Evidence map›Paper›PMID 38263624›Full record

ArticleEnvironmental science & technology2024

Chemical Space Covered by Applicability Domains of Quantitative Structure-Property Relationships and Semiempirical Relationships in Chemical Assessments.

Zhizhen Zhang, Alessandro Sangion, Shenghong Wang, Todd Gouin, Trevor Brown, Jon A Arnot, Li Li

Abstract read
In one paragraph

Article in Environmental science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  4. Article
  5. Environmental science & technology · 2025
    Review
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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

7 authors.

Zhizhen ZhangSchool of Public Health, University of Nevada, Reno, Reno, Nevada 89557, United States.ORCID 0000-0003-1128-1912
Alessandro SangionARC Arnot Research & Consulting, Toronto, Ontario M4M 1W4, Canada.
Shenghong WangSchool of Public Health, University of Nevada, Reno, Reno, Nevada 89557, United States.
Todd GouinTG Environmental Research, Sharnbrook, Bedford MK44 1PL, U.K.
Trevor BrownARC Arnot Research & Consulting, Toronto, Ontario M4M 1W4, Canada.
Jon A ArnotARC Arnot Research & Consulting, Toronto, Ontario M4M 1W4, Canada.
Li LiSchool of Public Health, University of Nevada, Reno, Reno, Nevada 89557, United States.ORCID 0000-0002-5157-7366

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.

Indexed as

applicability domainchemical assessmentchemical inventorieschemical propertyhazardquantitative structure−property relationships (QSPRs)

Identifiers

PMID38263624
PMCPMC10882972

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.