The Decisive Role of Artificial Intelligence in Toxicology: Advancements and Applications
Kizhakkepurakkal Balachandran Megha, SS Athira, N Greeshma, Aswathy V S, RY Manjoosha, J Renu, PV Mohanan · 2025
The intersection of artificial intelligence and toxicology has created a new era of innovation and a changing landscape of toxicity assessment and management. The role of AI in predictive toxicology using machine learning algorithms to analyse huge datasets to forecast the toxicity of chemical compounds with remarkable accuracy is highly competent. AI models are developed to predict the adverse effects of chemical exposure on human health. The integration of omics data, like proteomics, genomics, metabolomics, etc with a machine learning approach elucidates the intricate toxicity mechanisms and identification of biomarkers for early detection of adverse effects. AI can play an important role in chemical risk assessment, data analysis, and interpretation creating evidence-based decisions promptly. AI in toxicology is paving the way to provide more accurate, cost-effective, and ethically responsible decisions for toxicity assessment and risk management. The influence of AI has reached the various branches of toxicology. One of the highlighted features is reduction in in vivo studies can be achieved. AI enhances the predictive capabilities and ultimately mitigates the adverse effects of chemical exposure on human health and the environment.