Physiologically-based pharmacokinetic modeling of drugs metabolized via several CYP enzymes in populations of pregnant women
Andre Dallmann (1), Ibrahim Ince (2), Katrin Coboeken (2), Thomas Eissing (2), Georg Hempel (1)
(1) University of Münster, Münster, Germany, (2) Systems Pharmacology and Medicine, Bayer AG, Leverkusen, Germany
Objectives: The objective of this study is to verify a physiologically-based pharmacokinetic (PBPK) model for the prediction of pharmacokinetics (PK) of drugs metabolized via several CYP enzymes in populations of pregnant women.
Methods: A recently developed and verified pregnancy PBPK model for renally cleared drugs [1,2] was extended to predict the disposition of drugs metabolized via several CYP enzymes, including CYP 2A6, 2E1 and 3A4/5. Therefore, the literature was screened for quantitative information on pregnancy-dependent changes in the activity of relevant CYP enzymes. In case sufficient data were available throughout pregnancy, the observed changes were described by a monotonous function fitted to the data. Otherwise the changes were described in steps of trimesters. If conflicting data or no data on enzyme activity were available, sensitivity analyses were performed based on in vivo concentration-time profiles to identify the apparent changes in enzyme activity. Subsequently, pregnancy PBPK models were built to predict the PK of drugs metabolized by CYP 2A6, 2E1 and/or 3A4/5. PK predictions were evaluated by comparing them with in vivo data taken from the literature. The physiological changes related to pregnancy as well as the substance PBPK models were developed in PK-Sim and Mobi as part of the Open Systems Pharmacology Suite [3,4].
Results: Compared to the non-pregnant state, an average 1.8-fold increase was reported for CYP 2A6 and 2E1 at the end of pregnancy. A somewhat lower increase was obtained on the basis of a sensitivity analysis for CYP 3A4/5. Using these increases in enzyme activity, the PBPK models successfully predicted the PK of all drugs administered to pregnant women. More than 90% of the predicted mean plasma concentrations in pregnant women fell within the 1.5-fold error range. For all drugs, ratios of predicted to observed AUC were within the range of 0.8 – 1.2.
Conclusions: We successfully developed and verified a pregnancy population PBPK model for drugs metabolized via several CYP enzymes. Ultimately, this model can be applied to investigate in silico the PK of drugs undergoing metabolism in pregnancy and help design dosages e.g. for clinical trials in this vulnerable special population.
References:
[1] Dallmann, A, et al. Gestation-specific changes in the anatomy and physiology of healthy pregnant women: An extended repository of model parameters for physiologically based pharmacokinetic modeling in pregnancy [submitted for publication]
[2] Dallmann, A, et al. Physiologically based pharmacokinetic modeling of renally cleared drugs in pregnant women [submitted for publication]
[3] Eissing T, et al. A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks. Frontiers in physiology 2011;2:1-10.
[4] www.open-systems-pharmacology.org
