Evidence map›Paper›PMID 39748807›Full record

ArticleCurrent opinion in toxicology2019

New Approach Methodologies for Exposure Science.

John F Wambaugh, Jane C Bare, Courtney C Carignan, Kathie L Dionisio, Robin E Dodson, Olivier Jolliet, Xiaoyu Liu, David E Meyer, Seth R Newton, Katherine A Phillips and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Current opinion in toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Incorporating a dermal absorption route into high throughput toxicokinetic modeling.Journal of exposure science & environmental epidemiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

John F WambaughNational Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Jane C BareNational Risk Management Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Cincinnati, OH 45268, USA.
Courtney C CarignanDepartment of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA.
Kathie L DionisioNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Robin E DodsonSilent Spring Institute, Newton, MA 02460, USA.
Olivier JollietEnvironmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
Xiaoyu LiuNational Risk Management Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
David E MeyerNational Risk Management Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Cincinnati, OH 45268, USA.
Seth R NewtonNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Katherine A PhillipsNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Paul S PriceNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Caroline L RingToxStrategies, Inc, Austin, TX, 78759, USA.
Hyeong-Moo ShinDepartment of Earth and Environmental Sciences, University of Texas, Arlington, TX 76019, USA.
Jon R SobusNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Tamara TalNational Health and Environmental Effects Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Elin M UlrichNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Daniel A ValleroNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Barbara A WetmoreNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Kristin K IsaacsNational Exposure Research Laboratory, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Chemical risk assessment relies on knowledge of hazard, the dose-response relationship, and exposure to characterize potential risks to public health and the environment. A chemical with minimal toxicity might pose a risk if exposures are extensive, repeated, and/or occurring during critical windows across the human life span. Exposure assessment involves understanding human activity, and this activity is confounded by interindividual variability that is both biological and behavioral. Exposures further vary between the general population and susceptible or occupationally exposed populations. Recent computational exposure efforts have tackled these problems through the creation of new tools and predictive models. These tools include machine learning to draw inferences from existing data and computer-enhanced screening analyses to generate new data. Mathematical models provide frameworks describing chemical exposure processes. These models can be statistically evaluated to establish rigorous confidence in their predictions. The computational exposure tools reviewed here are oriented toward 'high-throughput' application, that is, they are suitable for dealing with the thousands of chemicals in commerce with limited sources of chemical exposure information. These new tools and models are moving chemical exposure and risk assessment forward in the 21st century.

Identifiers

PMID39748807
PMCPMC11694839

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.