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Adaptive seamless designs combine confirmatory testing, a domain of phase IIItrials, with features such as treatment or subgroup selection, typicallyassociated with phase II trials. They promise to increase the efficiency ofdevelopment programmes of new drugs, e.g. in terms of sample size and / ordevelopment time. It is well acknowledged that adaptive designs are moreinvolved from a logistical perspective and require more upfront planning, oftenin form of extensive simulation studies, than conventional approaches. Here wepresent a framework for adaptive treatment and subgroup selection using thesame notation, which links the somewhat disparate literature on treatmentselection on one side and on subgroup selection on the other. Furthermore, weintroduce a flexible and yet efficient simulation model that serves bothdesigns. As primary endpoints often take a long time to observe, interimanalyses are frequently informed by early outcomes. Therefore, all methodspresented accommodate both, interim analyses informed by the primary outcome oran early outcome. The R package asd, previously developed to simulate designswith treatment selection, was extended to include subpopulation selection(so-called adaptive enrichment designs). Here we describe the functionality ofthe R package asd and use it to present some worked-up examples motivated byclinical trials in chronic obstructive pulmonary disease and oncology. Theexamples illustrate various features of the R package providing at the sametime insights into the operating characteristics of adaptive seamless studies.

Seamless phase II/III clinical trials using early outcomes for treatment or subgroup selection: Methods and aspects of their implementation