Big data enables the analysis of vast amounts of information from diverse sources such as genomic, proteomic, and metabolomic studies. This comprehensive approach allows researchers to identify patterns and associations that were previously undetectable. For instance, analyzing data from multiple studies can lead to the discovery of biomarkers that predict toxic responses to specific chemicals.
Moreover, big data facilitates predictive modeling, which is crucial for assessing the potential risks of new substances. By using machine learning algorithms, toxicologists can predict the adverse effects of chemicals before they are tested in animal models, thereby reducing the need for animal testing.
