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Screening for drinking water contaminants of concern using an automated exposure-focused workflow



The number of chemicals present in the environment exceeds the capacity of government bodies to characterize risk. Therefore, data-informed and reproducible processes are needed for identifying chemicals for further assessment. The Minnesota Department of Health (MDH), under its Contaminants of Emerging Concern (CEC) initiative, uses a standardized process to screen potential drinking water contaminants based on toxicity and exposure potential.


Recently, MDH partnered with the U.S. Environmental Protection Agency (EPA) Office of Research and Development (ORD) to accelerate the screening process via development of an automated workflow accessing relevant exposure data, including exposure new approach methodologies (NAMs) from ORD’s ExpoCast project.


The workflow incorporated information from 27 data sources related to persistence and fate, release potential, water occurrence, and exposure potential, making use of ORD tools for harmonization of chemical names and identifiers. The workflow also incorporated data and criteria specific to Minnesota and MDH’s regulatory authority. The collected data were used to score chemicals using quantitative algorithms developed by MDH. The workflow was applied to 1867 case study chemicals, including 82 chemicals that were previously manually evaluated by MDH.


Evaluation of the automated and manual results for these 82 chemicals indicated reasonable agreement between the scores although agreement depended on data availability; automated scores were lower than manual scores for chemicals with fewer available data. Case study chemicals with high exposure scores included disinfection by-products, pharmaceuticals, consumer product chemicals, per- and polyfluoroalkyl substances, pesticides, and metals. Scores were integrated with in vitro bioactivity data to assess the feasibility of using NAMs for further risk prioritization.


This workflow will allow MDH to accelerate exposure screening and expand the number of chemicals examined, freeing resources for in-depth assessments. The workflow will be useful in screening large libraries of chemicals for candidates for the CEC program.

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Fig. 1: Overview of the exposure screening workflow.
Fig. 2: Comparison of manual and automated scores.
Fig. 3: Exposure case study results.
Fig. 4: Bioactivity-to-exposure ratios for chemicals with high exposure scores.

Data availability

The results of the automated workflow for the case study chemicals and raw data values for each source and criteria are included in the Supplemental files.


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The authors would like to thank Drs Peter Egeghy and Katherine Phillips of the US EPA for their technical review of this paper. The information in this document has been funded wholly or in part by the US Environmental Protection Agency. It does not signify that the contents necessarily reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. The paper has been subjected to the Agency’s review process and approved for publication.

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Authors and Affiliations



KKI designed workflow organization and data source integration, performed data analyses, and drafted figures, tables, and text. JTW designed and implemented workflow code, scoring algorithms, and reporting formats, and performed workflow runs. KPF performed bioactivity, toxicokinetic, and BER analyses and contributed associated text. AJW provided chemistry data support and contributed to text. JAF, ML, and JCL provided management support for the ORD/MDH CRADA project. AS provided management support for the workflow database and information technology infrastructure. KLD and JFW developed exposure and toxicokinetic NAM methods and datasets. HG, AJB, and CG of MDH developed the workflow criteria and scoring under the CEC program, provided manual scoring results, performed data analyses, and contributed to text.

Corresponding author

Correspondence to Kristin K. Isaacs.

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No human data not otherwise publicly available were analyzed herein.

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Isaacs, K.K., Wall, J.T., Paul Friedman, K. et al. Screening for drinking water contaminants of concern using an automated exposure-focused workflow. J Expo Sci Environ Epidemiol (2023).

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  • Emerging Contaminants
  • Exposure Modeling
  • New Approach Methodologies (NAMs)
  • Environmental Monitoring


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