使用三唑类药物对肝脏脂肪变性进行qIVIVE建模

IF 2.9 Q2 TOXICOLOGY
A.M. Steinbach , C.T. Willenbockel , P. Marx-Stoelting , M.T.D. Cronin , V. Städele
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引用次数: 0

摘要

由于日益增长的科学、社会和监管需求以及伦理考虑,迫切需要改进无动物化学测试策略。在这种情况下,一个有希望的发展是体外测试和硅工具的应用增加。本研究旨在将定量的体外到体内外推法(qIVIVE)与肝脏脂肪变性的不良结局途径(AOP)结合起来。肝脂肪变性是一个重要的(毒理学)终点,它构成了代谢功能障碍相关脂肪变性肝病(MASLD)的第一步,这是公共卫生部门日益严峻的挑战。重点研究了细胞暴露于杀菌剂丙环康唑和替布康唑后,在体外测量甘油三酯积累的晚期关键事件,以及在体内观察到的相应的肝脏脂肪空泡化关键事件。基于生理的动力学(PBK)和体外分布模型促进了qIVIVE方法。PBK模型预测的浓度与实验测定的体内血浆和肝脏杀菌剂浓度吻合良好。当转化为等效的口服剂量时,甘油三酯积累的体外浓度-反应数据与口服丙咪唑和戊康唑后啮齿动物肝脏脂肪空泡化的体内数据显示出良好的相关性。qivive衍生的基准剂量值与体内实验获得的值相似。本案例研究证实了将AOPs和qIVIVE整合在一起进行逆境预测的有效性,特别是在3R原则的“替代”方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AOP-informed qIVIVE modelling for liver steatosis using triazoles
Due to increasing scientific, societal and regulatory demands as well as ethical considerations there is an urgent need for improved animal-free strategies for chemical testing. A promising development in this context is the increased application of in vitro testing and in silico tools. This study aimed at integrating quantitative in vitro to in vivo extrapolation (qIVIVE) with the adverse-outcome pathway (AOP) for liver steatosis. Liver steatosis is an important (toxicological) endpoint which constitutes the first step of metabolic-dysfunction associated steatotic liver disease (MASLD), a growing challenge in the public health sector. Focus was set on the late key event of triglyceride accumulation measured in vitro after exposure of cells to the fungicides propiconazole and tebuconzole, and the corresponding key event of liver fat vacuolation observed in vivo. The qIVIVE approach was facilitated by physiologically based kinetic (PBK) and in vitro distribution models. Concentrations predicted by PBK modelling corresponded well with experimentally determined in vivo plasma and liver concentrations of the fungicides. The in vitro concentration–response data for triglyceride accumulation, when translated to equivalent oral doses, showed good correlation to rodent in vivo data on liver fat vacuolation after oral exposure to propi- and tebuconazole. qIVIVE-derived benchmark dose values were similar to values obtained from the in vivo experiments. This case study confirms the usefulness of integrating AOPs and qIVIVE for adversity prediction particularly with regard to the “replacement” aspect of the 3R principle.
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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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