A Physiologically Based Pharmacokinetic Modeling Approach to Predict Disease–Drug Interactions: Suppression of CYP3A by IL‐6. Issue 2 (10th April 2013) - Machavaram, K K; Almond, L M; Rostami‐Hodjegan, A; Gardner, I; Jamei, M; Tay, S; Wong, S; Joshi, A; Kenny, J R
<x xml:space="preserve">Abstract</x> 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. Clinical Pharmacology & Therapeutics (2013); 94 2, 260–268. doi:10.1038/clpt.2013.79