  One of the challenges in the design of confirmatory trials is to deal with
uncertainties regarding the optimal target population for a novel drug.
Adaptive enrichment designs (AED) which allow for a data-driven selection of
one or more pre-specified biomarker subpopulations at an interim analysis have
been proposed in this setting but practical case studies of AEDs are still
relatively rare. We present the design of an AED with a binary endpoint in the
highly dynamic setting of cancer immunotherapy. The trial was initiated as a
conventional trial in early triple-negative breast cancer but amended to an AED
based on emerging data external to the trial suggesting that PD-L1 status could
be a predictive biomarker. Operating characteristics are discussed including
the concept of a minimal detectable difference, that is, the smallest observed
treatment effect that would lead to a statistically significant result in at
least one of the target populations at the interim or the final analysis,
respectively, in the setting of AED.
