Pregnancy-PBPK models: How are biochemical and physiological processes integrated?

IF 3.1 Q2 TOXICOLOGY
E. Thépaut , C. Brochot , K. Chardon , S. Personne , F.A. Zeman
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引用次数: 1

Abstract

Physiologically based pharmacokinetic (PBPK) modeling is used to predict the pharmacokinetic behavior of xenobiotics in humans. During pregnancy, anatomical and physiological parameters are modified leading to toxicokinetics’ changes of substances in the body. Considering these physiological parameters change in the building processes of pregnancy PBPK (p-PBPK) model is essential to have accurate estimates of tissue/organ concentrations for the pregnant women but also for the fetus.

The review aims to summarize which specific processes are considered in the building of p-PBPK models and may be useful at the early stages of p-PBPK modeling.

To achieve this objective, a literature search focusing on anatomical, physiological, and biochemical parameters impacted by pregnancy was conducted. Most of the time, p-PBPK models do not include all the specific processes identified but only the most impacting ones on the global kinetics, depending mainly on the substance of interest. Allometric relations were identified to be classically included in the pregnancy models to describe the modifications induced by pregnancy to overcome the lack of data usually observed for the gestation. However, more and more data are gathered for pregnancy leading to the introduction of more data-based equations in PBPK modeling.

The most common strategy for p-PBPK development is based on the development of adult PBPK models that are then adapted to specific populations such as pregnant women. The adult PBPK model structure is modified to account for the pregnancy by adding specific compartments of fetal development and also specific compartments that are impacted during the pregnancy such as fat or mammary glands. Extrapolation of pregnant rat model is the other common strategy option used more specifically for environmental substances.

Overall, further data on maternal and fetal pharmacokinetics are needed to validate the xenobiotic exposure predictions during pregnancy, using for example in vitro, in vivo or ex vivo experiments.

妊娠- pbpk模型:生化和生理过程是如何整合的?
基于生理的药代动力学(PBPK)模型用于预测异种抗生素在人体内的药代动力学行为。在怀孕期间,解剖和生理参数发生改变,导致体内物质的毒性动力学发生变化。考虑到这些生理参数在妊娠PBPK (p-PBPK)模型建立过程中的变化,对于准确估计孕妇和胎儿的组织/器官浓度至关重要。本文旨在总结在构建p-PBPK模型时考虑的具体过程,以及在p-PBPK建模的早期阶段可能有用的过程。为了实现这一目标,我们对妊娠对解剖、生理和生化参数的影响进行了文献检索。大多数情况下,p-PBPK模型不包括所有确定的特定过程,而只包括对整体动力学影响最大的过程,主要取决于感兴趣的物质。异速生长关系被确定为典型的妊娠模型,以描述由妊娠引起的变化,以克服缺乏通常观察到的妊娠数据。然而,越来越多的妊娠数据被收集,导致PBPK建模中引入了更多基于数据的方程。最常见的p-PBPK发展策略是基于成人PBPK模型的发展,然后适应特定人群,如孕妇。通过添加胎儿发育的特定区室以及在怀孕期间受到影响的特定区室(如脂肪或乳腺),对成人PBPK模型结构进行了修改,以解释妊娠。外推怀孕大鼠模型是另一种常见的策略选择,更具体地用于环境物质。总的来说,需要进一步的母体和胎儿药代动力学数据来验证怀孕期间的外源暴露预测,例如使用体外、体内或离体实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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