PS49: Advancing Rare Disease Drug Development with Totality of Evidence

Rare disease drug development faces significant hurdles due to small, heterogeneous patient populations, limited historical data, and often incomplete understanding of disease mechanisms. These complexities call for innovative approaches to evidence generation that extend beyond traditional clinical trial designs. The concept of "totality of evidence" has become a fundamental strategy in rare disease research, emphasizing the integration of diverse data sources such as clinical trial results, natural history studies, real-world evidence, and preclinical or biomarker data. Additionally, many rare diseases lack comprehensive knowledge of disease progression, necessitating the use of multiple endpoints to capture various dimensions of treatment effects. In this context, the totality of evidence across multiple outcome families is crucial to demonstrate the benefit of a medicinal product, especially the rare disease clinical trials are often underpowered due to small sample sizes. This session will present advanced statistical methodologies that address these unique challenges to advance drug development for rare diseases, including hypothesis testing strategies of multiple key outcomes to achieve overall power as well as significance for individual endpoints, Bayesian external information borrowing, and statistical challenges and practical solutions. It will feature case studies of real-world applications, illustrating how these methodologies have successfully supported regulatory submissions and informed clinical decision-making. Practical tools such as {gst} R package and R shiny app will also be demonstrated together with case studies.