Out of 10,000 known diseases or conditions, we only have cures and treatments for a small proportion of them. The cost for bringing a potential treatment from discovery to market has nearly doubled in the last 10 years and has now reached an astronomical amount of $2.6 billion. There is an urgent need to make drug development less time-consuming and less costly. Innovative trial designs and analyses such as Bayesian approach, which can be used to synthesize all available data including those from previous trials, expert opinions, and external data to guide the choice of trial design and increase efficiency, as laid out in the FDA’s Critical Path Initiative list are essential to meet this need. Bayesian applications in medical product development have gained popularity in the last few years. Despite many successes, the application across the various areas of drug development has been modest. This book will be the first to provide comprehensive coverage of Bayesian application across the span of medical product development from discovery to clinical trial to manufacturing with practical examples as illustration and computation codes to help readers implement the examples. We expect this book will have a wide appeal to statisticians, scientists, and clinicians working in drug development who are motivated to accelerate and streamline the drug development process as well students who aspire to work in this field.