Introduction to MBMA
The Model-Based Meta-Analysis sub-Special Interest Group (MBMA sub-SIG) of the Statistics and Pharmacometrics Special Interest group (SxP SIG) held an Introduction to MBMA webinar on 26th January, 2021.
The Model-Based Meta-Analysis sub-Special Interest Group (MBMA sub-SIG) of the Statistics and Pharmacometrics Special Interest group (SxP SIG) held an Introduction to MBMA webinar on 26th January, 2021. It was organized by Marion Bouillon-Pichault and Matt Zierhut of the MBMA subgroup. The webinar enabled attendees to understand what MBMA is and presented some examples showing the impact it can have in drug development and other critical business decisions. It was a very well attended session with over 250 engaged attendees.
Abstract
As landscapes for the treatment of many diseases have grown increasingly competitive and costs to conduct clinical trials have soared, it is critical to understand the landscape of available treatments, as well as the probability that a specific compound could compete successfully in this market.
Model-based meta-analysis (MBMA) is a tool for integrating prior knowledge, both public and proprietary, and for using it to inform discovery and development decisions. As in traditional meta-analysis, MBMA allows one to more precisely quantify a treatment effect by incorporating data from multiple studies. Inclusion of model parameters further enables quantification and explanation of variability observed across trials by accounting for differences in effect modifiers, such as treatments, doses, time, population characteristics, etc. Thus, MBMA is a powerful tool for predicting new, potentially interesting clinical scenarios through clinical trial simulation. Additionally, applying the MBMA to perform simulations can improve strategic decision-making by projecting the likelihood of achieving differentiable efficacy and/or safety.
The webinar will enable you to understand what MBMA is and will present some examples showing the impact it can have in drug development and other critical business decisions.