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Applicability of the Threshold of Toxicological Concern (TTC) approach to cosmetics – preliminary analysis

机译:毒理学阈值(TTC)方法在化妆品中的适用性–初步分析

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摘要

This report describes the application of chemoinformatic methods to explore the applicability of the Threshold of Toxicological Concern (TTC) approach to cosmetic ingredients. For non-cancer endpoints, the most widely used TTC approach is the Cramer classification scheme, which categorises chemicals into three classes (I, II and III) depending on their expected level of concern for oral systemic toxicity (low, medium, high, respectively). The chemical space of the Munro non-cancer dataset was characterised to assess whether this underlying TTC dataset is representative of the “world” of cosmetic ingredients, as represented by the COSMOS Cosmetics Inventory. In addition, the commonly used Cramer-related Munro threshold values were applied to a toxicological dataset of cosmetic ingredients, the COSMOS TTC dataset, to assess the degree of protectiveness resulting from the application of the Cramer classification scheme. This analysis is considered preliminary, since the COSMOS TTC dataset and Cosmetics Inventory are subject to an ongoing process of extension and quality control within the COSMOS project.The results of this preliminary analysis show that the Munro dataset is broadly representative of the chemical space of cosmetics, although certain structural classes are missing, notably organometallics, silicon-containing compounds, and certain types of surfactants (non-ionic and cationic classes). Furthermore, compared with the Cosmetics Inventory, the Munro dataset has a higher prevalence of reactive chemicals and a lower prevalence of larger, long linear chain structures. The COSMOS TTC dataset, comprising repeat dose toxicity data for cosmetics ingredients, shows a good representation of the Cosmetics Inventory, both in terms of physicochemical property ranges, structural features and chemical use categories. Thus, this dataset is considered to be suitable for investigating the applicability of the TTC approach to cosmetics. The results of the toxicity data analysis revealed a number of cosmetic ingredients in Cramer Class I with No Observed Effect Level (NOEL) values lower than the Munro threshold of 3000 µg/kg bw/day. The prevalence of these “false negatives” was less than 5%, which is the percentage expected by chance resulting from the use of the 5th percentile of cumulative probability distribution of NOELs in the derivation of TTC values. Furthermore, the majority of these false negatives do not arise when structural alerts for DNA-binding are used to identify potential genotoxicants, to which a lower TTC value of 0.0025 µg/kg bw/day is typically applied. Based on these preliminary results, it is concluded that the current TTC approach is broadly applicable to cosmetics, although a number of improvements can be made, through the quality control of the underlying TTC datasets, modest revisions / extensions of the Cramer classification scheme, and the development of explicit guidance on how to apply the TTC approach.
机译:本报告介绍了化学信息学方法的应用,以探索毒理学阈值(TTC)方法在化妆品成分中的适用性。对于非癌症终点,最广泛使用的TTC方法是Cramer分类方案,该方案将化学品分为三类(I,II和III),具体取决于它们对口腔全身毒性的预期关注水平(分别为低,中,高) )。 Munro非癌症数据集的化学空间经过表征,可以评估该基础TTC数据集是否代表化妆品成分的“世界”,如COSMOS化妆品清单所代表。此外,将常用的与Cramer相关的Munro阈值应用于化妆品成分的毒理学数据集COSMOS TTC数据集,以评估应用Cramer分类方案产生的保护程度。该分析被认为是初步的,因为COSMOS TTC数据集和化妆品清单在COSMOS项目中一直处于扩展和质量控制的过程中,该初步分析的结果表明Munro数据集可广泛代表化妆品的化学空间,尽管缺少某些结构类别,尤其是有机金属,含硅化合物和某些类型的表面活性剂(非离子和阳离子类别)。此外,与化妆品清单相比,Munro数据集具有较高的反应性化学物质普及率,而具有较大的长线性链结构的较低普及率。 COSMOS TTC数据集(包括化妆品成分的重复剂量毒性数据)在物理化学性质范围,结构特征和化学用途类别方面都很好地表示了化妆品清单。因此,该数据集被认为适合于研究TTC方法在化妆品中的适用性。毒性数据分析的结果表明,Cramer I类中的许多化妆品成分的未观察到的作用水平(NOEL)值均低于Munro阈值3000 µg / kg bw / day。这些“假阴性”的患病率小于5%,这是在TTC值推导中使用NOEL累积概率分布的第5个百分位数时偶然获得的百分比。此外,当使用DNA结合的结构警报来识别潜在的遗传毒性剂时,这些假阴性中的大多数不会出现,通常将其应用较低的TTC值0.0025 µg / kg bw / day。根据这些初步结果,可以得出结论,尽管可以通过基础TTC数据集的质量控制,对Cramer分类方案的适度修订/扩展和进行一些改进,但当前的TTC方法可广泛应用于化妆品。制定有关如何应用TTC方法的明确指南。

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