Empirical models for anatomical and physiological changes in a human mother and fetus during pregnancy and gestation

Abstract

Many parameters treated as constants in traditional physiologically based pharmacokinetic models must be formulated as time-varying quantities when modeling pregnancy and gestation due to the dramatic physiological and anatomical changes that occur during this period. While several collections of empirical models for such parameters have been published, each has shortcomings. We sought to create a repository of empirical models for tissue volumes, blood flow rates, and other quantities that undergo substantial changes in a human mother and her fetus during the time between conception and birth, and to address deficiencies with similar, previously published repositories. We used maximum likelihood estimation to calibrate various models for the time-varying quantities of interest, and then used the Akaike information criterion to select an optimal model for each quantity. For quantities of interest for which time-course data were not available, we constructed composite models using percentages and/or models describing related quantities. In this way, we developed a comprehensive collection of formulae describing parameters essential for constructing a PBPK model of a human mother and her fetus throughout the approximately 40 weeks of pregnancy and gestation. We included models describing blood flow rates through various fetal blood routes that have no counterparts in adults. Our repository of mathematical models for anatomical and physiological quantities of interest provides a basis for PBPK models of human pregnancy and gestation, and as such, it can ultimately be used to support decision-making with respect to optimal pharmacological dosing and risk assessment for pregnant women and their developing fetuses. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U . S . Environmental Protection Agency .

Characterization of the Ontogeny of Hepatic UDP‐Glucuronosyltransferase Enzymes Based on Glucuronidation Activity Measured in Human Liver Microsomes

“…Pediatric physiologically based pharmacokinetic (PBPK) modeling is a valuable tool to predict the impact of age on the exposure of metabolized drugs. Such models consider age‐dependent changes in physiological parameters including maturation of organ size, function, and composition and can also include nonmonotonic metabolic maturation processes . A recent guidance from the European Medicines Agency advocated the need to address the effects of ontogeny on quantitative changes in the contribution of elimination pathways across pediatric age groups…”

“…Such models consider age-dependent changes in physiological parameters including maturation of organ size, function, and composition and can also include nonmonotonic metabolic maturation processes. [10][11][12][13] A recent guidance from the European Medicines Agency advocated the need to address the effects of ontogeny on quantitative changes in the contribution of elimination pathways across pediatric age groups. 14 To date, the ontogeny of 7 hepatic UGT isoforms (UGT1A1, UGT1A4, UGT1A6, UGT1A9, UGT2B7, UGT2B15, and UGT2B17) has been evaluated based on glucuronidation activity or protein abundance determined in human liver microsomes (HLMs) in independent studies.…”

Placental transfer of xenobiotics in pregnancy physiologically-based pharmacokinetic models: Structure and data

“…The articles [17,26,144]. However quantitative data are lacking for a proper parametrization of this process.…”

Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy

“…Following satisfactory calibration, population prediction was achieved by performing sensitivity analysis and Monte Carlo simulations. The population nonpregnancy model was extended to pregnancy by incorporating physiological changes in pregnancy 4 , 44 , 45 . The pregnancy model was simulated to predict pharmacokinetic data for the second and third trimester of pregnancy using a verification dataset 30 .…”

“…Pregnancy-related changes were incorporated as gestational-dependent polynomial equations adapted from several publications 4 , 44 , 45 . The equations used in our model are provided in Supplementary Table 4 .…”