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When Context Is Hard to Come By: External Comparators and How to Use Them.

Christina MackJennifer B ChristianEmma BrinkleyEdward J WarrenMarni HallNancy A Dreyer
Published in: Therapeutic innovation & regulatory science (2020)
External comparators, also referred to as historical or synthetic controls, present transformational opportunities for broad context and insights alongside clinical research results. The recent confluence of access to quality real-world data (RWD), advanced epidemiologic methods, and legislative directives to regulators for expanded use of RWD is increasing interest in real-world external comparators, opening the door to achieve broader generalizability and learn more, faster. In this less standardized area of research, tailored scientific methodology must be applied for external comparators to accomplish clinical development objectives. Here, we describe methodological considerations for design and illustrate how RWD comparators have been used for regulatory and reimbursement decisions.
Keyphrases
  • transcription factor
  • big data
  • electronic health record
  • machine learning
  • quality improvement
  • artificial intelligence