  A new approach to adaptive design of clinical trials is proposed in a general
multiparameter exponential family setting, based on generalized likelihood
ratio statistics and optimal sequential testing theory. These designs are easy
to implement, maintain the prescribed Type I error probability, and are
asymptotically efficient. Practical issues involved in clinical trials allowing
mid-course adaptation and the large literature on this subject are discussed,
and comparisons between the proposed and existing designs are presented in
extensive simulation studies of their finite-sample performance, measured in
terms of the expected sample size and power functions.
