Drug development involving small populations such as pediatric and rare disease present unique opportunities and challenges. Although there are several incentive programs to expedite the drug approval process of rare diseases, the same regulatory (FDA) approval standard applies as for common conditions ie substantial evidence regarding the effectiveness and safety of the drug. Similarly, FDA requires substantial evidence to support the safe and effective use of drugs in pediatric populations conditional on prior evidence from the adult population. Recruiting pediatric patients and patients with rare conditions is challenging due to limited number of patients, ethical concerns, as well as scheduling and logistical considerations for patients and caregivers. Given the requirement for substantial evidence coupled with limited access to patients in small population, innovative design and analyses are much needed to leverage historical data when appropriate, optimize the value of patient data, and minimize patient risk. In this talk, we will discuss several methods of borrowing historical data and use of Bayesian methods in small populations as well as highlight applications.