Evidence map›Paper›PMID 39584503›Full record

ArticleALTEX2025

A systematic analysis of read-across adaptations in testing proposal evaluations by the European Chemicals Agency.

Hannah M Roe, Han-Hsaun D Tsai, Nicholas Ball, Fred A Wright, Weihsueh A Chiu, Ivan Rusyn

Abstract read
In one paragraph

Article in ALTEX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Hannah M RoeDepartment of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.
Han-Hsaun D TsaiDepartment of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.
Nicholas BallThe Dow Chemical Company, Horgen, Switzerland.
Fred A WrightDepartments of Statistics and Biological Sciences, North Carolina State University, Raleigh, NC, USA.
Weihsueh A ChiuDepartment of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.
Ivan RusynDepartment of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA.

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Efstratios Pistikopoulos · 2017 to 2026
$21.2M
Regulatory Science in Environmental Health and ToxicologyT32ES026568 · NIEHS · TEXAS A&M UNIVERSITY · PI Weihsueh A Chiu, Natalie M Johnson · 2016 to 2026
$3.8M
NIEHS NIH HHS P42 ES027704NIEHS NIH HHS T32 ES026568
6 · The paper itself

Abstract

An essential aspect of the EU’s Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulation is the European Chemicals Agency’s (ECHA) evaluation of testing proposals submitted by registrants to address data gaps. Registrants may propose adaptations, such as read-across, to waive standard testing; however, it is widely believed that ECHA often finds justifications for read-across hypotheses inadequate. From 2008 to August 2023, 2,630 testing proposals were submitted to ECHA; of these, 1,538 had published decisions that were systematically evaluated in this study. Each document was manually reviewed and information extracted for further analyses, focusing on 17 assessment elements (AEs) from the Read-Across Assessment Framework (RAAF) and testing proposal evaluations (TPE). Each submission was classified as to the AEs relied upon by the registrants and by ECHA. Data was analyzed for patterns and associations. Adaptations were included in 23% (350) of proposals, with analogue (168) and group (136) read-across being most common. Of the 304 read-across hypotheses, 49% were accepted, with group read-across showing significantly higher odds of acceptance. Data analysis examined factors such as tonnage band (Annex), test guidelines, hypothesis AEs, and structural similarities of target and source sub­stances. While decisions were often context-specific, several significant associations influencing acceptance emerged. Overall, this analysis provides a comprehensive overview of 15 years of experience with testing proposal-specific read-across adaptations by both registrants and ECHA. These data will inform future submissions as they identify most critical AEs to increase the odds of read-across acceptance.

Indexed as

Animal Testing AlternativesHazardous SubstancesToxicity TestsEuropeEuropean UnionHumansHazardous SubstancesadaptationsECHAOECD test guideline studiesREACHread-across

Identifiers

PMID39584503
PMCPMC11976166

What OpenQuestion holds

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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.