How "big" should the data be to make an impact in toxicology? Learnings from disaster research

抄録

Climate change and shifts in economic activity markedly increase risks from catastrophic chemical contamination events resulting from climate-related or man-made emergencies. The complexities of hazardous chemical exposures, potential adverse health impacts, and the need to rapidly and comprehensively evaluate environmental mixtures call for novel approach methods to disasters. Disaster research is possible when a team of scientists from biomedical, epidemiological, data and engineering disciplines come together to design comprehensive solutions for complex exposure- and hazard-related challenges. New approach methods for rapid exposure and hazard characterization involve a number of sensitive analytical and toxicological methods that generate large amounts of information that can be classified as “big data.” However, toxicologists and risk assessors are not usually trained in the analysis of “big data” and need to collaborate with the data scientists and statisticians. This presentation will describe the efforts of the Superfund Research Center at Texas A&M University that is developing exposure and hazard assessment tools that can be used by the first responders, impacted communities, and the government agencies. We created a number of computational and statistical methods for analysis and integration of “big data” in environmental health. In addition, we work closely with industry and government decision-makers to determine what types of “big data” are most useful and how best to communicate large amounts of information to support environmental health decisions.