ABSTRACT
In this chapter, we explore some of the computational tools of Bayesian pharmaceutical development. After providing a general overview of the concepts underlying and motivating modern Bayesian computation, we delve into statistical software commonly used to get the job done: the statistical programming language R and the probabilistic programming language JAGS. After introducing these, we provide concrete implementations of three commonly used models in pharmaceutical drug development. We conclude with two sections on commonly encountered problems in Bayesian pharmaceutical development: prior elicitation and sample size determination.
