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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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.
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.
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.
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.
KEY WORDSesomeprazole nonlinear pharmacokinetics omeprazole physiologically based pharmacokinetic (PBPK) model racemic drug
Absorption, distribution, metabolism and excretion
Automated sensitivity analysis
Human liver microsomes
Physiologically based pharmacokinetic modeling
Volume of distribution at steady state
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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