Agenda

Clinical development programs are too often designed around population averages that can obscure meaningful sex- and hormone-related biological variability. Hormonal dynamics, sex-based covariates, contraceptive use, and differences in cellular pathways can influence exposure, response, safety, and study outcomes. Model-informed approaches can help development teams account for these variables earlier, before critical study design decisions are locked.

This interactive roundtable will explore how modeling and simulation can help teams build confidence in target selection, anticipate off-target safety considerations, plan biomarker and PK/PD sampling at the right time, and support more efficient clinical and regulatory strategies. Through discussion with experts in pharmacometrics, biostatistics, regulatory strategy, and clinical operations, participants will consider where modeling can reduce uncertainty, sharpen FDA engagement, and help development teams design studies that better reflect the populations they aim to serve.