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Conference

ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop

Conference: ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop

Date: September 16 - 18, 2026

Location: Rockville, MD

Matt Zierhut will co-lead a roundtable discussion with Jonathan French from Johnson & Johnson, at the 2026 American Statistical Association (ASA) Biopharmaceutical Section Regulatory-Industry Statistics Workshop (RISW) on September 17, 2026. The workshop is one of the premier forums where leaders from the pharmaceutical industry, academia, and the U.S. Food and Drug Administration (FDA) come together to discuss advances in regulatory science, statistical methods, and drug development. It is sponsored by the American Statistical Association’s Biopharmaceutical Section in cooperation with the FDA Statistical Association.

Where to hear Certara insights and expertise

September 17, 2026 | 11:45am - 1:00pm
Use of Model-Based Meta-Analysis (MBMA) to Better Integrate Multiple Data Sources in Drug Development,

Presenters: Matt Zierhut, Certara and Jonathan French, Johnson & Johnson

Matt and Jonathan’s roundtable, “Use of Model-Based Meta-Analysis (MBMA) to Better Integrate Multiple Data Sources in Drug Development,” is organized by the Statistics and Pharmacometrics (SxP) Special Interest Group (SIG). The session will focus on how Model-Based Meta-Analysis (MBMA) enables sponsors to integrate evidence across clinical trials and external data sources to improve development decisions, optimize trial design, and strengthen regulatory strategies. The discussion also supports the SxP Special Interest Group’s mission of fostering closer collaboration between statisticians and pharmacometricians while advancing the use of quantitative methods in model-informed drug development (MIDD).

Find additional details on the workshop and view the complete program here.

Matthew Zierhut

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.

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