ABSTRACT
This chapter begins with a brief overview of the drug development process. It discusses the opportunities and challenges of applying Bayesian statistics in drug development. The Bayesian system provides a formal framework to combine prior information with current data to make inferences about a quantity of interest. In addition, the Bayesian approach provides great flexibility to update inferences each time new data become available. Bayesian statistics has made significant inroads in drug development, notably in clinical trial design and analysis. Central to the objection to the Bayesian method is its requirement of a prior distribution, which is based on expert opinions and historical data. To fully capitalize on the benefits of the Bayesian approach, however, it is essential to develop best practices of Bayesian statistics, gain consensus among sponsors and regulators, and continue demonstration of the utilities of Bayesian in all aspects of drug development.
