MBMA is a combination of mathematical modeling and meta-analysis that integrates data from a wide range of literature and uses models to accurately describe time-effect or dose-effect relationships. Compared to meta-analysis, MBMA has the advantages of increasing the accuracy of prediction, assessing the entire time-effect process, establishing covariates models to correct for heterogeneity, and using simulations to predict efficacy under conditions not previously addressed in trials.
One of the features of this database is to provide a summary and analysis of the published clinical trial literature for various diseases. We will present the basic information on trial design, common clinical endpoints, baseline characteristics of participants, and covariates that may have potential clinical significance.
Another function of this database is the presentation of MBMA analysis results. Through the external Rshiny interactive app, users can explore the distribution of trial data, typical values of drug efficacy prediction and their confidence intervals, and the analysis results of any other secondary indicators.