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首页> 外文期刊>Toxicology in vitro: an international journal published in association with BIBRA >Analysis of the Local Lymph Node Assay (LLNA) variability for assessing the prediction of skin sensitisation potential and potency of chemicals with non-animal approaches
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Analysis of the Local Lymph Node Assay (LLNA) variability for assessing the prediction of skin sensitisation potential and potency of chemicals with non-animal approaches

机译:分析局部淋巴结测定法(LLNA)的变异性,以评估使用非动物方法对皮肤致敏潜力和化学药效的预测

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The knowledge of the biological mechanisms leading to the induction of skin sensitisation has favoured in recent years the development of alternative non-animal methods. During the formal validation process, results from the Local Lymph Node Assay (LLNA) are generally used as reference data to assess the predictive capacity of the non animal tests. This study reports an analysis of the variability of the LLNA for a set of chemicals for which multiple studies are available and considers three hazard classification schemes: POS/NEG, GHS/CLP and ECETOC. As the type of vehicle used in a LLNA study is known to influence to some extent the results, two analyses were performed: considering the solvent used to test the chemicals and without considering the solvent. The results show that the number of discordant classifications increases when a chemical is,tested in more than one solvent Moreover, it can be concluded that study results leading to classification in the strongest classes (1A and EXT) seem to be more reliable than those in the weakest classes. This study highlights the importance of considering the variability of the reference data when evaluating non-animal tests. (C) 2016 The Authors. Published by Elsevier Ltd.
机译:近年来,引起皮肤致敏的生物学机制的知识已促进了替代性非动物方法的发展。在正式的验证过程中,局部淋巴结测定(LLNA)的结果通常用作参考数据,以评估非动物试验的预测能力。这项研究报告了对一组可进行多项研究的化学品的LLNA变异性的分析,并考虑了三种危害分类方案:POS / NEG,GHS / CLP和ECETOC。由于已知在LLNA研究中使用的媒介物类型在一定程度上影响结果,因此进行了两项分析:考虑用于测试化学药品的溶剂,而不考虑溶剂。结果表明,在一种以上的溶剂中测试一种化学物质时,不一致分类的数量增加了。此外,可以得出结论,导致最强分类(1A和EXT)分类的研究结果似乎比在最强分类中的分类更可靠。最弱的阶级。这项研究强调了评估非动物实验时考虑参考数据变异性的重要性。 (C)2016作者。由Elsevier Ltd.发布

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