药品
肝损伤
医学
毒性
药物毒性
药理学
药物开发
假阳性悖论
肝毒性
内科学
计算机科学
机器学习
作者
Shraddha Thakkar,Ting Li,Zhichao Liu,Weida Tong,Ruth Roberts,Weida Tong
标识
DOI:10.1016/j.drudis.2019.09.022
摘要
Drug-induced liver injury (DILI) is of significant concern to drug development and regulatory review because of the limited success with existing preclinical models. For developing alternative methods, a large drug list is needed with known DILI severity and toxicity. We augmented the DILIrank data set [annotated using US Food and Drug Administration (FDA) drug labeling)] with four literature datasets (N >350 drugs) to generate the largest drug list with DILI classification, called DILIst (DILI severity and toxicity). DILIst comprises 1279 drugs, of which 768 were DILI positives (increase of 65% from DILIrank), whereas 511 were DILI negatives (increase of 65%). The investigation of DILI positive–negative distribution across various therapeutic categories revealed the most and least frequent DILI categories. Thus, we consider DILIst to be an invaluable resource for the community to improve DILI research.
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