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A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways

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Abstract

Background

Physiologically based pharmacokinetic modeling is considered a valuable tool for predicting pharmacokinetic changes in pregnancy to subsequently guide in-vivo pharmacokinetic trials in pregnant women. The objective of this study was to extend and verify a previously developed physiologically based pharmacokinetic model for pregnant women for the prediction of pharmacokinetics of drugs metabolized via several cytochrome P450 enzymes.

Methods

Quantitative information on gestation-specific changes in enzyme activity available in the literature was incorporated in a pregnancy physiologically based pharmacokinetic model and the pharmacokinetics of eight drugs metabolized via one or multiple cytochrome P450 enzymes was predicted. The tested drugs were caffeine, midazolam, nifedipine, metoprolol, ondansetron, granisetron, diazepam, and metronidazole. Pharmacokinetic predictions were evaluated by comparison with in-vivo pharmacokinetic data obtained from the literature.

Results

The pregnancy physiologically based pharmacokinetic model successfully predicted the pharmacokinetics of all tested drugs. The observed pregnancy-induced pharmacokinetic changes were qualitatively and quantitatively reasonably well predicted for all drugs. Ninety-seven percent of the mean plasma concentrations predicted in pregnant women fell within a twofold error range and 63% within a 1.25-fold error range. For all drugs, the predicted area under the concentration–time curve was within a 1.25-fold error range.

Conclusion

The presented pregnancy physiologically based pharmacokinetic model can quantitatively predict the pharmacokinetics of drugs that are metabolized via one or multiple cytochrome P450 enzymes by integrating prior knowledge of the pregnancy-related effect on these enzymes. This pregnancy physiologically based pharmacokinetic model may thus be used to identify potential exposure changes in pregnant women a priori and to eventually support informed decision making when clinical trials are designed in this special population.

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Acknowledgements

This publication and the work involved were funded by Bayer AG.

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Authors and Affiliations

  1. Department of Pharmaceutical and Medical Chemistry, Clinical Pharmacy, Westfälische Wilhelms-University Münster, 48149, Münster, Germany

    André Dallmann & Georg Hempel

  2. Clinical Pharmacometrics, Bayer AG, 51368, Leverkusen, Germany

    Ibrahim Ince, Katrin Coboeken & Thomas Eissing

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  1. André Dallmann
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Correspondence to André Dallmann.

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André Dallmann is a PhD student at the University of Münster and is employed on a grant from Bayer AG. Ibrahim Ince, Katrin Coboeken, and Thomas Eissing were employed by Bayer AG during preparation of this article and are potential stock holders of Bayer AG. Georg Hempel has receives a research grant from Bayer AG since 2008.

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Dallmann, A., Ince, I., Coboeken, K. et al. A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways. Clin Pharmacokinet 57, 749–768 (2018). https://doi.org/10.1007/s40262-017-0594-5

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