Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework Article Swipe
YOU?
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· 2016
· Open Access
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· DOI: https://doi.org/10.1021/acs.est.5b05311
Driven by major scientific advances in analytical methods, biomonitoring, computation, and a newly articulated vision for a greater impact in public health, the field of exposure science is undergoing a rapid transition from a field of observation to a field of prediction. Deployment of an organizational and predictive framework for exposure science analogous to the "systems approaches" used in the biological sciences is a necessary step in this evolution. Here we propose the aggregate exposure pathway (AEP) concept as the natural and complementary companion in the exposure sciences to the adverse outcome pathway (AOP) concept in the toxicological sciences. Aggregate exposure pathways offer an intuitive framework to organize exposure data within individual units of prediction common to the field, setting the stage for exposure forecasting. Looking farther ahead, we envision direct linkages between aggregate exposure pathways and adverse outcome pathways, completing the source to outcome continuum for more meaningful integration of exposure assessment and hazard identification. Together, the two frameworks form and inform a decision-making framework with the flexibility for risk-based, hazard-based, or exposure-based decision making.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1021/acs.est.5b05311
- OA Status
- green
- Cited By
- 127
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2238431257
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2238431257Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1021/acs.est.5b05311Digital Object Identifier
- Title
-
Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway FrameworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-01-13Full publication date if available
- Authors
-
Justin Teeguarden, Yu‐Mei Tan, Stephen W. Edwards, Jeremy A. Leonard, Kim A. Anderson, Richard Corley, Molly L. Kile, Staci Massey Simonich, David Stone, Robert L. Tanguay, Katrina M. Waters, Stacey L. Harper, David E. WilliamsList of authors in order
- Landing page
-
https://doi.org/10.1021/acs.est.5b05311Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.osti.gov/biblio/1249371Direct OA link when available
- Concepts
-
Aggregate (composite), Environmental toxicology, Link (geometry), Exposure assessment, Toxicology, Environmental science, Environmental health, Computer science, Medicine, Toxicity, Biology, Nanotechnology, Materials science, Computer network, Internal medicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
127Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 11, 2024: 14, 2023: 16, 2022: 7, 2021: 10Per-year citation counts (last 5 years)
- References (count)
-
37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.decision | 174 |
| abstract_inverted_index.envision | 129 |
| abstract_inverted_index.exposure | 25, 50, 74, 86, 100, 108, 123, 134, 151 |
| abstract_inverted_index.linkages | 131 |
| abstract_inverted_index.methods, | 7 |
| abstract_inverted_index.organize | 107 |
| abstract_inverted_index.pathways | 101, 135 |
| abstract_inverted_index.sciences | 61, 87 |
| abstract_inverted_index.Aggregate | 99 |
| abstract_inverted_index.Together, | 156 |
| abstract_inverted_index.aggregate | 73, 133 |
| abstract_inverted_index.analogous | 52 |
| abstract_inverted_index.companion | 83 |
| abstract_inverted_index.continuum | 145 |
| abstract_inverted_index.framework | 48, 105, 165 |
| abstract_inverted_index.intuitive | 104 |
| abstract_inverted_index.necessary | 64 |
| abstract_inverted_index.pathways, | 139 |
| abstract_inverted_index.sciences. | 98 |
| abstract_inverted_index.Deployment | 42 |
| abstract_inverted_index.analytical | 6 |
| abstract_inverted_index.assessment | 152 |
| abstract_inverted_index.biological | 60 |
| abstract_inverted_index.completing | 140 |
| abstract_inverted_index.evolution. | 68 |
| abstract_inverted_index.frameworks | 159 |
| abstract_inverted_index.individual | 111 |
| abstract_inverted_index.meaningful | 148 |
| abstract_inverted_index.prediction | 114 |
| abstract_inverted_index.predictive | 47 |
| abstract_inverted_index.scientific | 3 |
| abstract_inverted_index.transition | 31 |
| abstract_inverted_index.undergoing | 28 |
| abstract_inverted_index.approaches" | 56 |
| abstract_inverted_index.articulated | 13 |
| abstract_inverted_index.flexibility | 168 |
| abstract_inverted_index.integration | 149 |
| abstract_inverted_index.observation | 36 |
| abstract_inverted_index.prediction. | 41 |
| abstract_inverted_index.risk-based, | 170 |
| abstract_inverted_index.computation, | 9 |
| abstract_inverted_index.forecasting. | 124 |
| abstract_inverted_index.complementary | 82 |
| abstract_inverted_index.hazard-based, | 171 |
| abstract_inverted_index.toxicological | 97 |
| abstract_inverted_index.biomonitoring, | 8 |
| abstract_inverted_index.exposure-based | 173 |
| abstract_inverted_index.organizational | 45 |
| abstract_inverted_index.decision-making | 164 |
| abstract_inverted_index.identification. | 155 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 98 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 13 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.6200000047683716 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.99797092 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |