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Predicting Nonlinear Pharmacokinetics of Omeprazole Enantiomers and Racemic Drug Using Physiologically Based Pharmacokinetic Modeling and Simulation: Application to Predict Drug/Genetic Interactions

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ABSTRACT

Purpose

The objective of this study is to develop a physiologically-based pharmacokinetic (PBPK) model for each omeprazole enantiomer that accounts for nonlinear PK of the two enantiomers as well as omeprazole racemic drug.

Methods

By integrating in vitro, in silico and human PK data, we first developed PBPK models for each enantiomer. Simulation of racemic omeprazole PK was accomplished by combining enantiomer models that allow mutual drug interactions to occur.

Results

The established PBPK models for the first time satisfactorily predicted the nonlinear PK of esomeprazole, R-omeprazole and the racemic drug. The modeling exercises revealed that the strong time-dependent inhibition of CYP2C19 by esomeprazole greatly altered the R-omeprazole PK following administration of racemic omeprazole as in contrast to R-omeprazole given alone. When PBPK models incorporated both autoinhibition of each enantiomer and mutual interactions, the ratios between predicted and observed AUC following single and multiple dosing of omeprazole were 0.97 and 0.94, respectively.

Conclusions

PBPK models of omeprazole enantiomers and racemic drug were developed. These models can be utilized to assess CYP2C19-mediated drug and genetic interaction potential for omeprazole and esomeprazole.

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Abbreviations

ADME:

Absorption, distribution, metabolism and excretion

ASA:

Automated sensitivity analysis

CLint :

Intrinsic clearance

DDI:

Drug-drug interaction

EM:

Extensive metabolizers

HLM:

Human liver microsomes

PBPK:

Physiologically based pharmacokinetic modeling

PK:

Pharmacokinetics

PM:

Poor metabolizers

TDI:

Time-dependent inhibition

Vss:

Volume of distribution at steady state

WT:

Wild type

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ACKNOWLEDGMENTS AND DISCLOSURES

The authors would like to thank Professor Amin Rostami-Hodjegan from the University of Manchester for his valuable scientific input. This project was supported by FDA’s Critical Path Fellowship. This project was also supported in part by an appointment to the ORISE Research Participation Program at the Center for Drug Evaluation and Research administered by the Oak Ridge Institute for Science and Education through an agreement between the U.S. Department of Energy and CDER. The views presented in this manuscript are those of authors and do not necessarily reflect the official view of the FDA.

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Authors and Affiliations

  1. Office of Clinical Pharmacology, Office of Translational Sciences Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, Maryland, 20993, USA

    Fang Wu, Ping Zhao, Shiew-Mei Huang, Edward D. Bashaw & Sue-Chih Lee

  2. SIMCYP Limited, Blades Enterprise Centre, Sheffield, UK

    Lu Gaohua & Masoud Jamei

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  1. Fang Wu
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  2. Lu Gaohua
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  7. Sue-Chih Lee
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Correspondence to Sue-Chih Lee.

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Wu, F., Gaohua, L., Zhao, P. et al. Predicting Nonlinear Pharmacokinetics of Omeprazole Enantiomers and Racemic Drug Using Physiologically Based Pharmacokinetic Modeling and Simulation: Application to Predict Drug/Genetic Interactions. Pharm Res 31, 1919–1929 (2014). https://doi.org/10.1007/s11095-013-1293-z

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