Keywords: pediatric, extrapolation, Bayesian, rare disease, hierarchical
Pediatric drug development, limited by the nature of rare disease and the desire to protect children from unnecessary exposure to experimental drug, is often challenged with smaller sample size and insufficient data. Bayesian extrapolation, as a statistical tool, may be utilized to extend information from adequate and well-controlled studies in the adult (source) population to make inferences for the pediatric (target) population, as long as similarities in disease progression, response to intervention and PK/PD response between source and target population can be established. Similarly, information in the older children (source) may be extrapolate to younger children (target) using the same approach. Thus, the method may help reduce or even eliminate the need to conduct large clinical trials in pediatric population. In this presentation, we will discuss the use of a few Bayesian statistical methods including power prior and Bayesian hierarchical model for incorporating prior information from the adult population and in combination with pediatric trial data to make efficacy and safety inferences for the pediatric population.