In silico testing refers to the use of computational models and simulations to predict the toxicological properties of chemical compounds. These models utilize existing data and knowledge about chemical structures and biological mechanisms to forecast potential adverse effects without the need for extensive laboratory testing. In silico approaches can include QSAR models, molecular docking, and machine learning algorithms.
