Physiologically based toxicokinetic models for prediction of complex metabolic interactions between chemical in mixtures
Résumé
The emergence of metabolic interactions during in vivo co-exposures depends on the concentrations of mixture components actually delivered to the metabolizing cells. For simulation and prediction purposes, physiologically based pharmacokinetic (PBPK) models have been used successfully for quite a while to predict such concurrent internal exposures. However, a classical PBPK framework alone cannot address the complexity of metabolism and its receptor mediated modulations for more than a handful of interacting chemicals. A solution to that problem is to integrate PBPK and systems biology modeling. We demonstrate here such an approach and present the software tools we have developed. Our software (an extension of GNU MCSim) automatically merges metabolic pathways models for individual chemicals and couples them to a template PBPK model. The transport and metabolism models generated are very efficient and can simulate interactions between a theoretically unlimited number of substances at tissue levels. We use a fine-grain description of reactions, so that development and computation time increases only linearly with the number of substances considered, even though the number of possible interactions increases exponentially. Several examples of application to the prediction of the joint kinetics of mixtures up to a hundred of chemicals are given. The efficient parameterization of such models remains an issue which we discuss. Our integrative approach can be extended beyond metabolic interactions, into the realm of cellular effects.