Pediatric drug development is often slowed by small sample sizes, recruitment challenges, and regulatory complexity. When a global sponsor faced an incomplete pediatric study, the MMS biostatistics team used KerusCloud®, a powerful simulation-driven study design platform, to assess the feasibility and success probability of a Bayesian extrapolation approach.

By virtually testing study assumptions, MMS confirmed that combining adult and pediatric data through Bayesian “dynamic borrowing” could deliver robust, evidence-based results helping the sponsor demonstrate efficacy, de-risk development, and meet EMA recommendations under tight timelines.

This case study reveals how MMS transformed uncertainty into clarity through data-driven simulations and Bayesian modeling that supported confident regulatory decision-making.

Key Benefits / What You’ll Learn:

• Understand how Bayesian extrapolation can bridge adult and pediatric data for efficacy validation.
• See how KerusCloud® simulations assess feasibility and success probabilities before analysis begins.
• Learn how dynamic borrowing improves precision and reduces reliance on underpowered pediatric datasets.
• Discover how MMS experts delivered a regulatory-ready analysis that met EMA timelines.

Created by MMS statistical experts with deep experience in Bayesian modeling and pediatric extrapolation, leveraging over a decade of successful global submissions supported by KerusCloud®.