The future of genomic data in toxicology looks promising with advances in precision medicine and personalized healthcare. The integration of multi-omics data, including genomics, proteomics, and metabolomics, will provide a holistic understanding of toxicological responses. Furthermore, the development of artificial intelligence and machine learning algorithms will enhance the predictive power of genomic data, leading to more accurate and individualized risk assessments.
