Software Beats Animal Tests at Predicting Toxicity of Chemicals

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Machine-learning software trained on masses of chemical-safety data is so good at predicting some kinds of toxicity that it now rivals — and sometimes outperforms — expensive animal studies, researchers report. From a report: Computer models could replace some standard safety studies conducted on millions of animals each year, such as dropping compounds into rabbits’ eyes to check if they are irritants, or feeding chemicals to rats to work out lethal doses, says Thomas Hartung, a toxicologist at Johns Hopkins

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