A Physiologically Based Pharmacokinetic Modeling Approach to Predict Disease–Drug Interactions: Suppression of CYP3A by IL-6

Abstract

Elevated cytokine levels are known to downregulate expression and suppress activity of cytochrome P450 enzymes (CYPs). Cytokine-modulating therapeutic proteins (TPs) used in the treatment of inflammation or infection could reverse suppression, manifesting as TP-drug-drug interactions (TP-DDIs). A physiologically based pharmacokinetic model was used to quantitatively predict the impact of interleukin-6 (IL-6) on sensitive CYP3A4 substrates. Elevated simvastatin area under the plasma concentration-time curve (AUC) in virtual rheumatoid arthritis (RA) patients, following 100 pg/ml of IL-6, was comparable to observed clinical data (59 vs. 58%). In virtual bone marrow transplant (BMT) patients, 500 pg/ml of IL-6 resulted in an increase in cyclosporine AUC, also in good agreement with the observed data (45 vs. 39%). In a different group of BMT patients treated with cyclosporine, the magnitude of interaction with IL-6 was underpredicted by threefold. The complexity of TP-DDIs highlights underlying pathophysiological factors to be considered, but these simulations provide valuable first steps toward predicting TP-DDI risk.