Abstract
Background
In the past years, several repositories for anatomical and physiological parameters required for physiologically based pharmacokinetic modeling in pregnant women have been published. While providing a good basis, some important aspects can be further detailed. For example, they did not account for the variability associated with parameters or were lacking key parameters necessary for developing more detailed mechanistic pregnancy physiologically based pharmacokinetic models, such as the composition of pregnancy-specific tissues.
Objectives
The aim of this meta-analysis was to provide an updated and extended database of anatomical and physiological parameters in healthy pregnant women that also accounts for changes in the variability of a parameter throughout gestation and for the composition of pregnancy-specific tissues.
Methods
A systematic literature search was carried out to collect study data on pregnancy-related changes of anatomical and physiological parameters. For each parameter, a set of mathematical functions was fitted to the data and to the standard deviation observed among the data. The best performing functions were selected based on numerical and visual diagnostics as well as based on physiological plausibility.
Results
The literature search yielded 473 studies, 302 of which met the criteria to be further analyzed and compiled in a database. In total, the database encompassed 7729 data. Although the availability of quantitative data for some parameters remained limited, mathematical functions could be generated for many important parameters. Gaps were filled based on qualitative knowledge and based on physiologically plausible assumptions.
Conclusion
The presented results facilitate the integration of pregnancy-dependent changes in anatomy and physiology into mechanistic population physiologically based pharmacokinetic models. Such models can ultimately provide a valuable tool to investigate the pharmacokinetics during pregnancy in silico and support informed decision making regarding optimal dosing regimens in this vulnerable special population.
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The authors thank Kirstin Thelen (Bayer AG) for valuable discussions.
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Andre Dallmann is a PhD student at the University of Münster and is employed on a grant from Bayer AG. Ibrahim Ince, Michaela Meyer, Stefan Willmann, and Thomas Eissing were employed by Bayer AG during the preparation of this manuscript and are potential stock holders of Bayer AG. Georg Hempel has received a research grant from Bayer AG since 2008.
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Dallmann, A., Ince, I., Meyer, M. 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. Clin Pharmacokinet 56, 1303–1330 (2017). https://doi.org/10.1007/s40262-017-0539-z
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DOI: https://doi.org/10.1007/s40262-017-0539-z