Model-Based Meta-Analysis (MBMA) has emerged as a powerful tool for integrating data across clinical trials and generating insights that efficiently inform drug development and regulatory decision-making. This webinar will unpack two distinct MBMA methodologies: modeling absolute outcomes and relative treatment effects.
Using a mix of simulated and real-world case studies, this webinar will cover:
- Choosing the Right Modeling Approach
When to apply absolute outcome vs. relative effect models based on clinical and development objectives. - Maximizing Impact with Covariates
Differentiating between prognostic and predictive covariates and how they influence model applications, plus best practices for covariate exploration. - Informing Decisions with Simulations
How MBMA-based simulations can improve trial design, support treatment comparisons, and guide go/no-go decisions. - Ensuring Model Credibility
Techniques for evaluating model fit and credibility to ensure reliable, decision-ready results. - Applying MBMA in the Real World
Case studies showing how MBMA informs regulatory submissions, product strategy, and development planning.
Register now
Matt Zierhut, PhD MBA
Vice President, MBMA Capability Lead, Certara Drug Development Solutions
Matt advances the integration of published clinical outcomes data into development decisions and commercial and regulatory strategy via model-based meta-analysis (MBMA). Matt works closely with clinical development teams to ensure MBMA is leveraged for optimal impact when making the most critical decisions.
Register now
