AI and ML algorithms are capable of analyzing vast datasets to identify patterns and correlations that might not be apparent through traditional methods. This capability enables the prediction of chemical toxicity with greater precision. For instance, AI models can integrate data from various sources, such as genomic, proteomic, and metabolomic datasets, to predict the toxic potential of new compounds.
