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

Abstract

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.

Keywords: MCP-Mod; adaptive designs; conditional rejection probability principle; generalized multiple contrast tests; proof-of-concept.