there hasn't historically been a ton of data and analytics that go into designing smarter trials that are leveraging data to increase the probability of success.
Alex Deyle: So you can imagine a company like Flatiron, who has one of, if not the largest, highly curated oncology real-world data sets is well positioned to take all of that data and apply analytics to help make protocols and clinical trials more operationally feasible and potentially even more scientifically feasible. The second area we focus on is the long pull in the tent for any clinical trial is how long it takes you to actually find and accrue patients to that trial. And so on that front, where we focus on is how do we leverage data, technology, AI, and software at the point of care to identify the right sites at the right time and get the right eyeballs on those patients so that they get an opportunity to be considered and put on clinical trials.
Alex Deyle: The third area we focus on is lowering the burden and costs of data collection for clinical trials. So, this is a problem where, for anyone who hasn't seen how this works in the real world, in the context of a clinical trial, you literally have people sitting at sites who are looking at their EHR, their electronic health record software, and then swiveling their chair to manually transcribe data from one system into another system for the clinical trial.
Alex Deyle: And Flatiron, as a company who's built an EHR and who knows how to process data out of those EHRs, we now have software that facilitates the automatic transfer of data from an EHR system into an EDC system, an EDC system being an electronic data capture system, which is the source of record for clinical trials. And so that alone takes out a huge amount of operational burden on sites, on sponsors. It reduces significantly the need to do source data verification. Reduces the amount of transcription errors that exist, and it allows us to collect that data faster with higher quality and with less operational overhead to get that done.
Dr. Trevor Royce: Yeah, that makes a lot of sense. Just to pause for a second and reflect on what we've covered so far, I think it's really important for our leaders to appreciate some of these very unique and powerful structural systems in place from the Flatiron side. I'm not sure that everyone actually appreciates, number one, that Flatiron has this amazing electronic health record with direct access to community oncology sites. And immediately, you can see how that would be such a useful feature for execution of clinical trials. And then two, the data wherewithal and the experience and reps and builds of these very large scaled. And what's known throughout the industry is incredibly high quality data sets, because if you're running a clinical trial, your data quality is essential. So those are two key features, as you mentioned, about how the infrastructure is in place to tackle some of these challenges.
Case Study: Partnering with Exact Sciences on Molecular Residual Disease (MRD) Research
Dr. Tim Showalter: All of the inefficiencies, Flatiron has a real opportunity to streamline and build a better product, essentially. I love your analogy of each trial has its own physical structure, and you stand up all the resources, and then you've got to repeat it for the next study. One thing that could help our listeners maybe is to go a little deeper into a specific example. And when I was at the ASCO annual meeting this year, I know I saw some interesting announcements from your group or research from your group with Exact Sciences. Maybe can you catch us up a little bit about the work that Flatiron has partnered with Exact Sciences to accomplish?
Alex Deyle: Yeah, absolutely. So Exact Sciences, for those who may not know, they're a leader in the oncology diagnostic space. They've got a market-leading product out, Cologard, which many folks have probably seen commercials for, consumer-facing brand. But they're also developing really amazing tests in what's called the MRD space, or molecular residual disease. And so those are tests intended to be able to detect the existence of cancer in circulating tumor DNA, even after patients may have had a surgical resection, to identify patients who may be at higher risk for recurrence of their cancer.
Alex Deyle: So the unique thing in the MRD space is right now you have MRD tests on the market for just starting to emerge on the market, and they're available for a couple of different or reimbursed in a couple of different tumor types and indications. But there's a real belief that these tests have clinical validity in a wide set of different types of cancers. And so we partnered on with Exact Sciences. It was basically the question was, how do we generate evidence on the clinical utility of MRD tests across a broad swath of different tumor types as quickly as possible with as little burden on the participating sites and the broader research ecosystem as possible and generate data that is high enough quality to support potential use cases related to regulatory or reimbursement and to really help build confidence in this emerging space?
Alex Deyle: We are partnering with Exact Sciences. Flatiron is actually sponsoring the trial in close partnership with Exact Sciences. The objective of the study is to enroll just over 1,300 patients across multiple different solid tumor indications, collecting both tissue and blood samples at multiple times throughout that patient's journey so that we can run the exact MRD test against those samples and eventually use this as clinical utility data in support of better understanding the utility of MRD tests across lots of different indications.
Alex Deyle: This is exciting. That's the scientific objective. What's super cool from an operational perspective is we are standing this study up at over 30 different clinical trial research sites, but we're leveraging master clinical trial agreements that Flatiron has established across our network of tech-enabled sites. Going back to that analogy about building everything and then tearing it down. What we've done is we've rolled out these master agreements across our sites. And that includes rolling out what we call a parent protocol, which is a parent study protocol that allows us to quickly spin up new sub-studies underneath that.
Alex Deyle: And so we've stood this exact study up as a sub-study within a under a Flatiron Master protocol within our existing contractual infrastructure that can be used for multiple clinical trials in the future. And we were able to go from essentially study concept to first patient in, in about six months. That includes writing the protocol, finalizing the protocol, getting IRB approval, reaching out to sites, selecting sites, getting a site activated. And so all of that is a big part because we had this existing operational infrastructure that we had stood up and rolled out across the network to be ready for these types of studies.
Dr. Trevor Royce: And could you put that six months into context against an industry benchmark or standard? How fast or slow does that for our listeners?
Alex Deyle: Yeah, it's a great question. It's hard to know exactly, but our understanding from our work with Exact Sciences and our work with other sponsors on similar trials is that it's significantly faster than industry averages. It often depends, because that includes protocol development. And I think protocol development can take a really long time at certain places, but this was a unique melding of the minds between Flatiron in Exact Sciences, or we just had a really great collaboration model in place and we were able to move really, really quickly through that.
Dr. Trevor Royce: Yeah, I'd love to hear Tim's take on this, but I can tell you from experience as an academic physician, six months is like very, very fast.
Dr. Tim Showalter: Yeah, I think that's remarkable. Congratulations. I think that's a great storyline. And I can imagine with the system that the deactivation steps and getting things moving and particularly the operational advantage of having that parent protocol with pre-existing research and data collection relationships is just a huge value add there.
Alex Deyle: A couple other things that are exciting about the study setup, I mentioned there are multiple different cohorts. And so patients are eligible across lots of different solid tumors. And also the eligibility criteria, patients can become eligible at different points in their journey. So it's actually a bit of a complex protocol for a site to keep track of in terms of which patients are potentially eligible.
Alex Deyle: As you all know, oftentimes clinical trials will have a single PI at a site who's maybe a breast cancer specialist or a lung cancer specialist, and they'll see those patients and keep it top of mind. But this can span multiple different oncologists at any given site who are treating these patients. And so what we've done is at the sites participating, we've spun up our patient matching technology so that now we have constantly in real time screening the EHR data using our data access technology, including structured data matching, variable-specific machine learning models, as well as now LLMs, so that we are constantly screening and surfacing up to the sites the patients who meet the eligibility criteria for the trial.
Alex Deyle: So they don't have to go look from scratch to find patients. We are surfacing those up to them in real time. And we've shown and we've published that through our approach, we can reduce the amount of effort that the sites have to spend on screening by 95%. So you can imagine that's a huge benefit to sites because they're basically being served up the patients who are potentially eligible for this study rather than having to go through and comb through hundreds if not thousands of patient charts who may be coming in for visits in the upcoming couple of weeks to find and identify who might be eligible.
Powering NCI-Funded Trials with NRG Oncology and EHR to EDC Solutions
Dr. Trevor Royce: A really good example of execution on the industry-sponsored side. What about on the cooperative group side? I think you guys recently had a partnership announced with NRG. Can you tell us a little bit about what that looks like? And maybe tell us a little bit about what NRG is.
Alex Deyle: Yeah, absolutely. So NRG is one of the cooperative groups under NCI. They run a large portfolio of NCI-funded oncology clinical trials. And our partnership with NRG is actually in a space that I haven't, I mentioned earlier around streamlining data acquisition, but I hadn't yet gotten to in terms of what we were doing for Exact Sciences. And so this is a nice tee up of that space around how we're streamlining data acquisition.
Alex Deyle: And so in this space, we've partnered with NRG in to deploy what we call Flatiron ClinicalPipe, which is our EHR to EDC data solution on a NRG trial with a specific, the study itself will obviously have a scientific objective, but it will also have an operational objective to measure the utility of the use of an EHR to EDC technology on an oncology trial. Let me step back and maybe spend a little bit more time putting color around EHR to EDC and what we mean by that.
Alex Deyle: So what we found is there's a significant amount of data that is entered into the EHR as part of routine care or for patients who are on clinical trials that then later has to get transcribed into a separate clinical trial database. And so we've built technology that facilitates sites to automatically push that data from their EHR into the EDC without having to do manual transcription. But what's interesting, or one of the things that's interesting, is we know not all data, and you all know, certainly as oncologists, not all data for clinical trials naturally lives in the EHR. And oftentimes there's a whole bunch of data that needs to be entered related to adverse events or concomitant medications that typically requires details beyond what's in the EHR.
Alex Deyle: And so what we've done is we've actually built out workflows that embed into the EHR that facilitate the structured capture of that clinical trial data so that that too can be eligible to be pushed into the EDC. And so one of the things that we're really excited about with the partnership with NRG is they're going to deploy ClinicalPipe on one of their trials, And we're going to measure the utility of ClinicalPipe versus sites that have ClinicalPipe versus sites that do not on the speed of data transfer, the quality, the reduction of queries. And that's going to include both standard structured data transfer, as well as deployment of these research workflows that allow for specialized collection of things like adverse events and tumor burden.
The End-to-End Solution: Compelling Results of a Fully Integrated Model
Dr. Paul Gerrard: Take a step back and we think screening patients for trials, enrollment, data collection. If somebody were to put it all together and use the Flatiron solution for all the little steps, what would that look like?
Alex Deyle: The way Flatiron partners, we can deploy each of these individual solutions on any phase one to phase three oncology trial. But Paul, to your point, where it gets really exciting is when we have an opportunity to take on end-to-end execution for a full study within fully powered by our network of tech-enabled sites with all of these solutions in play. And that's where you really start to see some of the really exciting efficiencies.
Alex Deyle: And so what we have found now looking at a couple of different trials that we've run end-to-end that we're seeing, we can typically enroll those studies four to six times faster, than traditional approaches and at a 20 to 30 percent lower cost. Cost being inclusive of overall burden on the ecosystem in terms of not having to fly CRAs out to do on-site monitoring and shortening the timeline and getting to database lock several months earlier than you otherwise would because of all the efficiencies gained.
Dr. Paul Gerrard: That's very cool. That's a pretty compelling reduction in resource requirements.
Alex Deyle: Super exciting. And I think where we're focusing, as I mentioned, the different technology pieces I talked about can be used in phase one to phase three interventional oncology trials. The whole end-to-end model where we're taking on full end-to-end execution, or in the case of the Exact Sciences space, even sponsoring, we're starting in the post-approval, peri-post-approval space. We have a portfolio of post-marketing commitments from the FDA that we're now running in that end-to-end model, which is also an area where we've seen historically a lot of FDA support for more pragmatically designed approaches to clinical trials in that peri-post-approval space.
The Biggest Challenge: Overcoming the Status Quo in Clinical Research
Dr. Tim Showalter: You guys are clearly up to a lot in this space. I'm curious if you've had any major learnings that you want to comment on, like what surprised you in terms of standing up this new clinical research business unit, or what did you find the most challenging?
Alex Deyle: Hands down, the most challenging is overcoming status quo in clinical trials. The sheer just momentum machinery that goes into place. And listen, it makes a ton of sense. Clinical trials are huge investments. People are investing a significant amount of dollars into running a clinical trial. And the reality is you typically don't get fired for playing it safe. And so even know the current model is inefficient and often results in suboptimal outcomes or trials that never effectively enroll enough patients. The reality is there's safety in following the way it's always been done. And so I think the biggest challenge is just finding individuals, finding organizations who we can partner with, who are really motivated to challenge the status quo and shake things up and do things differently.
Career Advice for Health Tech Innovators: Solve Problems That Matter
Dr. Tim Showalter: Before we wrap up, I did want to just ask you to provide our listeners some career advice. So I think a lot of early career folks are listening and I'm curious what advice you might give for those who are interested in a health technology career or who really are just starting out in terms of building their own careers. What have you learned along the way?
Alex Deyle: One, it's actually one of our values here at Flatiron, but it resonates very deeply with me, which is solve problems that matter. I think anyone who has tried to do anything innovative around technology in the healthcare space knows that it is never easy and there are always challenges to have to work through. And I think when you orient yourself towards solving problems that matter to you and that matter to patients. It helps you get through the inevitable ups and downs of the challenges of fighting against the status quo in healthcare and health tech. And so I would say, find something that you're really passionate about and that really has an impact for patients and people and solve problems that matter.
Alex Deyle: And then the second one would be going back to what I said earlier, build and insert yourself into multidisciplinary teams. Healthcare is not a place that you can get just a couple of smart outsiders to transform how clinical trials are done. It takes people with experience and an understanding of the legal framework and the compliance frameworks and clinicians and people who have actually been boots on the ground. And so I think just finding companies and building companies that bring expertise from all the different aspects of health tech together to solve problems, I think that's the best, one of the best ways to do it. And I'd recommend, it's also one of the best opportunities to learn and to get yourself out of your comfort zone and learn from others who are deep subject matter experts in other areas, which is why I loved working with you, Tim and Trevor.
Dr. Tim Showalter: Thank you, likewise.
Dr. Trevor Royce: I'll just quickly reflect on one of those things you said there, the solve problems that matter. At least for me personally, the Flatiron values are legendary. And there have been multiple instances where I've gone back struggling with an early product phase and an early stage startup and gone just back to square zero and looked at the Flatiron values because there's some real gems in there and I think they're tried and true and I think Flatiron's journey is reflective of that. Tim, I'm sure, I suspect you feel the same way.
Dr. Tim Showalter: Yeah, it's health tech wisdom in pearls. So it's perfect.
Dr. Paul Gerrard: That is the quote of the episode.
Dr. Trevor Royce: Be willing to sit on the floor. That's another gold one.
Dr. Paul Gerrard: Solve problems that matter.
Dr. Trevor Royce: Well, Alex Deyle, thanks for joining us. I think we heard a lot about how Flatiron's work is reshaping what's possible in clinical trials. It's been great to hear from you and how your team is pushing the clinical trial field forward and innovating in that area. This wraps up another episode for Health Tech Remedy. Be sure to subscribe, rate, share the podcast with friends and colleagues. Reach out if you have a guest or topic you'd like to see featured. Thank you all for listening.
Alex Deyle: Thanks, guys. This was fun.
