Considerations and Bayesian Applications in Pharmaceutical Development for Rare Diseases
Clinical development for rare diseases often face multisided challenges: lack of well-defined clinical endpoints, poor understanding of treatment effect, small but highly diverse patient populations, and drastically variable patient enrollment rates across investigational sites, just to name a few. Most of these challenges can be addressed through more efficient and innovative trial designs, such as adaptive designs and usage of biomarkers. Bayesian statistics can provide a natural and systematic tool to assist such designs through interim analysis or borrowing information from historical or external data. This chapter will introduce the background of rare disease definition and its regulations. Then, it will discuss the unique clinical development considerations for rare diseases and small sample size trials. Examples that showcase innovative trial designs and novel analytical methodologies, especially Bayesian statistics, will then be presented to illustrate their implementation in real clinical trial settings. Finally, it will summarize the challenges and future directions in rare disease clinical development research.