概述

What can existing clinical trial evidence tell you about the potential of your next drug candidate, and how can you use that evidence to make better development decisions?

Join Certara experts Matt Zierhut and Roman Casciano to explore how publicly available clinical trial evidence, curated through CODEX Analytics and analyzed using model-based meta-analysis (MBMA), can provide quantitative insights to support drug development decisions.

See how CODEX helps teams identify relevant studies, explore treatment outcomes, compare therapies, and uncover evidence gaps. Learn how MBMA builds on that evidence to characterize treatment effects and dose-response relationships, benchmark treatment performance, and evaluate development scenarios.

Through real-world examples, Matt and Roman will show how these approaches can inform dose selection, clinical trial design, treatment differentiation, development strategy, and regulatory interactions. They will also discuss how CODEX, customized databases, and quantitative analyses can complement internal databases, AI-enabled curation, and data science capabilities.

点击报名

Key learning objectives:

How CODEX turns clinical trial evidence into curated, analysis-ready data.
How MBMA characterizes treatment effects, dose-response relationships, and development scenarios.
How these approaches can inform dose selection, trial design, and treatment benchmarking.
How MBMA can support regulatory interactions and evidence generation.
How external evidence can complement internal AI and data science capabilities.

Who should attend

This webinar is designed for professionals who use clinical trial evidence to guide development decisions, including:

Pharmacometrics and Quantitative Sciences: MBMA, PK/PD modeling, exposure-response analysis, and quantitative decision-making
Clinical Pharmacology and Clinical Development: Dose selection, trial design, treatment differentiation, and development strategy
Regulatory Affairs and Regulatory Science: Model-informed evidence generation, regulatory strategy, and quantitative justification
Biostatistics and Biometrics: Evidence synthesis, comparative effectiveness, and quantitative analysis
HEOR, Market Access, and Medical Affairs: Comparative evidence, treatment outcomes, and evidence generation planning
Data Science and AI: Clinical trial databases, AI-assisted curation, evidence integration, and advanced analytics
Therapeutic Area and R&D Leadership: Clinical development strategy, portfolio decisions, and evidence-based decision-making