Inter-phenotypic differences in CYP2C9 and CYP2C19 metabolism: Bayesian meta-regression of human population variability in kinetics and application in chemical risk assessment

Quantifying variability in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. In this context, genetic polymorphisms cytochromes P450 (CYPs) drive inter-phenotypic differences may result reduction or increase metabolism of drugs other xenobiotics. Here, an extensive literature search was performed identify PK data probe substrates the human polymorphic isoforms CYP2C9 CYP2C19. Relevant from 158 publications were extracted markers chronic exposure (clearance area under plasma concentration-time curve) analysed using Bayesian meta-regression model. Enzyme function (EF), driven by across range allozymes present poor metabolisers (EMs PMs), fraction metabolised (Fm), identified as exhibiting highest impact on metabolism. The model provided good predictions such differences. Integration population distributions estimates EF Fm allowed derivation CYP2C9- CYP2C19-related UFs which ranged 2.7 12.7, above default factor TK (3.16) PMs major (Fm >60%). These results provide pathway-related conservative silico options integrate CYP2C19 vitro kinetic evidence absence data. future development quantitative extrapolation models is discussed with particular attention integrating vivo