The U.S. Food and Drug Administration has significantly expanded its use of real-world evidence to support regulatory decisions, launching a comprehensive Real-World Evidence Program in December 2018 that could fundamentally change how new drug indications are approved. This initiative, mandated by the 21st Century Cures Act signed into law on December 13, 2016, allows the agency to evaluate drug and biologic products using real-world evidence to support approval of new indications, expansion to new populations, or post-approval studies.
Real-world evidence represents clinical evidence about benefits or risks of medical products derived from analyzing real-world data collected through routine clinical practice. Unlike traditional randomized controlled trials that test interventions under ideal conditions, RWE studies examine how treatments perform in everyday clinical settings where patients and clinicians make treatment decisions based on individual characteristics and preferences.
Dramatic Growth in Available Data Sources
The expansion of RWE capabilities has been driven by unprecedented growth in electronic data collection across the U.S. healthcare system. Hospital adoption of electronic health record systems has surged from approximately 31% in 2003 to 99% currently. Similarly, office-based physicians using electronic records increased from just 11% in 2006 to 90% by 2017.
This digital transformation generates billions of user-specific data points daily from wearable devices and smartphones, though over 99% of this newly created digital data remains unanalyzed. New open data policies, including Open FDA and academic data sharing initiatives, are expanding the pool of searchable data for RWE investigators. Advanced software capabilities in artificial intelligence, machine learning, and natural language processing are simplifying the analysis of large databases to assess correlations between patient features, healthcare professional characteristics, diseases, and treatments.
Addressing Traditional Trial Limitations
Randomized controlled trials, while considered the gold standard for evaluating intervention efficacy, face significant limitations that RWE can help address. RCTs suffer from high costs, long completion times, comparison against only placebo or few alternative treatments, impractical eligibility criteria, underrepresentation of certain populations, and trial effects that can inflate measured benefits.
RWE studies offer several advantages over traditional trials. They cost substantially less than RCTs, particularly for studies examining long-term outcomes. Postmarket multiyear cardiovascular RCT outcomes trials for diabetes drugs cost approximately $250 million, while RWE studies require far less investment. RWE can identify rare unanticipated complications better than RCTs, which typically study fewer subjects for shorter periods. These studies also provide information about real-world adherence to interventions and disease severity thresholds at which treatments are prescribed.
Regulatory Applications and Industry Impact
The FDA's RWE framework applies across its drug and biologic review process, covering both prospective noninterventional clinical trials and retrospective observational studies. While the agency has historically used RWE for assessing postmarket product safety, application to support effectiveness determinations has been limited to specific instances until this expanded program.
In oncology, where treatment decisions are complicated by numerous disease forms and rare conditions with limited approved treatments, RWE has become particularly valuable. The FDA approval of a first-line therapy for Merkel cell carcinoma exemplifies how electronic health record data was used in real-world evidence studies to provide essential information about treatment responses and patient outcomes.
Quality Standards and Implementation Challenges
Despite its promise, RWE faces significant challenges that must be addressed for broader regulatory acceptance. Unlike RCTs where data collection is tightly controlled and all fields are complete, RWE studies must contend with potential biases from unrecognized confounders, selection bias, adherence bias, and confounding bias. Data quality issues include systematic omissions, misclassification, and the absence of generally agreed-upon standards for design, conduct, analysis, and reporting.
The biopharmaceutical industry is working to establish rigorous standards for regulatory-grade data quality. This includes setting standards for data provenance, documenting data origin and lineage, and validating structured data with chart notes to ensure consistency, completeness, and representativeness of target patient populations. Industry stakeholders are collaborating with organizations like the Friends of Cancer Research to create quality assessment standards and define minimum data sets.
Statistical Innovation and Future Applications
The growth of personalized medicine and complex treatment landscapes necessitates new statistical approaches for RWE studies. Traditional statistics applied to large patient populations may not work effectively for smaller populations common in rare diseases and personalized therapies. The FDA has indicated that synthetic control arms could help augment clinical data by reducing the number of subjects assigned to control arms in randomized trials or enabling smaller randomized trials.
Currently, approximately 2,000 oncology trials are listed on ClinicalTrials.gov, but only 3-4% of the patient population qualifies for participation. This recruitment challenge creates opportunities for RWE studies to provide valuable insights into treatment patterns and outcomes that traditional trials cannot capture.
Expanding Role in Healthcare Decision-Making
RWE is increasingly being used for regulatory approval decisions, postapproval monitoring of safety signals, payer coverage decisions, and outcomes-based contracting. The FDA predicts that greater use of RWE will result in safety and efficacy information becoming available sooner and help further inform regulatory decisions.
Looking ahead, RWE studies are expected to become increasingly important for assessing safety and effectiveness in real-world populations for regulatory purposes, comparing clinical outcomes in observational trials to determine optimal treatment strategies, identifying prescribing patterns for population health analyses, measuring resource utilization, and comparing economic outcomes to determine cost-effective treatment strategies.
While RWE will increasingly supplement post-approval RCTs, it is unlikely to replace phase 1-3 trials for most therapies. The combination of both RCTs and RWE trials can provide evidence that neither type alone can readily provide, with each approach addressing specific weaknesses and leveraging unique strengths in the evolving landscape of drug development and regulatory approval.
