Progress in the field of medical research requires further development of clinical trial methodology to overcome the challenges resulting from small patient populations and restricted resources.
Classical single-stage designs with fixed sample sizes do not allow for interim analyses or design modifications. In contrast, adaptive designs adhere to established quality criteria while providing flexibility when conducting a clinical trial. In the face of new discoveries or information collected in the course of a trial, sample size adjustment, the selection of the target population and further design modifications can be performed. This enhances the chance of success of a clinical trial. Besides adaptive designs, classical approaches may be replaced or complemented by Bayesian methods. In a Bayesian approach prior knowledge can be efficiently included and hence the amount of information utilized in statistical analyses is increased. Furthermore, Bayes procedures allow the results of a statistical evaluation to be displayed very clearly.
Modern approaches, such as adaptive designs and Bayesian designs overcome the challenges in clinical research due to enhanced flexibility and efficiency. In addition, both approaches can be combined.