Traditional methods of toxicity testing, such as animal testing, are time-consuming and ethically challenging. AI and ML can predict toxicity by analyzing chemical structures and biological data. For instance, ML models can be trained on datasets containing information about chemicals and their known toxic effects. These models can then predict the toxicity of new, untested compounds with high accuracy.
