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Mining of Consumer Product and Purchasing Data to Identify Potential Chemical Co-exposures
Citation:
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. ISES 2020, Virtual, Virtual, September 21 - 22, 2020. https://doi.org/10.23645/epacomptox.13268930
Impact/Purpose:
This research presents a data-driven method for identifying priority chemical combinations for testing in high-throughput screening programs.Poster to be presented at the ISES 2020 meeting in September 2020.
Description:
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 to prioritize in vitro toxicity screening. However, due to the vast number of potential chemical combinations, this has been a major challenge. Objectives: To develop a data-driven procedure for identifying prevalent chemical combinations that 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 60,000 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. We also identified chemicals exhibiting aggregate exposure. Lastly, a case study of endocrine active chemicals revealed priority chemical combinations co-targeting receptors involved in 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 sets of chemicals for high-throughput screening in in vitro assays.
URLs/Downloads:
DOI: Mining of Consumer Product and Purchasing Data to Identify Potential Chemical Co-exposures
ISES2020POSTER_FIMSTANFIELD_V2.PDF (PDF, NA pp, 2666.533 KB, about PDF)