The Chemical and Product Categories database (CPCat) catalogs the use of over 40,000 chemicals and their presence in different consumer products. The chemical use information is compiled from multiple sources while product information is gathered from publicly available Material Safety Data Sheets (MSDS). EPA researchers are evaluating the possibility of expanding the database with additional product and use information.

The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure predictions. The database currently includes biomonitoring exposure data from three studies: the American Healthy Homes Survey, the First National Environmental Health Survey of Child Care Centers and the Children's Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants study. Data include the amounts of chemicals found in food, drinking water, air, dust indoor surfaces and urine. The database will eventually include high-throughput exposure predictions for thousands of chemicals based on manufacture and use information. EPA researchers developed high-throughput exposure models to predict exposures for 1,763 chemicals using production volume, environmental fate and transport models, and a simple indicator of consumer product use.The model is being improved by adding more refined indoor and consumer use information since these are also large determinants of exposure. As these models are refined and more exposure data is collected, it will be added to ExpoCastDB.

The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure predictions. The database currently includes biomonitoring exposure data from three studies: the American Healthy Homes Survey, the First National Environmental Health Survey of Child Care Centers and the Children's Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants study. Data include the amounts of chemicals found in food, drinking water, air, dust indoor surfaces and urine. The database will eventually include high-throughput exposure predictions for thousands of chemicals based on manufacture and use information. EPA researchers developed high-throughput exposure models to predict exposures for 1,763 chemicals using production volume, environmental fate and transport models, and a simple indicator of consumer product use.The model is being improved by adding more refined indoor and consumer use information since these are also large determinants of exposure. As these models are refined and more exposure data is collected, it will be added to ExpoCastDB.

EPA researchers have been using advances in computational toxicology to address lack of data on the thousands of chemicals. EPA released chemical data on 1,800 chemicals. The 1,800 chemicals were screened in more than 800 rapid, automated tests (called high-throughput screening assays) to determine potential human health effects. The data is available through the interactive Chemical Safety for Sustainability Dashboards (iCSS dashboard) and the complete data sets are also available for download.

EPA researchers have been using advances in computational toxicology to address lack of data on the thousands of chemicals. EPA released chemical data on 1,800 chemicals. The 1,800 chemicals were screened in more than 800 rapid, automated tests (called high-throughput screening assays) to determine potential human health effects. The data is available through the interactive Chemical Safety for Sustainability Dashboards (iCSS dashboard) and the complete data sets are also available for download.

This dataset represents quantitative data on product chemical composition for >75,000 chemicals contained in >15,000 consumer products. The dataset provided at the FigShare link is fully described in the associated Scientific Data publication (Dionisio et al.). The dataset is presented in the form of a MySQL relational database, which mimics CPDat data available under the 'Exposure' tab of the CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard). This dataset is associated with the following publication: Dionisio, K., K. Phillips, P. Price, C. Grulke, A. Williams, D. Biryol, T. Hong, and K. Isaacs. The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products. Scientific Data. Springer Nature Group, New York, NY, 5: 180125, (2018).

This dataset represents quantitative data on product chemical composition for >75,000 chemicals contained in >15,000 consumer products. The dataset provided at the FigShare link is fully described in the associated Scientific Data publication (Dionisio et al.). The dataset is presented in the form of a MySQL relational database, which mimics CPDat data available under the 'Exposure' tab of the CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard). This dataset is associated with the following publication: Dionisio, K., K. Phillips, P. Price, C. Grulke, A. Williams, D. Biryol, T. Hong, and K. Isaacs. The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products. Scientific Data. Springer Nature Group, New York, NY, 5: 180125, (2018).

Background: Chemicals in consumer products are a major contributor to human chemical co-exposures. Consumers purchase and use a wide variety of products containing potentially thousands of chemicals. There is a need to identify potential real-world chemical co-exposures in order to prioritize in vitro toxicity screening. However, due to the vast number of potential chemical combinations, this has been a major challenge. Objectives: We aim to develop and implement a data-driven procedure for identifying prevalent chemical combinations to which humans are exposed through purchase and use of consumer products. Methods: We applied frequent itemset mining on an integrated dataset linking consumer product chemical ingredient data with product purchasing data from sixty thousand households to identify chemical combinations resulting from co-use of consumer products. Results: We identified co-occurrence patterns of chemicals over all households as well as those specific to demographic groups based on race/ethnicity, income, education, and family composition. We also identified chemicals with the highest potential for aggregate exposure by identifying chemicals occurring in multiple products used by the same household. Lastly, a case study of chemicals active in estrogen and androgen receptor in silico models revealed priority chemical combinations co-targeting receptors involved in important biological signaling pathways. Discussion: Integration and comprehensive analysis of household purchasing data and product-chemical information provided a means to assess human near-field exposure and inform selection of chemical combinations for high-throughput screening in in vitro assays. This dataset is associated with the following publication: Stanfield, Z., C. Addington, K. Dionisio, D. Lyons, R. Tornero-Velez, K. Phillips, T. Buckley, and K. Isaacs. Mining of consumer product and purchasing data to identify potential chemical co-exposures.. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 129(6): N/A, (2021).

The Acute Exposure Guideline Levels Chemical Listing provides a complete listing of risk exposure guidelines from rare exposure to certain chemicals.

The Acute Exposure Guideline Levels Chemical Listing provides a complete listing of risk exposure guidelines from rare exposure to certain chemicals.