https://scholars.lib.ntu.edu.tw/handle/123456789/573152
標題: | Mechanism-informed read-across assessment of skin sensitizers based on SkinSensDB | 作者: | Tung C.-W CHIA-CHI WANG Wang S.-S. |
關鍵字: | 4 aminobenzoic acid; alpha tocopherol; benzen 1 methoxy 4 methyl 2 nitro; butanol; citronellol; diethyltoluamide; photosensitizing agent; phthalic acid; pyridine; salicylic acid benzyl ester; salicylic acid hexyl ester; unclassified drug; hapten; adverse outcome pathway; Article; controlled study; data base; diagnostic test accuracy study; human; local lymph node assay; measurement accuracy; prediction; priority journal; read across assessment; receiver operating characteristic; sensitivity and specificity; skin sensitization; SkinSensDB database; animal testing alternative; decision tree; factual database; procedures; risk assessment; skin test; Animal Testing Alternatives; Databases, Factual; Decision Trees; Haptens; Humans; Local Lymph Node Assay; Risk Assessment; Skin Tests | 公開日期: | 2018 | 卷: | 94 | 起(迄)頁: | 276-282 | 來源出版物: | Regulatory Toxicology and Pharmacology | 摘要: | Integrative testing strategies using adverse outcome pathway (AOP)-based alternative assays for assessing skin sensitizers show the potential for replacing animal testing. However, the application of alternative assays for a large number of chemicals is still time-consuming and expensive. In order to facilitate the assessment of skin sensitizers based on integrative testing strategies, a mechanism-informed read-across assessment method was proposed and evaluated using data from SkinSensDB. First, the prediction performance of two integrated testing strategy models was evaluated giving the highest area under the receiver operating characteristic curve (AUC) values of 0.928 and 0.837 for predicting human and LLNA data, respectively. The proposed read-across prediction method achieves AUC values of 0.957 and 0.802 for predicting human and LLNA data, respectively, with interpretable activation statuses of AOP events. As data grows, a better prediction performance is expected. A user-friendly tool has been constructed and integrated into SkinSensDB that is publicly accessible at http://cwtung.kmu.edu.tw/skinsensdb. ? 2018 Elsevier Inc. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042730172&doi=10.1016%2fj.yrtph.2018.02.014&partnerID=40&md5=3b3d46f0aad0ec22183fbf644d01aed2 https://scholars.lib.ntu.edu.tw/handle/123456789/573152 |
ISSN: | 2732300 | DOI: | 10.1016/j.yrtph.2018.02.014 |
顯示於: | 獸醫學系 |
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