Using Modeling & Simulation in Duchenne to Build More Efficient, Informative Clinical Trials & Reduce Development Uncertainty

• Characterizing disease progression in Duchenne using longitudinal natural history and clinical trial data to better understand variability, trajectories, and relationships across clinically meaningful outcomes
• Using disease progression models and clinical trial simulation to inform decisions around endpoint selection, eligibility criteria, study duration, sample size, and other key trial design assumptions
• Applying model-informed drug development approaches to reduce development uncertainty, support more evidence-based decision-making, and strengthen regulatory interactions

Speakers:

Paige Martin

Associate Scientific Director

Critical Path Institute (C-Path)