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Real-world evidence to support regulatory decision-making for medicines: Considerations for external control arms.

Mehmet BurcuNancy A DreyerJessica M FranklinMichael D BlumCathy W CritchlowEleanor M PerfettoWei Zhou
Published in: Pharmacoepidemiology and drug safety (2020)
Randomized clinical trials (RCTs) are the gold standard in producing clinical evidence of efficacy and safety of medical interventions. More recently, a new paradigm is emerging-specifically within the context of preauthorization regulatory decision-making-for some novel uses of real-world evidence (RWE) from a variety of real-world data (RWD) sources to answer certain clinical questions. Traditionally reserved for rare diseases and other special circumstances, external controls (eg, historical controls) are recognized as a possible type of control arm for single-arm trials. However, creating and analyzing an external control arm using RWD can be challenging since design and analytics may not fully control for all systematic differences (biases). Nonetheless, certain biases can be attenuated using appropriate design and analytical approaches. The main objective of this paper is to improve the scientific rigor in the generation of external control arms using RWD. Here we (a) discuss the rationale and regulatory circumstances appropriate for external control arms, (b) define different types of external control arms, and (c) describe study design elements and approaches to mitigate certain biases in external control arms. This manuscript received endorsement from the International Society for Pharmacoepidemiology (ISPE).
Keyphrases
  • decision making
  • clinical trial
  • healthcare
  • machine learning
  • physical activity
  • mass spectrometry
  • deep learning