Quantitative Assessment of Elagolix Enzyme-Transporter Interplay and Drug–Drug Interactions Using Physiologically Based Pharmacokinetic Modeling

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Abstract

Introduction: Elagolix is approved for the management of moderate-to-severe pain associated with endometriosis. The aim of this analysis was to develop a physiologically based pharmacokinetic (PBPK) model that describes the enzyme-transporter interplay involved in the disposition of elagolix and to predict the magnitude of drug–drug interaction (DDI) potential of elagolix as an inhibitor of P-glycoprotein (P-gp) and inducer of cytochrome P450 (CYP) 3A4. Methods: A PBPK model (SimCYP® version 15.0.86.0) was developed using elagolix data from in vitro, clinical PK and DDI studies. Data from DDI studies were used to quantify contributions of the uptake transporter organic anion transporting polypeptide (OATP) 1B1 and CYP3A4 in the disposition of elagolix, and to quantitatively assess the perpetrator potential of elagolix as a CYP3A4 inducer and P-gp inhibitor. Results: After accounting for the interplay between elagolix metabolism by CYP3A4 and uptake by OATP1B1, the model-predicted PK parameters of elagolix along with the DDI AUC∞ and Cmax ratios, were within 1.5-fold of the observed data. Based on model simulations, elagolix 200 mg administered twice daily is a moderate inducer of CYP3A4 (approximately 56% reduction in midazolam AUC∞). Simulations of elagolix 150 mg administered once daily with digoxin predicted an increase in digoxin Cmax and AUC∞ by 68% and 19%, respectively. Conclusions: A PBPK model of elagolix was developed, verified, and applied to characterize the disposition interplay between CYP3A4 and OATP1B1, and to predict the DDI potential of elagolix as a perpetrator under dosing conditions that were not tested clinically. PBPK model-based predictions were used to support labeling language for DDI recommendations of elagolix.

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Chiney, M. S., Ng, J., Gibbs, J. P., & Shebley, M. (2020). Quantitative Assessment of Elagolix Enzyme-Transporter Interplay and Drug–Drug Interactions Using Physiologically Based Pharmacokinetic Modeling. Clinical Pharmacokinetics, 59(5), 617–627. https://doi.org/10.1007/s40262-019-00833-6

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