Real-world data will likely play a bigger role in FDA drug reviews as the agency adopts lessons from Covid-19 to future regulatory decisions.
The urgency of the pandemic has propelled U.S. health leaders to use data from sources such as patient medical records and mobile devices to help make decisions in real time. The Food and Drug Administration signaled it will further expand use of these sources through the release of two new draft guidances and a partnership to rapidly assess Covid-19 products.
“The pandemic has highlighted the value of real world evidence, both for what it can tell you about things like transmission and masks and tests and risk, but also for its agility and relevance,” Nancy A. Dreyer, chief scientific officer at IQVIA Real-World Solutions, said.
Challenges remain, however, in ensuring such data can meet the standards for making regulatory decisions and figuring out what do when there are holes in the information.
Real-world evidence generally includes data on a drug’s use, benefits, or risks derived from sources other than traditional clinical trials. Clinical trials can be limited in scope, so real-world data can augment those studies, such as by characterizing the experience of patient populations not included in the trials, Jeff Allen, president and CEO of Friends of Cancer Research, said.
But certain types of information are still best fit coming from clinical trials because some drug evaluations require well-measured, well-annotated study designs that can eliminate bias population variables, said Allen, whose organization has run pilot projects on real-world evidence.
“It’s not just a data problem. It’s also a methodology problem,” Miruna Sasu, chief strategy officer of COTA Inc., which provides oncology real-world data and analytics for providers, said. The methods used to analyze data stem from the 1950s and are designed for clinical trials, she said.
“I hope that this experience of knowing both what’s possible and what currently is not possible in terms of real world data will allow the developers of the data and the technologies to collect the data to be able to address some of those gaps in the future,” Allen said.
The FDA has moved increasingly toward using more real-world data, but the pandemic has brought its use to the forefront. Real-world studies from Israel factored into decisions about boosters and also helped drive guidelines on masking at the Centers for Disease Control and Prevention.
“Covid has sort of forced the examination of real world evidence,” Allen said. “Particularly in the early months of Covid-19, there were not clinical trials that were set up so the information had to come from real-life clinical experiences. Obviously, that quickly transitioned as therapies became available, or different observational cohorts were more formalized.”
The FDA recently expanded a contract with health-care analytics company Aetion Inc. to use real-world evidence to study Covid-19 medical products . The agency has also released two draft guidances over the past month on real-world evidence: one on data standards and another on using EHRs and medical claims data to make regulatory decisions about drugs.
Patient-generated data can help understand how well a medical intervention is working, not just in the clinical setting but in a patient’s normal environment, Anindita Saha, assistant director of the FDA’s Digital Health Center of Excellence, said at the National Association of Rare Disorders’ rare diseases summit.
“We can use that information, especially in the rare disease cases, really shifting towards a more patient-generated, real world evidence framework rather than just from device generation or EHR generated data,” she said.
The 2016 biomedical innovation law 21st Century Cures required the FDA to develop a real-world evidence framework. An agreement the FDA reached with industry in August for the next round of user fees also includes language on advancing real-world evidence. But some of the concerns from sponsors and the FDA continue to be around data quality.
“I’ve seen this evolution from no real world data all the way to now,” where studies have external control arms, meaning they pull data based on how patients are doing with standard medical care, Sasu said.
“But the truth is that even in areas where real world data is truly robust at this point, regulatory agencies are still asking for clinical trial patients, because we know that this statistical methodology will help us make sure that that the trial is robust,” she said.
Amy Abernethy, president of Verily’s clinical research business and former second-in-command at the FDA, said at a recent HLTH innovation and transformation conference that she envisions a world of continuous generation of evidence both in the context of clinical trials and in the health-care system—both before and after a product hits the market—to provide the best care for patients.
“The whole landscape of evidence generation is shifting, with perhaps smaller and smaller traditional clinical trials, and now more of a focus on systematic evidence generation collecting data, making sense of medical products in that post approval setting across the medical product lifecycle,” Abernethy said.
Gaps in the Data
Sasu said regulators need to clarify how drug companies can address gaps in real-world data that are almost inevitable because they’re being captured in health-care settings by doctors who aren’t conducting studies in controlled environments.
“The guidance that we have seen makes it known that they understand these gaps. But it doesn’t really say here’s what you do to help us approve the drug based on this,” Sasu said, adding that the FDA is ahead of its counterparts in this effort.
There are often legitimate reasons why some data points are missing, such as patients are too sick to answer or there are incomplete electronic medical records as part of routine care, Dreyer said.
“That worries people understandably,” she said. “So you have to figure out how important that missing data is, and who it’s missing for and where it’s missing.”
Nevertheless, real-world data can be used every step along the way of a drug development process to minimize the timeline, Sasu said.
“Drugs used to get to market in 10 to 15 years. We just proved that we can do it in a year,” she said. “Let’s go out and actually curate and get enough data so that we can do this in databases, stop burdening the patients so much and get these drugs to market in a year.”