Evidence map›Paper›PMID 32424443›Full record

ReviewArchives of toxicology2020

Quantitative adverse outcome pathway (qAOP) models for toxicity prediction.

Nicoleta Spinu, Mark T D Cronin, Steven J Enoch, Judith C Madden, Andrew P Worth

Abstract readReview
In one paragraph

Review in Archives of toxicology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Unveiling toxicological adverse outcomes: toward construction and simulation of large-scale networks.Toxicological sciences : an official journal of the Society of Toxicology · 2026
    Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Adverse Outcome Pathways Mechanistically Describing Hepatotoxicity.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

5 authors.

Nicoleta SpinuSchool of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.ORCID http://orcid.org/0000-0002-9465-3090
Mark T D CroninSchool of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.ORCID http://orcid.org/0000-0002-6207-4158
Steven J EnochSchool of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.ORCID http://orcid.org/0000-0001-9111-5783
Judith C MaddenSchool of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.ORCID http://orcid.org/0000-0001-6142-5860
Andrew P WorthEuropean Commission, Joint Research Centre (JRC), Ispra, Italy. andrew.worth@ec.europa.eu.ORCID http://orcid.org/0000-0002-5303-0452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The quantitative adverse outcome pathway (qAOP) concept is gaining interest due to its potential regulatory applications in chemical risk assessment. Even though an increasing number of qAOP models are being proposed as computational predictive tools, there is no framework to guide their development and assessment. As such, the objectives of this review were to: (i) analyse the definitions of qAOPs published in the scientific literature, (ii) define a set of common features of existing qAOP models derived from the published definitions, and (iii) identify and assess the existing published qAOP models and associated software tools. As a result, five probabilistic qAOPs and ten mechanistic qAOPs were evaluated against the common features. The review offers an overview of how the qAOP concept has advanced and how it can aid toxicity assessment in the future. Further efforts are required to achieve validation, harmonisation and regulatory acceptance of qAOP models.

Indexed as

Adverse Outcome PathwaysToxicity TestsAnimalsForecastingHumansRisk AssessmentSoftwareBayesian networkComputational approachKey event relationshipPredictive toxicologyQuantitative adverse outcome pathway (qAOP)Response-response relationship

Identifiers

PMID32424443
PMCPMC7261727

What OpenQuestion holds

Textmetadata
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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.