The future of metabolomics in toxicology looks promising as technological advances continue to enhance its capabilities. The integration of artificial intelligence and machine learning in data analysis is expected to improve the resolution and accuracy of metabolomic studies. Additionally, the development of global metabolomic databases will facilitate the sharing of data and the identification of universal biomarkers for various toxicological conditions.
