评估毒理学关注阈值(TTC)及其排除在医疗器械可提取化学物质生物相容性评估中的效用。

IF 3.1 Q2 TOXICOLOGY
Grace Patlewicz , Mark Nelms , Diego Rua
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引用次数: 1

摘要

毒理学关注阈值(TTC)是一种实用的方法,用于建立安全阈值,低于该阈值不会对人类健康造成明显风险。在这里,通过Toxtree v3.1中的Kroes TTC决策模块对约45000种物质的大量库存(称为LRI数据集)进行了分析,以将物质分配到各自的TTC类别中。四千零二种物质被发现不适用于TTC方法。然而,对这些物质的仔细检查发现了几个实施问题:以盐形式表示的物质被自动指定为不适合TTC,因为其中许多物质含有作为抗衡离子的必需金属,这将使它们适用TTC。根据目前软件中实施的规则,高效力致癌物和二恶英类物质没有被完全捕获。当含磷物质中的许多适合TTC时,它们被视为除外物质。有人提议进行改进,以解决目前软件实施中的局限性。该研究的第二部分探索了一组代表医疗器械释放物质的物质,并将其与LRI数据集以及其他毒性数据集进行了比较,以调查其结构相似性。该研究的第三个组成部分试图扩大排除规则,以解决缺乏毒性数据的医疗器械释放物质的应用问题。然后将改进的规则应用于该数据集,并对TTC分配进行比较。该案例研究证明了评估既定TTC工作流程的软件实施的重要性,确定了某些局限性,并探索了将这些概念应用于医疗设备时的潜在改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the utility of the Threshold of Toxicological Concern (TTC) and its exclusions in the biocompatibility assessment of extractable chemical substances from medical devices

The Threshold of Toxicological Concern (TTC) is a pragmatic approach used to establish safe thresholds below which there can be no appreciable risk to human health. Here, a large inventory of ∼45,000 substances (referred to as the LRI dataset) was profiled through the Kroes TTC decision module within Toxtree v3.1 to assign substances into their respective TTC categories. Four thousand and two substances were found to be not applicable for the TTC approach. However, closer examination of these substances uncovered several implementation issues: substances represented in their salt forms were automatically assigned as not appropriate for TTC when many of these contained essential metals as counter ions which would render them TTC applicable. High Potency Carcinogens and dioxin-like substances were not fully captured based on the rules currently implemented in the software. Phosphorus containing substances were considered exclusions when many of them would be appropriate for TTC. Refinements were proposed to address the limitations in the current software implementation. A second component of the study explored a set of substances representative of those released from medical devices and compared them to the LRI dataset as well as other toxicity datasets to investigate their structural similarity. A third component of the study sought to extend the exclusion rules to address application to substances released from medical devices that lack toxicity data. The refined rules were then applied to this dataset and the TTC assignments were compared. This case study demonstrated the importance of evaluating the software implementation of an established TTC workflow, identified certain limitations and explored potential refinements when applying these concepts to medical devices.

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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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