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Adaptive dose-response studies to establish proof-of-concept in learning-phase clinical trials.

Shiyang MaMichael P McDermott
Published in: Biometrical journal. Biometrische Zeitschrift (2021)
In learning-phase clinical trials in drug development, adaptive designs can be efficient and highly informative when used appropriately. In this article, we extend the multiple comparison procedures with modeling techniques (MCP-Mod) procedure with generalized multiple contrast tests (GMCTs) to two-stage adaptive designs for establishing proof-of-concept. The results of an interim analysis of first-stage data are used to adapt the candidate dose-response models and the dosages studied in the second stage. GMCTs are used in both stages to obtain stage-wise p -values, which are then combined to determine an overall p -value. An alternative approach is also considered that combines the t -statistics across stages, employing the conditional rejection probability principle to preserve the Type I error probability. Simulation studies demonstrate that the adaptive designs are advantageous compared to the corresponding tests in a nonadaptive design if the selection of the candidate set of dose-response models is not well informed by evidence from preclinical and early-phase studies.
Keyphrases
  • clinical trial
  • case control
  • magnetic resonance
  • stem cells
  • phase ii
  • electronic health record
  • open label
  • big data
  • machine learning
  • cell therapy
  • bone marrow
  • artificial intelligence
  • virtual reality