PBPK modelling of inter-individual variability in the pharmacokinetics of environmental chemicals

International audienceGeneric PBPK models, applicable to a large number of substances, coupled to parameter databases and QSAR modules, are now available for predictive modelling of inter-individual variability in the absorption, distribution, metabolism and excretion of environmental chemicals. When needed, Markov chain Monte Carlo methods and multilevel population models can be jointly used for a Bayesian calibration of a PBPK model, to improve our understanding of the determinants of population heterogeneity and differential susceptibility. This article reviews those developments and illustrates them with recent applications to environmentally relevant questions

VIVD: Virtual in vitro distribution model for the mechanistic prediction of intracellular concentrations of chemicals in in vitro toxicity assays

In vitro toxicity testing routinely uses nominal treatment concentrations as the driver for measured toxicity endpoints. However, test compounds can bind to the plastic of culture vessels or interact with culture media components, such as lipids and albumin. Additionally, volatile compounds may partition into the air above culture media. These processes reduce the free concentrations of compound to which cells are exposed. Models predicting the freely dissolved concentrations by accounting for these interactions have been published. However, these have only been applied to neutral compounds or assume no differential ionisation of test compounds between the media and cell cytoplasm. Herein, we describe an in vitro distribution model, based on the Fick-Nernst Planck equation accounting for differential compound ionisation in culture medium and intracellular water. The model considers permeability of ionised and unionised species and accounts for membrane potential in the partitioning of ionised moieties. By accounting for lipid and protein binding in culture medium, binding to cell culture plastic, air-partitioning, and lipid binding in the cell, the model can predict chemical concentrations (free and total) in medium and cells. The model can improve in vitro in vivo extrapolation of toxicity endpoint by determining intracellular concentrations for translation to in vivo