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Your Environment. Your Health.

SRP Highlighted at Data Science Symposium

Stefano Monti and Michelle Heacock

Monti, left, with Heacock, right, during the symposium at the University of Cincinnati.
(Photo courtesy of Michelle Heacock)

Superfund Research Program (SRP) representatives provided the environmental health perspective on big data at an NIH data science symposium May 16 - 18 in Cincinnati. The symposium was hosted by the NIH Big Data to Knowledge (BD2K) and Library of Integrated Network-Based Cellular Signatures (LINCS) Data Coordination and Integration Center.

The BD2K-LINCS Data Science Symposium brought together scientists from academia, industry, and government to talk about using large datasets to improve drug development, biomedicine, and environmental health research.

SRP Health Scientist Administrator Michelle Heacock, Ph.D., presented NIEHS efforts to understand what people are exposed to in the environment and whether those exposures affect our health. She discussed such issues as the timing of exposure and the organ or tissue that may be affected by it.

She also discussed how big data may be used to estimate how the body responds to multiple chemicals. For example, she described the NIEHS-funded Comparative Toxicogenomics Database (CTD), a compilation of manually curated data about interactions between chemicals, genes, and diseases. With the CTD, researchers can identify different chemicals that lead to changes to genes and proteins in the body. By integrating these data with information about molecular pathways, they can also identify whether these changes are linked to human diseases.

Heacock also provided an overview of the SRP and described how diverse types of SRP data may be used together. She encouraged researchers to leverage existing data and to share their data with other scientists.

Stefano Monti, Ph.D., a professor at the Boston University (BU) School of Public Health and a BU SRP Center grantee, discussed his work using large datasets to screen for chemicals that may cause cancer. He highlighted his collaboration with the NIEHS National Toxicology Program using computational models to predict long-term cancer risk based on data from short-term exposure studies. This project is a step toward simpler and cheaper tests to screen chemicals for cancer risk.

Monti and Heacock also participated in a panel that focused on improving the use of big data in environmental health science.

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