  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
(CRP) principle to preserve the Type I error probability. Simulation studies
demonstrate that the adaptive designs are advantageous compared to the
corresponding tests in a non-adaptive design if the selection of the candidate
set of dose-response models is not well informed by evidence from preclinical
and early-phase studies.
