Assessing the Performance of Adaptive Design Trials Based on Real Clinical Trial Data

• Activity Number: 416
• Type: Contributed
• Date/Time: Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Suvajit Samanta*+ and Weili He and Yiyun Tang
• Companies: Merck Research Laboratories and Merck & Co., Inc. and Pfizer Inc.
• Keywords: Adaptive design ; clinical trials ; simulation methodology ; nonparametric bootstrap ; permutation method

Abstract

Adaptive clinical trials hold the promise of drastically improving the clinical development process by optimizing the risk and benefit profiles for patients. The theory and potential benefits of adaptive trials have extensively been discussed in literature. However, little information has been presented on case studies of adaptive design scenarios and the potential gains in efficiency as compared to traditional trials. On that regard, simulations play an important role in assessing the performance of adaptive designs as it is often too complex to determine operating characteristics of adaptive designs, such as power, type I error, number of required patients in simple formulas. The simulation studies make many assumptions including treatment response curve, distribution of responses which are generally unknown at the beginning of clinical program or trial. This research assesses the performance of one adaptive design by simulating the adaptive design based on data from completed real clinical trial using permutation method or nonparametric bootstrap method. The proposed assessment is robust as it does not make any underlying assumptions with regard to treatment response curve.