Real World Evidence Scientific Working Group

Phase I:

  • Team 1: The Current Landscape in Biostatistics of Real-World Data and Evidence: Clinical Study Design and Analysis (2021), Statistics in Biopharmaceutical Research (SBR)
  • Team 2: Biostatistical considerations when using RWD and RWE in Clinical Studies for Regulatory Purposes: A Landscape Assessment (2021), SBR.
  • Team 3: The Current Landscape in Biostatistics of Real-World Data and Evidence: Causal Inference Frameworks for Study Design and Analysis (2021), SBR.

Phase II:

  • Team 1: Estimands in Real-World Evidence Studies (2023), SBR.
  • Team 2: Statistical Consideration for Fit-For-Use Real-World Data to Support Regulatory Decision Making in Drug Development (2023), SBR.
  • Team 3: Examples of Applying Causal Inference Roadmap to RWE Clinical Studies (2023), SBR. 

 

Phase III:

  • Team 1: Sensitivity Analysis for Unmeasured Confounding in Medical Product Development and Evaluation Using Real World Evidence (2025), SBR.
  • Team 2:
    • Use of Real-World Data and Real-World Evidence in Rare Disease Drug Development: A Statistical Perspective (2025), Clinical Pharmacology & Therapeutics (CPT).
    • Challenges and Possible Strategies to Address Them in Rare Disease Drug Development: A Statistical Perspective (2025), CPT.
  • Team 3:
    • Decentralized Clinical Trials in the Era of Real-World Evidence: A Statistical Perspective (2025), Clinical and Translational Science (CTS).
    • Decentralized Clinical Trials in the Era of Real-World Evidence: A Critical Assessment of Recent Experiences (2025), CTS.

Phase IV:

  • Team 1:
    • External Controls in Drug Development: Regulatory Lessons, Risk Patterns, Statistical Methods, and a Sponsor-Facing Evaluation Framework (in preparation)
    • Externally Controlled Trials: A Review of Design and Borrowing Through a Causal Lens (in preparation)
  • Team 2:
    • Methodological and Regulatory Considerations for Causal AI in Drug Development (2026), npj Digital Medicine.
    • Statistical Considerations with the Use of AI/ML for Generating RWE in Drug and Biologics Product Development and Evaluation (in preparation)
  • Team 3: Negative Control for Generating Robust Real-World Evidence in Drug Development and Regulatory Decision-Making (in preparation)