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Demand for more efficient and faster development of medical products is prompting regulatory authorities to incorporate additional sources of information into research and approval processes, notably data provided by patient registries and medical records able to inform traditional clinical trials. FDA and the European Medicines Agency (EMA) are looking to tap real-world data (RWD) and real-world evidence (RWE) more broadly to accelerate the research and market approval process.
A notable advance was FDA’s recent reliance on RWE to approve an added indication for an important medicine. In July 2021 the agency extended the use of Astella’s liver transplant drug Prograf to also prevent rejection of lung transplants, based on data from a U.S. registry of lung transplant recipients.1 FDA determined that this non-interventional “study” with historical controls met FDA standards for being adequate and well-controlled and precluded bias as an explanation of results, explained John Concato, associate director for real world evidence analytics in the Office of Medical Policy at the Center for Drug Evaluation and Research. Concato also described at the recent Convergence meeting sponsored by the Regulatory Affairs Professionals (RAPS) how FDA demonstration projects are advancing the use of RWD/RWE in different types of studies.
In addition, new FDA draft guidance advises sponsors on strategies for accessing RWD from electronic health records (EHRs) and medical claims to help demonstrate the safety and effectiveness of a drug or biological product to support regulatory decisions.2 While such records are used to track medical product safety and to support additional uses and post-approval study requirements, the diversity and limitations of this information has stymied broader adoption for documenting drug effectiveness. Now FDA is asking biopharmaceutical developers to weigh in on strategies utilizing RWD to support regulatory decisions and to help define treatment exposure, outcomes, data quality assurance and data quality control procedures.
The potential for wider use of RWD and RWE in drug development has moved up on FDA’s agenda since it was featured in the 21st Century Cures Act of 2016 to support the approval of new indications for a drug and for meeting post-approval study requirements. FDA published a framework for wider evaluation of RWE in regulatory decision making in 20183 and issued guidances on using data from EHRs in submissions and on submitting RWD and RWE in applications.4 The agency also expanded its Sentinel surveillance system to help assess how health system data can inform research projects. And FDA efforts to streamline clinical research during the pandemic has highlighted the potential for wider use of RWE to inform research protocols, identify research subjects, and track outcomes and responses remotely. Upcoming revisions in the Prescription Drug User Fee program (PDUFA VII) further expand the use of RWE in these and other initiatives.
Similarly, the European Medicines Agency (EMA) looks to make wider use of RWE in regulatory submissions. At the recent RAPS meeting, EMA director of surveillance and epidemiology Xavier Kurz described a new study on the issue, noting the frequent use of information from disease registries and hospital records, while also acknowledging limitations in the data and confusion over terminology and methods.
Concato and other FDA officials have addressed these developments at numerous meetings and conferences this past year. At a July 2021 symposium on how RWE is changing scientific standards, experts also noted the limitations and need for caution in interpreting studies utilizing RWE. Long-time RWD skeptic Steven Nissen of the Cleveland Clinic warned that RWE is a “dangerous delusion” and should not be viewed as providing “conclusive evidence” on a treatment, citing the failure of early claims of cardiovascular benefits to women of hormone replacement therapy. He argued that wider use of RWE largely aims to save money on clinical development, and that a better strategy is to find more efficient ways to conduct randomized trials.
Most experts, however, look to more advanced data analytical methods to validate data in this area. The rising demand for highly personalized therapies to treat very small patient populations, such as for rare conditions and neonatal populations makes it vital to devise methods for accurate assessment of RWE. In addition, efforts to include more data on patient minorities and other sub-populations in biomedical research looks to tap RWD to make research more inclusive and representative.