Design and Analysis of Clinical Trials with Biologics Using Dose Time Response Models

• Activity Number: 191
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Markus Reiner Lange* and Heinz Schmidli
• Companies: Novartis Pharma AG and Novartis Pharma AG
• Keywords: clinical trial ; monoclonal antibody ; KPD model ; Bayesian inference ; nonlinear regression ; experimental design

Abstract

Biologics such as monoclonal antibodies are increasingly and successfully used for the treatment of many chronic diseases. Semi-mechanistic nonlinear models are needed to adequately describe the dose-time response relationship for such drugs. We consider the optimal allocation of patients to doses in a planned clinical trial for a monoclonal antibody, in order to learn most about the nonlinear dose-time-response model. To characterize a design as optimal, various approaches have been introduced. Classical optimal design theory aims to maximize the Fisher information as an equivalent to minimizing the variance of the estimator. In the Bayesian framework, it is most common to find designs which maximize the expected Kullback-Leibler difference between prior and posterior of the model parameters. Due to heavy computational challenges, the latter is hardly used in clinical praxis. We will show approaches to tackle this problem, see how they compare to classical optimal designs and further demonstrate how to apply this concept for finding optimal clinical trial designs for monoclonal antibodies. For illustration, we will discuss the design of a clinical trial in patients with urticaria.