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.