Development of a Physiologically Based Pharmacokinetic Model to Predict Disease-Mediated Therapeutic Protein–Drug Interactions: Modulation of Multiple Cytochrome P450 Enzymes by Interleukin-6

Disease-mediated therapeutic protein–drug interactions have recently gained attention from regulatory agencies and pharmaceutical industries in the development of new biological products. In this study, we developed a physiologically based pharmacokinetic (PBPK) model using SimCYP to predict the impact of elevated interleukin-6 (IL-6) levels on cytochrome P450 (CYP) enzymes and the treatment effect of an anti-IL-6 monoclonal antibody, sirukumab, in patients with rheumatoid arthritis (RA). A virtual RA patient population was first constructed by incorporating the impact of systemic IL-6 level on hepatic and intestinal expression of multiple CYP enzymes with information from in vitro studies. Then, a PBPK model for CYP enzyme substrates was developed for healthy adult subjects. After incorporating the virtual RA patient population, the PBPK model was applied to quantitatively predict pharmacokinetics of multiple CYP substrates in RA patients before and after sirukumab treatment from a clinical cocktail drug interaction study. The results suggested that, compared with observed clinical data, changes in systemic exposure to multiple CYP substrates by anti-IL-6 treatment in virtual RA patients have been reasonably captured by the PBPK model, as manifested by modulations in area under plasma concentration versus time curves for midazolam, omeprazole, S-warfarin, and caffeine. This PBPK model reasonably captured the modulation effect of IL-6 and sirukumab on activity of CYP3A, CYP2C9, CYP2C19, and CYP1A2 and holds the potential to be utilized to assess the modulation effect of sirukumab on the metabolism and pharmacokinetics of concomitant small-molecule drugs in RA patients