Khaled Abduljalil1, Trevor N Johnson2, Amin Rostami-Hodjegan2,3. 1. Simcyp Limited (a Certara Company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK. khaled.abduljalil@certara.com. 2. Simcyp Limited (a Certara Company), Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK. 3. Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.
Abstract
BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
Authors: Wellington P Martins; Carolina O Nastri; Daniela A Barra; Paula A A S Navarro; Francisco Mauad Filho; Rui A Ferriani Journal: Eur J Obstet Gynecol Reprod Biol Date: 2009-04-21 Impact factor: 2.435