Simcyp Limited (a Certara Company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK.
Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.
Clin Pharmacokinet. 2018 Sep;57(9):1149-1171. doi: 10.1007/s40262-017-0618-1.
Postulating fetal exposure to xenobiotics has been based on animal studies; however, inter-species differences can make this problematic. Physiologically-based pharmacokinetic models may capture the rapid changes in anatomical, biochemical, and physiological parameters during fetal growth over the duration of pregnancy and help with interpreting laboratory animal data. However, these models require robust information on the longitudinal variations of system parameter values and their covariates.
The objective of this study was to present an extensive analysis and integration of the available biometric data required for creating a virtual human fetal population by means of equations that define the changes of each parameter with gestational age.
A comprehensive literature search was carried out on the parameters defining the growth of a fetus during in-utero life including weight, height, and body surface area in addition to other indices of fetal size, body fat, and water. Collated data were assessed and integrated through a meta-analysis to develop mathematical algorithms to describe growth with fetal age.
Data for the meta-analysis were obtained from 97 publications, of these, 15 were related to fetal height or length, 32 to fetal weight, 4 to fetal body surface area, 8 to crown length, 5 to abdominal circumference, 12 to head circumference, 14 to body fat, and 12 to body water. Various mathematical algorithms were needed to describe parameter values from the time of conception to birth.
The collated data presented in this article enabled the development of mathematical functions to describe fetal biometry and provide a potentially useful resource for building anthropometric features of fetal physiologically-based pharmacokinetic models.
推测胎儿暴露于外源性化学物质的依据是来自于动物研究;然而,种间差异使得这种推断变得很复杂。基于生理学的药代动力学模型可以捕捉到在妊娠期间胎儿生长过程中解剖学、生物化学和生理学参数的快速变化,并有助于解释实验室动物数据。然而,这些模型需要关于系统参数值及其协变量的纵向变化的可靠信息。
本研究的目的是提出一种广泛的分析和整合,以便通过定义每个参数随胎龄变化的方程,创建一个虚拟的人类胎儿群体所需的可用生物计量学数据。
对定义胎儿在子宫内生命期间生长的参数进行了全面的文献检索,包括体重、身高和体表面积,以及其他胎儿大小、体脂和水的指数。整理的数据通过荟萃分析进行评估和整合,以开发描述与胎龄相关的生长的数学算法。
荟萃分析的数据来自 97 篇出版物,其中 15 篇与胎儿身高或长度有关,32 篇与胎儿体重有关,4 篇与胎儿体表面积有关,8 篇与头长有关,5 篇与腹围有关,12 篇与头围有关,14 篇与体脂有关,12 篇与体水有关。需要使用各种数学算法来描述从受孕到出生的参数值。
本文中整理的数据使能够开发描述胎儿生物计量学的数学函数,并为构建基于生理学的药代动力学模型的胎儿人体测量特征提供了一个潜在有用的资源。