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开发和验证一种基于生理学的模型,用于预测兔体内的药代动力学/毒代动力学。

Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits.

机构信息

Bayer AG, Engineering & Technology- Systems Pharmacology, Leverkusen, Germany.

Bayer Crop Science, Environmental Safety, Monheim, Germany.

出版信息

PLoS One. 2018 Mar 21;13(3):e0194294. doi: 10.1371/journal.pone.0194294. eCollection 2018.

Abstract

The environmental fates of pharmaceuticals and the effects of crop protection products on non-target species are subjects that are undergoing intense review. Since measuring the concentrations and effects of xenobiotics on all affected species under all conceivable scenarios is not feasible, standard laboratory animals such as rabbits are tested, and the observed adverse effects are translated to focal species for environmental risk assessments. In that respect, mathematical modelling is becoming increasingly important for evaluating the consequences of pesticides in untested scenarios. In particular, physiologically based pharmacokinetic/toxicokinetic (PBPK/TK) modelling is a well-established methodology used to predict tissue concentrations based on the absorption, distribution, metabolism and excretion of drugs and toxicants. In the present work, a rabbit PBPK/TK model is developed and evaluated with data available from the literature. The model predictions include scenarios of both intravenous (i.v.) and oral (p.o.) administration of small and large compounds. The presented rabbit PBPK/TK model predicts the pharmacokinetics (Cmax, AUC) of the tested compounds with an average 1.7-fold error. This result indicates a good predictive capacity of the model, which enables its use for risk assessment modelling and simulations.

摘要

药品的环境归宿以及作物保护产品对非靶标物种的影响是正在深入审查的主题。由于测量所有受影响物种在所有可想象的情况下的外来化合物的浓度和影响是不可行的,因此通常会选择兔子等标准实验室动物进行测试,并将观察到的不良影响转化为环境风险评估的重点物种。在这方面,数学建模对于评估未测试情况下农药的后果变得越来越重要。特别是,基于生理学的药代动力学/毒代动力学(PBPK/TK)模型是一种成熟的方法,用于根据药物和毒物的吸收、分布、代谢和排泄来预测组织浓度。在本工作中,开发了一种兔 PBPK/TK 模型,并使用文献中可用的数据进行了评估。模型预测包括静脉内(i.v.)和口服(p.o.)给予小化合物和大化合物的情况。所提出的兔 PBPK/TK 模型以平均 1.7 倍的误差预测了测试化合物的药代动力学(Cmax,AUC)。这一结果表明模型具有良好的预测能力,使其能够用于风险评估建模和模拟。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57b2/5862475/aa94fa6b23f5/pone.0194294.g001.jpg

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