Evidence map›Paper›PMID 37288009›Full record

ArticleFrontiers in toxicology2023

From vision toward best practices: Evaluating

Anthony J F Reardon, Reza Farmahin, Andrew Williams, Matthew J Meier, Gregory C Addicks, Carole L Yauk, Geronimo Matteo, Ella Atlas, Joshua Harrill, Logan J Everett and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in toxicology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–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

29 citing papers in PubMed.

  1. Article
  2. Analytical choices drive toxicogenomic potency estimates: a systematic evaluation of transcriptomic points of departure.Toxicological sciences : an official journal of the Society of Toxicology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. In vitro models of the male reproductive system: applications for developmental and reproductive toxicology.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Advancing systemic toxicity risk assessment: Evaluation of a NAM-based toolbox approach.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  16. Review
  17. Review
  18. Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025
    Review
  19. Article
  20. Article
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

15 authors.

Anthony J F ReardonExisting Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
Reza FarmahinExisting Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
Andrew WilliamsEnvironmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
Matthew J MeierEnvironmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
Gregory C AddicksEnvironmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
Carole L YaukDepartment of Biology, University of Ottawa, Ottawa, ON, Canada.
Geronimo MatteoDepartment of Biology, University of Ottawa, Ottawa, ON, Canada.
Ella AtlasEnvironmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
Joshua HarrillCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States.
Logan J EverettCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States.
Imran ShahCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States.
Richard JudsonCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States.
Sreenivasa RamaiahgariDivision of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
Stephen S FergusonDivision of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States.
Tara S Barton-MaclarenExisting Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate

Indexed as

benchmark dose (BMD) modelingchemical safetyin vitro to in vivo extrapolation (IVIVE)NAMsnew approach methodstranscriptomics

Identifiers

PMID37288009
PMCPMC10242042

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.