In the early stages of drug development there is often uncertainty about the most promising among a set of different treatments. In order to ensure the best use of resources in such situations it is important to decide which, if any, of the treatments should be taken forward for further testing. An efficient solution to this problem are multi-arm clinical trials in which several active treatments are compared to a common control group. By comparing several treatments within one trial the sample size and duration required tends to be markedly smaller than if each treatment would have been evaluated
separately. For added efficiency it is desirable to monitor the trial at a series of interim analyses in order to allow early stopping if efficacy is quickly established and similarly to eliminate ineffective treatments early. In confirmatory studies these designs are also useful as it has been shown that using two doses instead of a single dose can markedly improve the study's success probability.

This project aims to develop statistical methods to investigate how these, so called multi-arm multi-stage trials, can best be designed and analysed.