Physiological modeling of metabolic interactions

Purpose: Modeling metabolic interactions between chemicals can be a formidable model development task. Here I demonstrate a new approach and the capabilities of new tools to facilitate that development. Methods: Individual models of metabolic pathways are automatically merged and coupled to a template physiologically based pharmacokinetic (PBPK) model, using the GNU MCSim software. The global model generated is very efficient and able to simulate the interactions between a theoretically unlimited number of substances. Development time increases only linearly with the number of substances considered, while the number of possible interactions increases exponentially. Results: I show an example of application of that approach to the prediction of the kinetics of a mixture of 30 arbitrary chemicals. The qualitative and quantitative behavior of the corresponding pathway network is analyzed using Monte-Carlo simulations. In our example, the number of significant interactions, given the uncertainty and variability in pharmacokinetics and metabolism of those substances, is much lower than the theoretically possible number of interactions. Conclusion: The integrative approach to interaction modeling is efficient and can be extended beyond metabolic interactions. It relies on the availability of specific data on the rate constants of individual reactions. Such data could be obtained thought unconventional enzyme kinetics Experiments, or thought ab initio chemistry modeling of enzymatic reactions. We are currently exploring both approache