The epidemiology of databases: Part III: The expanding uses of real-world evidence
Priscilla Velentgas, Ph.D.
Senior Director of Science, Aetion
Part I: Four principles of working with real-world data
Part II: Four principles of working with real-world evidence
In a recent comment letter to the U.S. FDA, Aetion outlined key considerations to guide the agency’s formal exploration of the use of real-world evidence (RWE) in regulatory decision-making. In Part I of this series, we identify key principles of working with real-world data (RWD). In Part II, we define the foundational principles of designing studies with RWD. And our series concludes with a look at the expanding uses of RWE.
Real-world evidence is of most use when it results from analyses that ask clinically meaningful questions and produce clinically meaningful results.
Clinical meaning is supported by the study of real-world, patient-centric outcomes. A randomized clinical trial (RCT) may assess a specific biomarker—bone mineral density, for example—while an analysis of RWD may look at an endpoint meaningful for both providers and patients, such as bone fractures.
Only certain types of RWD analyses, however, have the potential to generate clinically meaningful results. Those analyses include, but are not limited to:
- Measuring the effectiveness and safety of a medication within subgroups of all treated patients.
- Identifying subgroups and assessing the rates of safety and effectiveness outcomes among them to facilitate clinical decision-making.
- Identifying gaps in treatment and adherence patterns that may reduce the real-world effectiveness of medications.
- Generating evidence to support payer coverage decisions and to assist in the design of formularies appropriate for older adults, individuals with multiple chronic illnesses, and other populations that may be underrepresented in clinical trials.
- Generating evidence to align drug costs with clinical outcomes in value-based payment models.
Applications of RWE in the future
As science and technology evolve, however, RWE analyses have the potential to uncover even more clinically meaningful results that could be used to support regulatory decision-making across the product life cycle, including:
1. New Drug Applications (NDAs) and Biologics License Applications (BLAs)
While RCTs will remain the gold standard in evidence generation, RWE can enhance an NDA or BLA submission—and support primary product approval when historical controls and/or synthetic comparison groups are in place.
2. Supplemental New Drug Applications (sNDAs)
RWE can support secondary product indications such as indication expansion, a population expansion (for example, to the pediatric population or different disease stage), and efficacy claim expansion—particularly when approval is based on a single-arm interventional trial and when using a parallel assignment control arm is unethical or infeasible.
3. Accelerated approval pathways
RWE can support accelerated approval pathways that may initially approve a new drug based on a biomarker endpoint but then require post-marketing clinical endpoint studies.
4. Postmarket safety requirements and commitments
RWE can help a product developer meet FDA postmarket requirements and commitments.
5. Rapid response to safety signals by regulators and manufacturers
RWE can help facilitate a rapid regulatory response to a safety signal, for example, through coordination with FDA’s Sentinel Initiative or through a manufacturer’s rapid analysis of fit-for-purpose RWD.
6. Improved research and development efficiency
RWE has the potential to improve the overall efficiency of drug development by enabling product developers to gain information more rapidly on specific patient populations, diseases, conditions, and treatments.
As the field of RWE matures—particularly in light of the potential for an expanded range of applications—the foundational principles of working with RWD will guide that evolution in ways that increase confidence for stakeholders and benefit patients.