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Pharmaceutics 2018, 10(1), 1; https://doi.org/10.3390/pharmaceutics10010001

Prediction of Drug-Drug Interactions with Bupropion and Its Metabolites as CYP2D6 Inhibitors Using a Physiologically-Based Pharmacokinetic Model

Department of Clinical Pharmacy and Pharmaceutical Management, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, China
These authors contributed equally to this work.
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Received: 31 October 2017 / Revised: 5 December 2017 / Accepted: 19 December 2017 / Published: 21 December 2017
(This article belongs to the Special Issue Preclinical Pharmacokinetics and Bioanalysis)
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Abstract

The potential of inhibitory metabolites of perpetrator drugs to contribute to drug-drug interactions (DDIs) is uncommon and underestimated. However, the occurrence of unexpected DDI suggests the potential contribution of metabolites to the observed DDI. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model for bupropion and its three primary metabolites—hydroxybupropion, threohydrobupropion and erythrohydrobupropion—based on a mixed “bottom-up” and “top-down” approach and to contribute to the understanding of the involvement and impact of inhibitory metabolites for DDIs observed in the clinic. PK profiles from clinical researches of different dosages were used to verify the bupropion model. Reasonable PK profiles of bupropion and its metabolites were captured in the PBPK model. Confidence in the DDI prediction involving bupropion and co-administered CYP2D6 substrates could be maximized. The predicted maximum concentration (Cmax) area under the concentration-time curve (AUC) values and Cmax and AUC ratios were consistent with clinically observed data. The addition of the inhibitory metabolites into the PBPK model resulted in a more accurate prediction of DDIs (AUC and Cmax ratio) than that which only considered parent drug (bupropion) P450 inhibition. The simulation suggests that bupropion and its metabolites contribute to the DDI between bupropion and CYP2D6 substrates. The inhibitory potency from strong to weak is hydroxybupropion, threohydrobupropion, erythrohydrobupropion, and bupropion, respectively. The present bupropion PBPK model can be useful for predicting inhibition from bupropion in other clinical studies. This study highlights the need for caution and dosage adjustment when combining bupropion with medications metabolized by CYP2D6. It also demonstrates the feasibility of applying the PBPK approach to predict the DDI potential of drugs undergoing complex metabolism, especially in the DDI involving inhibitory metabolites. View Full-Text
Keywords: physiologically based pharmacokinetic model; drug-drug interactions; bupropion; hydroxybupropion; threohydrobupropion; erythrohydrobupropion; inhibitory metabolites physiologically based pharmacokinetic model; drug-drug interactions; bupropion; hydroxybupropion; threohydrobupropion; erythrohydrobupropion; inhibitory metabolites
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Xue, C.; Zhang, X.; Cai, W. Prediction of Drug-Drug Interactions with Bupropion and Its Metabolites as CYP2D6 Inhibitors Using a Physiologically-Based Pharmacokinetic Model. Pharmaceutics 2018, 10, 1.

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