Physiologically Based Pharmacokinetic (PBPK) Modeling of Pitavastatin and Atorvastatin to Predict Drug-Drug Interactions (DDIs).

BACKGROUND: The disposition of statins varies and involves both metabolizing enzymes and transporters, making predictions of statin drug-drug interactions (DDIs) challenging. Physiologically based pharmacokinetic (PBPK) models have, however, demonstrated ability to predict complex DDIs.

OBJECTIVE: In this study, PBPK models of two statins (pitavastatin and atorvastatin) were developed and applied to predict pitavastatin and atorvastatin associated DDIs.

METHOD: Pitavastatin and atorvastatin PBPK models were developed using in vitro and human pharmacokinetic data in a population-based PBPK software (SimCYP® ) by considering the contribution of both metabolizing enzymes and transporters to their overall pharmacokinetics. The statin PBPK models and software's built-in or published models of inhibitors were used to predict DDIs under different scenarios.

RESULTS: The statin models reasonably predicted the observed exposure change due to Organic Anion Transporting Polypeptide (OATP) 1B1 polymorphism or clinical DDIs with itraconazole, erythromycin, and gemfibrozil, while under-predicted the observed DDIs caused by rifampin and cyclosporine. Further analysis demonstrated that OATP1B1 inhibition by rifampin or cyclosporine in the existing inhibitor models needs to be approximately tenfold stronger to recapitulate the observed DDI with these two inhibitors.

CONCLUSION: Through quantitative assessment of the effect of OATP1B1 genetic polymorphism and inhibitors of transporters and metabolizing enyzmes via PBPK modeling, we confirmed the importance of OATP1B1 in the disposition of these two statins, and explored potential causes for under-prediction of the inhibitory effect of rifampin and cyclosporine.