In drug development, making informed, data-driven decisions amidst variability across data sources and trials is a significant challenge. Model-Based Meta-Analysis (MBMA) addresses this by offering a flexible and powerful tool to handle this variability, making it more adaptable than traditional methods. Incorporating MBMA into your strategies helps establish market differentiation targets, design cost-effective trials, and quantify the probability of technical success.
In this on-demand webinar, “MBMA: Optimizing Drug Development with Aggregate Clinical Trial Data and Predictive Models,” Matt Zierhut shares insights on using clinical trial and real-world data. You’ll learn how the Codex tool facilitates exploration and access to organized, up-to-date clinical trial databases, crucial for timely decisions.
The webinar showcases real-world examples, including non-small cell lung cancer, rheumatoid arthritis, and weight loss, demonstrating how MBMA and the Codex tool address development questions. You’ll see how MBMA helps analyze market data, design cost-effective trials, and iteratively quantify technical success probability.
Case studies highlight MBMA’s practical applications. For instance, in non-small cell lung cancer, MBMA analyzes standard care data for objective response rate (ORR) and overall survival (OS), developing models to predict treatment success and simulate scenarios. In rheumatoid arthritis, MBMA focuses on phase two and three trials, using dose-response plots to address safety, efficacy, endpoints, and trial strategies.
By viewing this webinar, you’ll gain insights into how MBMA can enhance critical decisions and provide a deeper understanding of where a new compound could compete in the market.
