Toxicity prediction remains a longstanding challenge in the safety assessment of numerous artificial chemicals. While conventional single-endpoint models are effective for predicting many molecular properties, they fail to capture the complex mechanisms underlying toxicity, which involve multiple molecular targets, int...
Hao-Yue Tan, Tong Bao, Yin Fang et al.· Proceedings of the National...· 0 citations
This review examines the theoretical foundations and practical implementation of MTL in predictive toxicology and drug metabolism, and evaluates benchmark datasets, ADME–Tox integration strategies, mechanistically informed task grouping, transfer learning, and validation frameworks.
Hui-Xiao Hong, Jie Liu, Wen-Jing Guo et al.· Expert Opinion on Drug Metab...· 0 citations
The effectiveness of integrating high-throughput assay data with chemical structure analysis to enable reliable in silico prediction of neurotoxicity is demonstrated, offering a scalable and animal-free approach for assisting chemical safety assessment.
Zoe Li, Li Zhang, Tuan Xu et al.· Chemical Research in Toxicol...· 0 citations
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