Keywords: Bayesian framework, hHierarchical modeling, clinical trials, historical data
Pediatric trials are an important component of drug development and are typically conducted after the efficacy and safety has been established in adult population. Many disease areas are presented with inherent difficulties in conducting large pediatrics trials making such development highly challenging. The timing of pediatric trials after adult trials allows for utilization of prior information and can help enhance efficiencies. Bayesian framework can provide analytical avenues to effectively utilize historical information in design and analysis and enhance efficiencies in terms of sample size and power. In this presentation, we will discuss some practical scenarios where Bayesian framework can provide a reasonable path forward to demonstrate efficacy requirements for pediatric program. There are different ways to incorporate historical information and we will focus on Bayesian hierarchical model (Schoenfeld et al., 2009) and provide few extensions of this framework as well as examine sensitivity of underlying assumptions.