Predictive toxicology tools utilize algorithms and databases to estimate the toxicity of substances. These programs often rely on machine learning and artificial intelligence to improve prediction accuracy. By inputting the chemical structure of a substance, the software can predict potential toxicological endpoints, such as carcinogenicity or reproductive toxicity, thereby aiding decision-making in drug development and chemical manufacturing.
