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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/11036


    Title: Mechanism-informed read-across assessment of skin sensitizers based on SkinSensDB
    Authors: Tung, CW;Wang, CC;Wang, SS
    Contributors: National Institute of Environmental Health Sciences
    Abstract: 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.
    Date: 2018-04
    Relation: Regulatory Toxicology and Pharmacology. 2018 Apr;94:276-282.
    Link to: http://dx.doi.org/10.1016/j.yrtph.2018.02.014
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0273-2300&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000430137400029
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85042730172
    Appears in Collections:[童俊維] 期刊論文

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