In the past, environmental health studies evaluated potential health effects of one chemical at a time. More recently, environmental epidemiologists consider the broader context of daily human exposures which encompass multiple exposures or a mixture of exposures at any point in time. There is an array of statistical methodologies available to evaluate how multiple exposures impact health and each one poses different strengths and weaknesses.
The PRIME program was developed to address the methodological challenges of mixtures analysis, stimulate novel methods, and enable resources for the broader research community.
Building on the historical efforts of the NIEHS Mixtures Program and previous workshops, NIEHS created the Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) program, launching a funding opportunity in 2017 (RFA ES 17-001). Projects supported through PRIME aim to develop innovative statistical methods and consider toxicology in modeling strategies.
PRIME encourages team science. Experts in epidemiology, biostatistics, toxicology, data science, informatics, and related fields are working together to develop and compare novel approaches, which may involve simulated, shared data, as well as real-world applications to human study populations.
The expected outcomes of PRIME include:
- Comparison of existing and new approaches to identify the strengths and weaknesses across methods for various exposure and disease contexts.
- Improved quantitative methods to better understand the complex relationships between environmental exposures and health outcomes.
- Informatics tools and related software for broad implementation of methods.
- New interdisciplinary methods for mixtures research in epidemiology.
- Resources for the research community including publications, webinars, example datasets, and training.
Funded PRIME Projects
PRIME grantees study how exposure to mixtures of metals, pesticides, endocrine disrupting chemicals, persistent organic pollutants, and air pollution affect health. Some researchers are also examining how non-chemical exposures, like stress and nutrition, may amplify or protect against the adverse health effects of a chemical mixture. Output of PRIME research includes publications as well as software and shared datasets.
The NIH RePORTER link lists all publications acknowledging a PRIME R01 as a funding source, but not all publications will be specific to the PRIME R01 aims.
Software and Shared Datasets
The PRIME GitHub site includes shared software in development, or previously developed and utilized, or expanding in a PRIME project. The GitHub also includes shared public and simulated datasets used for PRIME methods development.
Bonnie R. Joubert, Ph.D.
Health Scientist Administrator
P.O. Box 12233Mail Drop K3-12Durham, N.C. 27709
Grants Management Officer
San Diego, CA 92128
Leroy Worth Jr, Ph.D.
Scientific Review Officer
P.O. Box 12233Mail Drop K3-03Durham, N.C. 27709