Cell Painting and Chemical Structure Read-Across Can Complement Each Other for Rat Acute Oral Toxicity Prediction in Chemical Early Derisking

体内 毒性 急性毒性 训练集 化学结构 化学毒性 体外 化学 毒理 计算生物学 计算机科学 人工智能 生物化学 生物 生物技术 有机化学
作者
F. Camilleri,J. Wenda,C. Pecoraro-Mercier,Jean‐Paul Comet,David Rouquié
出处
期刊:Chemical Research in Toxicology [American Chemical Society]
卷期号:37 (11): 1851-1866 被引量:4
标识
DOI:10.1021/acs.chemrestox.4c00169
摘要

Early derisking decisions in the development of new chemical compounds enable the identification of novel chemical candidates with improved safety profiles. In vivo studies are traditionally conducted in the early assessment of acute oral toxicity of crop protection products to avoid compounds, which are considered "very acutely toxic", with an in vivo lethal dose of 50% (LD50) ≤ 60 mg/kg body weight. Those studies are lengthy and costly and raise ethical concerns, catalyzing the use of nonanimal alternatives. The objective of our analysis was to assess the predictive efficacy of read-across approaches for acute oral toxicity in rats, comparing the use of chemical structure information, in vitro biological data derived from the Cell Painting profiling assay on U2OS cells, or the combination of both. Our findings indicate that the classification of compounds as very acute oral toxic (LD50 ≤ 60 mg/kg) or not is possible using a read-across approach, with chemical structure information, morphological profiles, or a combination of both. When classifying compounds structurally similar to those in the training set, the chemical structure was more predictive (balanced accuracy of 0.82). Conversely, when the compounds to be classified were structurally different from those in the training set, the morphological profiles were more predictive (balanced accuracy of 0.72). Combining the two models allowed for the classification of compounds structurally similar to those in the training set to slightly improve the predictions (balanced accuracy of 0.85).
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