Abstract
The article by Lommerse et al. (2025) introduces vachette, a novel visualization technique that enhances the assessment and communication of pharmacometric model results. By aligning data from different covariate groups to a single reference curve through time and scale transformations, vachette enables all observations and simulations to be displayed in one cohesive and interpretable plot. This unified visualization helps both modelers and non-modelers better understand how covariate effects influence model predictions, evaluate model fit, and detect potential mis-specifications. Compared to traditional visual predictive checks (VPCs), vachette minimizes the need for data binning and stratification, providing a clearer, more intuitive, and efficient approach to assessing and communicating model performance within pharmacometric analyses.
Author(s): Jos Lommerse, Anna Largajolli, James Craig, Nele Plock, S. Y. Amy Cheung & Jeffrey R. Sachs
Publication date: Oct 13, 2025
Oncology, Cardiovascular and Metabolic Disease, Neurology and CNS Disorders, Infectious Disease, Pediatrics and Special Populations
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