  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 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.
