Data-driven personalization of a physiologically based pharmacokinetic model for caffeine: A systematic assessment.

ABSTRACT: Physiologically based pharmacokinetic (PBPK) models have been proposed as a tool for more accurate individual pharmacokinetic (PK) predictions and model-informed precision dosing, but their application in clinical practice is still rare. This study systematically assesses the benefit of using individual patient information to improve PK predictions. A PBPK model of caffeine was stepwise personalized by using individual data on (1) demography, (2) physiology, and (3) cytochrome P450 (CYP) 1A2 phenotype of 48 healthy volunteers participating in a single-dose clinical study. Model performance was benchmarked against a caffeine base model simulated with parameters of an average individual. In the first step, virtual twins were generated based on the study subjects' demography (height, weight,

SUBMITTER: Fendt R 

PROVIDER: S-EPMC8302243 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature