Evidence mapPaperPMID 41003772Full record

ArticleArchives of toxicology2026

From toxicogenomics data to cumulative assessment groups: a framework for chemical grouping.

Sebastian Canzler, Julienne Lehmann, Jana Schor, Wibke Busch, Giovanni Iacono, Jörg Hackermüller

Abstract read
In one paragraph

Article in Archives of toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Sebastian CanzlerDepartment Computational Biology and Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany. sebastian.canzler@ufz.de.
Julienne LehmannDepartment Computational Biology and Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany.
Jana SchorDepartment Computational Biology and Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany.
Wibke BuschDepartment Ecotoxicology, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany.
Giovanni IaconoEuropean Food Safety Authority (EFSA), 43126, Parma, Italy.
Jörg HackermüllerDepartment Computational Biology and Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany. joerg.hackermueller@ufz.de.

Funding

European Food Safety Authority OC/EFSA/IDATA/2022/01HORIZON EUROPE Reforming and enhancing the European Research and Innovation system Grant Agreement No 101057014
6 · The paper itself

Abstract

The grouping of chemicals based on common properties or molecular mechanisms of action is pivotal for advancing regulatory toxicology, reducing data gaps, and enabling cumulative risk assessments. This study introduces a novel framework using chemical-gene-phenotype-disease (CGPD) tetramers derived from the Comparative Toxicogenomics Database (CTD). Our approach integrates publicly available toxicogenomics data to identify and cluster chemicals with similar molecular and phenotypic effects. The considered chemicals belong to diverse use groups including pesticides, pharmaceuticals, and industrial chemicals. We validated our method by comparing CGPD tetramer-based clusters with cumulative assessment groups (CAGs) that have been established by EFSA for pesticides and demonstrate strong overlap with established groupings while identifying additional compounds relevant for risk assessment. Key examples include clusters associated with endocrine disruption and metabolic disorders. By bridging omics-derived molecular data with phenotypic and disease endpoints, this framework provides a comprehensive tool for chemical grouping and the support of evidence-based regulatory decision-making to facilitate the transition to next-generation risk assessment methodologies.

Indexed as

ToxicogeneticsAnimalsDatabases, FactualEndocrine DisruptorsHumansPesticidesPhenotypeRisk AssessmentEndocrine DisruptorsPesticidesChemical groupingCTDbaseData integrationTranscriptomics

Identifiers

PMID41003772
PMCPMC12858531

What Socratic 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 Socratic graph.