The increasing number of chemicals for which SHEDS probabilistic exposure assessment has been performed over the years. This dataset is associated with the following publication: Egeghy , P., L. Sheldon, K. Isaacs , H. Ozkaynak, M. Goldsmith, J. Wambaugh , R. Judson , and T. Buckley. Computational Exposure Science: An Emerging Discipline to Support 21st-Century Risk Assessment. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 124(6): 697–702, (2016).

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).

Datasets associated with the publication "Establishing a System of Consumer Products Categories to Support Rapid Modeling of Human Exposure". This dataset is associated with the following publication: Isaacs, K., K. Dionisio, K. Phillips, C. Bevington, P. Egeghy, and P. Price. Establishing a system of consumer product use categories to support rapid modeling of human exposure. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 30: 171-183, (2020).

Datasets associated with the publication "Establishing a System of Consumer Products Categories to Support Rapid Modeling of Human Exposure". This dataset is associated with the following publication: Isaacs, K., K. Dionisio, K. Phillips, C. Bevington, P. Egeghy, and P. Price. Establishing a system of consumer product use categories to support rapid modeling of human exposure. Journal of Exposure Science and Environmental Epidemiology. Nature Publishing Group, London, UK, 30: 171-183, (2020).

This dataset describes concentrations of DEHP in numerous types of environmental, biological, and manufactured media, along with rates of transformation and transportation. The references used to obtain this information, along with their authors, locations of study, and year of study, are also available. This dataset is associated with the following publication: Clewell, R., J. Leonard, C. Nicolas, J. Cambpell, M. Yoon, A. Efremenko, P. McMullen, M. Andersen, H. Clewell, K. Phillips, and C. Tan. Application of a combined aggregate exposure pathway and adverse outcome pathway (AEP-AOP) approach to inform a cumulative risk assessment: A case study with phthalates. TOXICOLOGY IN VITRO. Elsevier Science Ltd, New York, NY, USA, 66: 104855, (2020).

The Human Exposure Database System (HEDS) provides public access to data sets, documents, and metadata from EPA on human exposure. It is primarily intended for scientists involved in human exposure studies or work requiring such data.

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).

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 paper has data generated by NIH and the EPA coauthors provided input into the preparation of the manuscript. This dataset is not publicly accessible because: Data was not collected in EPA labs or paid for by EPA. It can be accessed through the following means: Data generated by NIH. Format: N/A. This dataset is associated with the following publication: Lynch, C., S. Sakamuru, R. Huang, D.A. Stavea, L. Varticovski, G.L. Hagar, R.S. Judson, K.A. Houck, N.C. Kleinstreuer, W. Casey, R.S. Paules, A. Simeonov, and M. Xia. (Toxicology) Identifying Environmental Chemicals as Agonists of the Androgen Receptor by Applying a Quantitative High-throughput Screening Platform. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 385: 48-58, (2017).