TRANSCRIPT
Deborah Borfitz:
Hello and welcome to the Scope of Things podcast, a no-nonsense look at the promise and problems of clinical research based on a sweep of the latest news and emerging trends in the field. And what I think is worthy of your 30 or so minutes of time. Please consider making this your trusted go-to channel for staying current on things that matter, whether they give us hope or cause for pause. In a few minutes, I'll be speaking with Dr. Dan Drozd, Chief Medical Officer at Picnic Health, about non-interventional studies and the collection of fit-for-use evidence to strengthen the quality of research. But first, the latest news, including an expanding good pharma scorecard, an entirely telehealth-based trial for cancer, a world-first online platform for bowel cancer research, improving patient-reported outcomes in cancer trials, a virtual clinical trial of psychedelics, and identifying type 1 diabetes in the symptomless window stage.
Deborah Borfitz:
A Yale study finds that medicines are inaccessible in many of the places where they are tested for FDA approval, based on an analysis of 172 approved drugs studied between 2015 and 2018 in nearly 90 countries. High-income countries had greater physical access to the medicines than upper middle and lower middle income countries, a gap that runs counter to vaguely written ethical frameworks in place for decades. The remedy for the test it but don't sell it problem comes in the form of an incentivizing good pharma scorecard that is being expanded to rate and rank companies based on post-trial access to the treatments they develop. Health ministers and clinical trial leaders from countries like Ethiopia and Uganda, who have managed to secure full access to the medicines they help test, will also be sharing their lessons learned with peer nations. Researchers at the Ohio State University have designed a first of its kind, entirely telehealth-based, nationwide targeted cancer drug therapy clinical trial for pancreatic cancer patients with a rare genetic mutation. The therapy is a smart drug that is already FDA approved for the treatment of bile duct cancers. Up to 40 adults with advanced or metastatic pancreatic cancer will be enrolled in the phase two study with telehealth delivered in partnership with local oncologists. A registry has also been created for patients to join and support research on rare types of pancreatic cancer.
Deborah Borfitz:
Experts in the UK have launched a world-first online platform enabling public participation to shape the future of bowel cancer research and patient care. The so-called Colo Speed team at Newcastle University are now signing up people to the platform where they can voice their level of interest and activities ranging from co-developing new research ideas and taking part in research directly as a participant to attending in-person and online patient meetings and going to research showcase events where they can meet researchers and learn about new bowel cancer studies. More than 3,000 people have already expressed an interest in the platform, putting it on course to be the largest of its kind in the world. The International SysQual IMI Consortium recently revealed how its recently issued recommendations for patient reported outcomes in cancer clinical trials were developed, while simultaneously releasing a suite of online materials to help researchers, clinicians, regulators, and policymakers implement them. By providing a harmonized framework, the recommendations are expected to improve the quality and consistency of PRO data, ensuring patient voices are more effectively integrated into cancer research, drug development, and clinical care. The newly released online toolkit includes plain language checklists to better support stakeholders in the design of clinical trial protocols and promote meaningful interpretation of cancer PRO findings.
Deborah Borfitz:
A virtual clinical trial of psychedelics on personalized computational models of patients' brains suggests that LSD and psilocybin may find utility in treating patients who do not fully regain consciousness after a coma. Researchers demonstrated that the psychedelic substances could shift brain activity in patients with disorders of consciousness towards healthier, more flexible, and complex dynamics. The treatments boosted responses to controlled changes, particularly among people in a minimally conscious state where the effects correlated with brain functional connectivity, providing a starting point for potential future clinical trials. And finally, researchers in the UK are using a genetic risk score in a pair of clinical trials, one for kids and another for adults, to predict who is at heightened risk of developing type 1 diabetes while they are still in the symptomless window, months or years before diagnosis. The test feeds into an existing clinical calculator, helping doctors identify children who should get autoantibody testing to confirm early stage disease. The idea here is to more broadly identify high-risk individuals early on, when a new-to-market drug in the UK and US would be of value in delaying disease onset and the need for insulin. In a recently published study, the genetic risk score showed that people scoring in the top 10% were eight times higher risk of being in the early stages of type 1 diabetes. As a reminder, links to the articles, studies, and press releases referenced in this month's news segment can be found in the show notes.
Deborah Borfitz:
It is now time to bring Picnic Health's Dr. Dan Drozd to the mic for a chat about how we can and why we should raise the bar for evidence generation via non-interventional studies. Welcome to the show, Dr. Drozd.
Dan Drozd:
Thanks so much for having me today, Deborah. Appreciate the opportunity to chat.
Deborah Borfitz:
Excellent. So you are not only an MD, but also an epidemiologist, an engineer, and a startup executive. How did all of these different roles sort of coalesce to define who you have become and how you came to be the chief medical officer at Picnic Health?
Dan Drozd:
Yeah, it's a it's a great question. I think my my path to where I am now has been pretty heterogeneous. I certainly, when I was growing up, I definitely thought that I would become a doctor. So there's a way of looking at it that very much is that I'm sort of, I think, serving in the role and doing the sort of work that I was really born to do. But when I was a child, I grew up walking around hospitals all the time. My grandpa was executive director of a county hospital in Los Angeles. I was very involved with computers. When I was an in undergrad, I was an English major, which really taught me to tell a story, which I think is it ends up being an underappreciated but very important part of my role. I worked as a startup engineer. And then my entree into clinical research really happened shortly after I made the decision ultimately to go to medical school. I worked on at an informatics research group at University of Washington and built a data integration platform to support HIV clinical research and really, I think formed sort of the basis in my introduction to what is it, what does it really mean to perform, you know, what I think we generically now might call patient-centric research.
Dan Drozd:
And to me, that's a term it gets thrown around a lot, but I think ultimately, you know, the goal is to engage study participants and patients in the research process and then with the intent of ultimately making making patients' lives better. And so I eventually went to med school and through residency and fellowship, really thought I would become an academic physician and was on kind of the pathway to do that. Felt the pull to really do something outside of academia, something where I might be able to have a larger impact, be able to move faster than things oftentimes can move within academia. I spent a period of time as a practicing physician. And then really my bridge into this world of technology on the one hand and medicine on the other sort of came to its fruition with my role at Picnic Health. I've been at Picnic now about six years. And I think the questions that drove me and continue to drive me are really how can we take all of this data that is collected through patients' routine clinical care and utilize and leverage that data to bring better, safer treatments to patients faster. The technology infrastructure and changes that have occurred over the last decade have been incredible. I think we all experience them in our day-to-day lives. And at Picnic, we really leverage that technology, kind of paired and grounded with scientific expertise to use AI as well as patients' right of access to collect and collate patients' medical record information and really identify the portions of that information that can be most impactful for driving key research questions for our study partners.
Deborah Borfitz:
Well, very good answer. Thank you. I appreciate all that. What a story. What a journey. And part of that journey is I recently learned, and you've many accomplishments on your resume, but over the past few decades, notably something of note would be that you were involved in the design and development of this registry database for the largest multi-centered non-interventional HIV cohort in North America to study the long-term impact of HIV treatments. I mean, that had to come with some potentially huge technical and logistical and regulatory and data management challenges. You know, what did you find to be the core difficulties that you were able to turn into sort of actionable insights for similar endeavors since then?
Dan Drozd:
Yeah, I think it's a great question. So it goes without saying that obviously that that's work that I started in 2004 and had been ongoing a little a bit before I joined that effort. That was all led out of the University of Washington through a group of researchers there collaborating with other HIV researchers around the country, was certainly very lucky to get involved in that project and kind of building that infrastructure. Clearly, technology is vastly different today. I think even if we think about cyclical trends, EHR adoption, post-meaningful use legislation is far greater than it was back at that point in time. But I do think that there are really some core lessons from that time. And I should say that the project in that infrastructure is still up and running. It is still generating meaningful HIV clinical evidence related to treatment of patients with HIV infection. But in terms of lessons learned, I think really one is as you're thinking about ingesting data from vastly different data sources, where in the case of electronic health record data, the intent of the generation of the data ultimately is not to support research use cases. You need to be very thoughtful and intentional about picking which data is consistent enough across systems and across data collection mechanisms to be able to be used for whatever the particular research use case of interest happens to be. I think it does need to be a very thoughtful and intentional process. I think data harmonization is a related kind of subset of that. The way that data comes across from electronic health record systems, even simple things like units used to measure lab tests can be different. And so I think there is a lot of cleanup work that is necessary there. I think from maybe more a regulatory-facing perspective, ensuring that you have really clear and documented audit trails and rules for data transformations and protocol-driven abstraction when data is being abstracted directly.
Dan Drozd:
But I think at the end of the day, it really is an understanding at a deep scientific level of the research question at hand and making an honest assessment of whether the data that you're thinking about using is fit for purpose for whatever project you happen to be working on. And that includes things with regards to is the population itself relevant or the endpoints that are captured within the data robust and consistent enough to support whatever the evidentiary needs may be. But I do think there is really just tremendous potential there. If I look back on that system, for example, the treatment paradigm for treating patients with HAV back when this system was started was basically to treat patients for a period of time, allow their immune systems to recover, then take them off of treatment, allow their immune systems to deteriorate again, have patients end up in the hospital with opportunistic infections, and then put them back on medications. And so there was this Seesaw component to it. And I think the data coming out of this platform was some of the first data really to support, you know, what now is very much standard of care for treating patients with HIV. You should be treated as soon as you're diagnosed. You should stay on medications, you know, throughout the rest of your life. And that this is the best way to minimize the long-term impact of HIV on an individual and to return their life expectancy to normal or near normal.
Deborah Borfitz:
Yeah, good news. Good news for that whole population for sure. And a long time coming in just so many ways that it could have gone wrong. But you know, you learn as you go. For sure.
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Deborah Borfitz:
Yeah, you've made you've made the point that non-interventional research, while critical to answering complex questions about the natural history of disease and the impact of treatments in the real world, has been underutilized and inefficient. Yet they're used throughout clinical development and are an integral part of the long-term evaluation of the safety and efficacy of novel drugs post-approval. Could you enlighten me and listeners to the chief issues researchers are facing and the ramifications of this?
Dan Drozd:
Yeah, I would say at the outset that I want to be clear that I really am a pragmatist here. There are many, many situations where well-designed observational studies are the best solution to a particular evidentiary need. But that's definitely not everywhere. Randomized control trials clearly remain the foundation or cornerstone of generation of robust efficacy and safety data. But we need to acknowledge that there are situations where, for ethical reasons or financial reasons, inability to recruit patients where it's just not possible to run these studies. And at the same time, that because clinical trials, traditional clinical trials, are designed in a way to have a very specific population of patients that are being assessed in the trial, that the real world impact of treatments oftentimes is different in patients who don't strictly meet clinical trial inclusion and exclusion criteria. And we do, at the end of the day, oftentimes end up using treatments for populations of patients that don't look exactly like clinical trial patients. So that's that's what I would say first. I think the second is just more broadly, there are many, many situations where our need for data and evidence outpaces our ability to generate it today using kind of a more traditional, either randomized clinical trial-based approach or site-based observational research. And that we need to think about things in terms of the overall both evidentiary requirements, but also the burden that generating this data places on both patients and sites. And so for me, it's not really an either-or question. It becomes a question of how can we leverage technology to reduce burden and to make things more efficient.
Dan Drozd:
So, in essence, that you know, one plus one can be more than two at times, and that there really isn't a point in trying to design and run a study where you're not going to be able to recruit the patients to participate in the study, or where high numbers of patients drop out. The end goal is generating evidence. The end goal isn't in the running of the study itself. And so, lastly, I'll just call out kind of a broader bucket of studies, pragmatic trials, where I think there is a huge amount of opportunity, where particular subsets of studies can be run in ways that leverage real world data, leverage kind of more decentralized approaches to data collection, where at times certain outcomes for studies can be derived or abstracted from EHR data and then adjudicated that allow for more inclusive and representative populations of patients to be included in the study. And ultimately, this is about fitting data collection and study design to evidentiary goals and needs.
Deborah Borfitz:
You pointed to this a little bit already, but I'm going to ask more specifically what what would be your recommendations or your recommended tactics for sort of raising the bar for evidence generation in on non-interventional studies so clinicians can be fully confident of the safety and effectiveness of treatments they might consider prescribing to their patients. You got some go-to advice?
Dan Drozd:
Yeah, I think it's a great question. I think what I always try to do whenever I'm approaching a potential problem is to really try to think creatively. I don't think that technology or AI are the answers for everything, but they're incredibly they're they're incredibly important and powerful tools that we can use to, you know, really provide significant leverage when used in the right situations with appropriate oversights. And so I think having having an open mind to new and innovative ways of potentially running studies, I would also say that thinking about things from a study design perspective, really taking patient perspective and burden in mind. I have conversations all the time with people who, you know, we would like to, we would like to potentially, you know, have 17 patient reported outcome instruments done in this particular study. And it may be that there is some value coming from all 17 of those, for example, but you know, that places an incredible burden on study participants. And we know that the more burden you provide, the less likely people are to complete all of the activities. And so I think there's just some pragmatic thinking about, you know, the study participants are at the end of the day, they're all of us. We have a million things and competing interests and demands on our time. So we do really need to be thoughtful about how we're kind of optimizing designs of studies to minimize that burden. I mentioned this a bit before, but I think understanding your data sources, they're not all created equal, and understand whether that data can be used from an objective standpoint to meet whatever the evidentiary needs are and be really clear about limitations and risks, what data you're thinking about using.
Deborah Borfitz:
Yep, yep. Very good. I think I heard that word pragmatic at least three times. And it may come up again in my next question. I'm not sure. But prospective non-interventional studies, which generally happen at clinical sites and are run by contract research organizations, can sometimes struggle to keep participants engaged and retained, which brings us to the question of where different advanced technologies, such as those used by picnic health, might logically play a role. So I think I'll frame the question this way. What generally makes the case with study sponsors to run a study using the Picnic platform?
Dan Drozd:
I think the pitch is ultimately about, you know, kind of some of the things that I I will probably throw in the word pragmatic here again, I'll say. But I do think that re I do think it really is about our ability to think creatively about potential. Solutions to how to run studies leveraging technology when possible. The goal is really to generate the evidence that patients need as quickly as possible without sacrificing rigor. We know that sites are under a tremendous amount of strain, that they do tremendous work. And I think there are situations when we can relieve some of that burden through the use of technology from traditional sites and that we ought to, we ought to be aggressive in doing so when it makes sense. Clearly, there are things that need to happen at clinical sites. There are real, there's a real true value to those sites. But I think returning to that word pragmatic, you know, in situations where we can do a video visit to follow up with a patient, or a patient can potentially get labs drawn at a local site or have a phlepotomist come out to their house.
Dan Drozd:
We know that doing things like that has the has the real potential to reduce burden on participants, encourage potential study participants who might not otherwise have the time or flexibility to participate. We ask a tremendous amount of study participants. And in particular, in non-interventional research, where participants are not receiving a treatment as part of the study itself, an investigational treatment as part of the study itself. I think we need to be particularly attuned and thoughtful to the burden that we're placing on study participants, both because it's the right thing to do and also because it is really the only way in the long run that I think we'll be able to meet these increasing evidentiary needs that we have and to and to generate robust high-quality data at the sort of scale that we need to do going forward.
Deborah Borfitz:
Great answer. Thank you. You know, we're now in a new year, which begs the question, now what? From your unique vantage point in the clinical research space, what can we expect to see more or less of, or both, in 2026?
Dan Drozd:
I like this question a lot. You know, it's always it is always good to both reflect forward and backward as we're entering a new year. So I'll throw out a couple of things. I think, you know, a core of what we do at PICNIC ultimately is that ability to collect patients' medical records and gather that data longitudinally over time. I do think that there have been changes through TEFCA and individual access to records that have progressed over the course of 2025. And I do think that will continue to progress in 2026, really ultimately giving patients, all of us, better access, better and easier access to our own data. I think there was a recent FDA announcement in December, no longer requiring individual patient data and device submissions that are using real world data. I think we will continue to see trends like that progress as well in terms of integration, more direct integration and acceptability of the use of real world data and regulatory submissions. I would be remiss if I didn't say something about AI. I think we've seen a lot of experimentation and kind of pilot projects. And really now I think are starting to see kind of more increasing uptake from a larger, you know, more scaled perspective across the spectrum within clinical research and drug development. Everything from operational components, patient identification, clinical trial operations and study operations, data structuring. There's a long way to go. But I do think that we're starting to see evidence of scaling and ultimately impact there. And then ongoing efforts at clinical trial modernization, which kind of harken back to some of the comments I made about pragmatic studies previously. And then lastly, an area that's gotten a lot of attention recently over the last couple of months is around cell and gene therapy. I think we're seeing potential for accelerated approvals of cell and gene therapy treatments and willingness to adopt more innovative approaches to long-term follow-up in that space as well.
Deborah Borfitz:
Wow, lots of good things to look forward to this year. Hopefully, they will come to pass as you envision it. It could be one for the record books in terms of both patient care and more equitable, dare I say, meaningful, high-caliber research. Oh, thanks for your efforts to create some momentum in those directions. And thanks so much for taking the time to talk with me today.
Dan Drozd:
Thanks, Deborah. I appreciate it.
Deborah Borfitz:
We'll be talking again. And as always, a big thank you to everyone out there for listening in. If you're not subscribed to this podcast yet, please consider going to Apple Podcasts and doing so right now. So you don't miss your monthly dose of news and perspectives. You'll be hard pressed to find anywhere else. And if you're up for it, I'd also be so very grateful if you'd leave a rating and review while you're there. One final note if you'd like today's show, it's only a glimpse of news and insights we have untapped for the next scope event taking place in sunny Orlando, Florida, from February 2nd through the 5th, 2026, this year now. Please plan to join me there and be sure to use discount code SOT10 for a ten percent discount off any current rate. For more information, visit scopesummit.com. Bye for now.