Getting real about COVID-19 data with Amy Abernethy and Mark McClellan
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Responding to COVID-19 is forcing regulators, medical product developers and health systems to get real about real-world data and evidence as they reach for every available tool to learn about the disease and speed the development of effective interventions.
Amy Abernethy, FDA’s principal deputy commissioner and acting CIO, and Mark McClellan, director of the Duke-Margolis Center for Health Policy at Duke University, described in interviews for a pair of BioCentury This Week -- Special Report podcasts how the pandemic has accelerated progress on integrating real-world data and evidence into research and practice.
They also noted urgent needs to improve coordination of data acquisition and analysis in the coming weeks and months, and expressed the hope that advances made in extraordinary circumstances will persist when the world advances to a post-COVID-19 reality.
COVID-19 is the “first major public health emergency of the era of truly, digital access to broad, real-world data and hopefully real-world evidence,” McClellan told BioCentury.
As with other areas, from the integration of telemedicine and remote monitoring into research and practice to intensifying collaborations among organizations that are hard-wired for competition, the pandemic response is accelerating progress toward the goal of a learning health system, Abernethy and McClellan said.
“It has pushed us to make changes that we needed to make anyway, but were overcome by inertia or the old way of doing things, whether it’s telemedicine or other aspects of care delivery, [or] integrating public health and healthcare better,” McClellan told BioCentury.
“I have more hope in the last three weeks that we are moving in that direction in some kind of systematic fashion than I’ve ever seen.”
McClellan, a former FDA commissioner and CMS administrator, serves on the boards of Johnson & Johnson (NYSE:JNJ) and Cigna Corp. (NYSE:CI).
“My hope,” he said, “is that eventually we’re going to get to an even more unified approach where clinical experience matched with the fast capacity to do real-world analysis using well-defined, well-understood data and validated methods will give us stronger conclusions about safety and potentially, effectiveness.”
It will be possible, he added, to use those “systems as a basis for doing more practical, real-world clinical trials. It may be that this is the pandemic is the forcing event that brings that reality forward.”
The real goal
While conversations about real-world data often focus on answering specific questions or advocating technical methods, Abernethy told BioCentury that COVID-19 reminds everyone of the big goal: to create systems that make it possible for every patient’s data to inform and improve decisions made by and for future patients.
The idea, she said, is to create an ecosystem in which “the care of each person is informed by all people who look similar to her, and her care has been reinvested into a system for the future, so that she has her own data legacy that also continues to advance our understanding and the frontline of knowledge.”
Abernethy said she has been thinking and writing about this idea for 20 years and that the COVID-19 response has forced quick, meaningful changes. “I have more hope in the last three weeks that we are moving in that direction in some kind of systematic fashion than I’ve ever seen.”
Prior to joining FDA in February 2019, Abernethy was CMO, CSO and SVP for oncology at Flatiron Health, a unit of Roche (SIX:ROG; OTCQX:RHHBY).
She said that achieving the vision of a learning healthcare system “requires alignment of incentives, and one of the things about COVID-19 is a lot of the competition that has often been one of the biggest challenges has started to blur into the background.”
The Reagan-Udall Foundation and Friends of Cancer Research have created the COVID-19 Evidence Accelerator to foster collaboration among FDA, industry and academic groups to use real-world data to address the pandemic (see “Accelerating the Collection of Real-World Data About COVID-19”).
Rather than setting up real-world data as an alternative to data collected in clinical trials, Abernethy and McClellan described an iterative relationship in which clinical observations prompt data collection that can lead to clinical trials.
“You’re seeing studies that are finding associations between existing drugs and outcomes, drugs like famotidine, for example,” McClellan said.
McClellan and Abernethy both pointed to the role of real-world data in producing early, quick information about higher rates of blood clotting problems in hospitalized COVID-19 patients and suggesting the potential benefits of blood thinning agents to prevent clotting.
Those data have prompted the quick initiation of clinical trials.
Associations with immediate, practical utility like the role of coagulation in COVID-19 are being uncovered as a result of the “interaction between clinical anecdotal information and large-scale, real-world analysis that is possible now and in ways that weren’t possible before,” McClellan said.
While they are optimistic about progress that has been made, McClellan and Abernethy acknowledge that more must be done -- and quickly.
The question of whether systems can be put in place to get data from clinical trials in time to craft interventions for the expected second wave of COVID-19 is “sobering,” Abernethy said. “We are going to need to do a lot of clinical development, and frankly start to prioritize our clinical toolbox through prospective data collection and clinical trials, and we need to do so fast.”
Completing studies in time to deploy interventions in the fall or winter will be a challenge, especially if the pandemic fades in the summer months, McClellan said. “People need to be asking now ‘How are you actually going to get the randomized clinical trial evidence that we need?’”
Given the large number of potential treatments and vaccines, it isn’t going to be possible to obtain the necessary data using conventional methods, McClellan and Abernethy said.
Answering critical questions about what works and what doesn’t work for COVID-19 will require changes in data systems “to incorporate more randomization into real-world practical settings,” McClellan said.
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