How to Optimize Mouse Clinical Trials (MCTs) Through Statistical Endpoints and Study Design
Mouse clinical trials (MCT) using PDX models are a predictive and powerful platform to determine drug efficacy and discover and validate biomarkers. To fully optimize the design and use of MCTs current endpoint-based statistical methods need to be replaced. New methods are needed which fully utilize the array of data generated from these clustered longitudinal studies.
This White Paper presents a robust statistical framework moving beyond traditional analyses to fully optimize MCT use and data. Analysis using our published linear mixed models (LMM) is presented through case studies, which leverage tumor growth and drug response heterogeneity between individual models and mice to unlock the full power of MCTs.
Download This White Paper to Understand:
- How LMM analysis of MCT datasets allows optimization of MCT study design, including determining the number of PDX and mice per model needed
- How to quantify drug efficacy and move past conventional survival analyses to evaluate drug effect using LMMs
- How to use MCTs and LMM analysis to discover and validate biomarkers as well as reinterpreting clinical trial results