• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

妊娠和孕育期间人类母体和胎儿解剖学及生理学变化的经验模型。

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

机构信息

National Center for Environmental Assessment, US Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.

National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America.

出版信息

PLoS One. 2019 May 2;14(5):e0215906. doi: 10.1371/journal.pone.0215906. eCollection 2019.

DOI:10.1371/journal.pone.0215906
PMID:31048866
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6497258/
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.

摘要

许多在传统生理基于药代动力学模型中被视为常数的参数,在对妊娠和孕育进行建模时,必须被表述为随时间变化的量,因为在这期间会发生显著的生理和解剖变化。虽然已经发表了几集关于这些参数的经验模型,但每个模型都有缺点。我们试图为在受孕到分娩期间,人类母亲及其胎儿体内经历显著变化的组织体积、血流速率和其他数量,创建一个经验模型库,并解决之前发布的类似模型库存在的缺陷。我们使用最大似然估计法对感兴趣的随时间变化的各种数量进行校准,然后使用赤池信息量准则(Akaike information criterion)为每个数量选择一个最佳模型。对于没有时间过程数据的感兴趣数量,我们使用百分比和/或描述相关数量的模型来构建复合模型。通过这种方式,我们开发了一套全面的公式集,描述了构建人类母亲及其胎儿在整个大约 40 周妊娠和孕育期间的 PBPK 模型所需的参数。我们还包括了描述各种胎儿血液途径血流速率的模型,这些模型在成人中没有对应物。我们的感兴趣的解剖学和生理学数量的数学模型库为人类妊娠和孕育的 PBPK 模型提供了基础,因此,它最终可以用于支持对孕妇及其发育中的胎儿进行最佳药物剂量和风险评估的决策。本文表达的观点仅代表作者的观点,不一定代表美国环境保护署的观点或政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/4c5158a71ba7/pone.0215906.g029.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/3bc6b37e8264/pone.0215906.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/6075b17a68fd/pone.0215906.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/01cb619f73cc/pone.0215906.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/75446e5b08fe/pone.0215906.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/08a02f9f5ac0/pone.0215906.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/2e2a48ab0926/pone.0215906.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/6150297cc330/pone.0215906.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/2b20da80b8da/pone.0215906.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/e977e31d24b7/pone.0215906.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/e29f16202720/pone.0215906.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/9f58f301cb45/pone.0215906.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/a95e9d60de8c/pone.0215906.g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/abe07b8d6914/pone.0215906.g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/cbdd5840e5f3/pone.0215906.g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/359ad77c8985/pone.0215906.g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/3e6bde335415/pone.0215906.g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/b08b3083c180/pone.0215906.g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/0c56281c30f9/pone.0215906.g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/0f655ba27c45/pone.0215906.g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/cd506e273979/pone.0215906.g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/140bf5a803e1/pone.0215906.g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/19262353c070/pone.0215906.g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/633ca84edfcf/pone.0215906.g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/cfa0ac8dd305/pone.0215906.g024.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/ddd6b3bbc564/pone.0215906.g025.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/7c88385fcf9b/pone.0215906.g026.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/7a1f159b6044/pone.0215906.g027.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/f9f075cd05e6/pone.0215906.g028.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/4c5158a71ba7/pone.0215906.g029.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/3bc6b37e8264/pone.0215906.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/6075b17a68fd/pone.0215906.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/01cb619f73cc/pone.0215906.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/75446e5b08fe/pone.0215906.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/08a02f9f5ac0/pone.0215906.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/2e2a48ab0926/pone.0215906.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/6150297cc330/pone.0215906.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/2b20da80b8da/pone.0215906.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/e977e31d24b7/pone.0215906.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/e29f16202720/pone.0215906.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/9f58f301cb45/pone.0215906.g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/a95e9d60de8c/pone.0215906.g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/abe07b8d6914/pone.0215906.g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/cbdd5840e5f3/pone.0215906.g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/359ad77c8985/pone.0215906.g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/3e6bde335415/pone.0215906.g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/b08b3083c180/pone.0215906.g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/0c56281c30f9/pone.0215906.g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/0f655ba27c45/pone.0215906.g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/cd506e273979/pone.0215906.g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/140bf5a803e1/pone.0215906.g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/19262353c070/pone.0215906.g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/633ca84edfcf/pone.0215906.g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/cfa0ac8dd305/pone.0215906.g024.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/ddd6b3bbc564/pone.0215906.g025.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/7c88385fcf9b/pone.0215906.g026.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/7a1f159b6044/pone.0215906.g027.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/f9f075cd05e6/pone.0215906.g028.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85d9/6497258/4c5158a71ba7/pone.0215906.g029.jpg

相似文献

1
Empirical models for anatomical and physiological changes in a human mother and fetus during pregnancy and gestation.妊娠和孕育期间人类母体和胎儿解剖学及生理学变化的经验模型。
PLoS One. 2019 May 2;14(5):e0215906. doi: 10.1371/journal.pone.0215906. eCollection 2019.
2
Physiological "constants" for PBPK models for pregnancy.孕期生理药代动力学模型的生理“常数”
J Toxicol Environ Health. 1997 Dec 12;52(5):385-401. doi: 10.1080/00984109708984072.
3
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.妊娠女性健康的解剖学和生理学的妊娠期特异性变化:妊娠生理基于药代动力学模型的扩展模型参数库。
Clin Pharmacokinet. 2017 Nov;56(11):1303-1330. doi: 10.1007/s40262-017-0539-z.
4
A physiologically based pharmacokinetic computer model for human pregnancy.一种基于生理学的人类妊娠药代动力学计算机模型。
Teratology. 1994 Feb;49(2):90-103. doi: 10.1002/tera.1420490205.
5
Development of a physiologically based pharmacokinetic model for bisphenol A in pregnant mice.建立孕鼠体内双酚A的生理药代动力学模型。
Toxicol Appl Pharmacol. 2007 Oct 15;224(2):182-91. doi: 10.1016/j.taap.2007.06.023. Epub 2007 Jul 12.
6
The development of a pregnancy PBPK Model for Bisphenol A and its evaluation with the available biomonitoring data.建立双酚 A 的妊娠人群 PBPK 模型及其与现有生物监测数据的评估。
Sci Total Environ. 2018 May 15;624:55-68. doi: 10.1016/j.scitotenv.2017.12.023. Epub 2017 Dec 13.
7
Construction of a physiologically based pharmacokinetic model for 2,4-dichlorophenoxyacetic acid dosimetry in the developing rabbit brain.建立用于发育中兔脑2,4-二氯苯氧乙酸剂量测定的生理药代动力学模型。
Toxicol Appl Pharmacol. 1996 Feb;136(2):250-9. doi: 10.1006/taap.1996.0032.
8
Physiologically based pharmacokinetic modeling of fetal and neonatal manganese exposure in humans: describing manganese homeostasis during development.基于生理学的人体胎儿和新生儿锰暴露的药代动力学模型:描述发育过程中的锰内稳态。
Toxicol Sci. 2011 Aug;122(2):297-316. doi: 10.1093/toxsci/kfr141. Epub 2011 May 27.
9
Fetal Physiologically Based Pharmacokinetic Models: Systems Information on Fetal Blood Components and Binding Proteins.胎儿生理药代动力学模型:胎儿血液成分和结合蛋白的系统信息。
Clin Pharmacokinet. 2020 May;59(5):629-642. doi: 10.1007/s40262-019-00836-3.
10
Mathematical modeling of the human fetal arterial blood circulation.人类胎儿动脉血液循环的数学建模。
Int J Biomed Comput. 1992 Aug;31(2):127-39. doi: 10.1016/0020-7101(92)90068-4.

引用本文的文献

1
An advancement in developmental and reproductive toxicity (DART) risk assessment: evaluation of a bioactivity and exposure-based NAM toolbox.发育和生殖毒性(DART)风险评估的进展:基于生物活性和暴露的NAM工具箱评估
Front Toxicol. 2025 Jun 30;7:1602065. doi: 10.3389/ftox.2025.1602065. eCollection 2025.
2
The silent threat: effects of PM2.5 exposure on perinatal complications and neonatal outcomes.无声的威胁:暴露于细颗粒物2.5对围产期并发症和新生儿结局的影响。
BMC Pregnancy Childbirth. 2025 Jul 2;25(1):686. doi: 10.1186/s12884-025-07767-x.
3
In vitro and computational approaches to predict developmental toxicity: Integrating PBPK models with cell-based assays.

本文引用的文献

1
httk: R Package for High-Throughput Toxicokinetics.httk:用于高通量毒物动力学的R软件包。
J Stat Softw. 2017 Jul 17;79(4):1-26. doi: 10.18637/jss.v079.i04.
2
Fetal Physiologically Based Pharmacokinetic Models: Systems Information on the Growth and Composition of Fetal Organs.胎儿生理药代动力学模型:胎儿器官生长和组成的系统信息。
Clin Pharmacokinet. 2019 Feb;58(2):235-262. doi: 10.1007/s40262-018-0685-y.
3
Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability.通过模拟毒物动力学变异性来识别对环境化学品敏感的人群。
预测发育毒性的体外和计算方法:将生理药代动力学(PBPK)模型与基于细胞的试验相结合。
Toxicol Appl Pharmacol. 2025 Sep;502:117435. doi: 10.1016/j.taap.2025.117435. Epub 2025 Jun 4.
4
New Approach Methodologies for Exposure Science.暴露科学的新方法学
Curr Opin Toxicol. 2019 Aug 29;15:76-92. doi: 10.1016/j.cotox.2019.07.001.
5
Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies.通过毒代动力学建模、体外-体内外推和新方法学来提高对人类变异性的认识。
Hum Genomics. 2024 Nov 21;18(1):129. doi: 10.1186/s40246-024-00691-9.
6
Development of a Physiologically Based Pharmacokinetic (PBPK) Model for F-53B in Pregnant Mice and Its Extrapolation to Humans.建立 F-53B 在妊娠小鼠体内的生理药代动力学(PBPK)模型及其向人体的外推。
Environ Sci Technol. 2024 Oct 22;58(42):18928-18939. doi: 10.1021/acs.est.4c05405. Epub 2024 Oct 12.
7
Physiologically based pharmacokinetic modeling of long-acting extended-release naltrexone in pregnant women with opioid use disorder.基于生理学的长效缓释纳曲酮在患有阿片类药物使用障碍的孕妇中的药代动力学模型。
CPT Pharmacometrics Syst Pharmacol. 2024 Nov;13(11):1939-1952. doi: 10.1002/psp4.13252. Epub 2024 Oct 9.
8
Development of a formula for estimated glomerular filtration rate in pregnant women from physiological hyperfiltration of serum creatinine.基于血清肌酐生理性高滤过推导孕妇估算肾小球滤过率公式的建立。
Sci Rep. 2024 Mar 27;14(1):7229. doi: 10.1038/s41598-024-57737-0.
9
Multi-organ developmental toxicity and its characteristics in fetal mice induced by dexamethasone at different doses, stages, and courses during pregnancy.孕期不同剂量、时期和阶段给予地塞米松致胎鼠多器官发育毒性及其特点。
Arch Toxicol. 2024 Jun;98(6):1891-1908. doi: 10.1007/s00204-024-03707-4. Epub 2024 Mar 24.
10
Investigating open access new approach methods (NAM) to assess biological points of departure: A case study with 4 neurotoxic pesticides.研究用于评估生物学起始点的开放获取新方法(NAM):以4种神经毒性杀虫剂为例的案例研究
Curr Res Toxicol. 2024 Feb 15;6:100156. doi: 10.1016/j.crtox.2024.100156. eCollection 2024.
Environ Int. 2017 Sep;106:105-118. doi: 10.1016/j.envint.2017.06.004. Epub 2017 Jun 16.
4
Development of a Novel Maternal-Fetal Physiologically Based Pharmacokinetic Model I: Insights into Factors that Determine Fetal Drug Exposure through Simulations and Sensitivity Analyses.一种新型基于生理的母婴药代动力学模型的开发 I:通过模拟和敏感性分析深入了解决定胎儿药物暴露的因素。
Drug Metab Dispos. 2017 Aug;45(8):920-938. doi: 10.1124/dmd.117.075192. Epub 2017 Jun 6.
5
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.妊娠女性健康的解剖学和生理学的妊娠期特异性变化:妊娠生理基于药代动力学模型的扩展模型参数库。
Clin Pharmacokinet. 2017 Nov;56(11):1303-1330. doi: 10.1007/s40262-017-0539-z.
6
Toxicokinetic models and related tools in environmental risk assessment of chemicals.化学品环境风险评估中的毒代动力学模型及相关工具。
Sci Total Environ. 2017 Feb 1;578:1-15. doi: 10.1016/j.scitotenv.2016.10.146. Epub 2016 Nov 12.
7
Integration of Life-Stage Physiologically Based Pharmacokinetic Models with Adverse Outcome Pathways and Environmental Exposure Models to Screen for Environmental Hazards.将基于生理的生命阶段药代动力学模型与不良结局途径及环境暴露模型相结合以筛选环境危害
Toxicol Sci. 2016 Jul;152(1):230-43. doi: 10.1093/toxsci/kfw082. Epub 2016 May 4.
8
Reprint of PopGen: A virtual human population generator.《群体遗传学:一个虚拟人类群体生成器》重印版
Toxicology. 2015 Jun 5;332:77-93. doi: 10.1016/j.tox.2015.04.014. Epub 2015 Apr 25.
9
Deciphering death: a commentary on Gompertz (1825) 'On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies'.解读死亡:对戈姆珀茨(1825年)《论表达人类死亡率规律的函数的性质,以及确定生命意外事件价值的一种新模式》的评论
Philos Trans R Soc Lond B Biol Sci. 2015 Apr 19;370(1666). doi: 10.1098/rstb.2014.0379.
10
Body composition changes in pregnancy: measurement, predictors and outcomes.孕期身体成分变化:测量、预测因素及结果
Eur J Clin Nutr. 2014 Jun;68(6):643-52. doi: 10.1038/ejcn.2014.40. Epub 2014 Mar 26.