Computational toxicology involves a variety of approaches, including Quantitative Structure-Activity Relationship (QSAR) models, molecular docking, and machine learning algorithms. These methods allow scientists to predict the interaction between chemicals and biological systems. By analyzing chemical structures and biological pathways, computational models can forecast potential toxic effects and identify mechanisms of action.
