Evidence map›Paper›PMID 40745925›Full record

ArticleALTEX2026

What does "success" look like in compliance check decisions by the European Chemicals Agency? The curious cases of accepted read-across adaptations.

Hannah M Roe, Han-Hsuan D Tsai, Nicholas Ball, King D Oware, Gang Han, Weihsueh A Chiu, Ivan Rusyn

Abstract read
In one paragraph

Article in ALTEX, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 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-Hsuan 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.
King D OwareDepartment of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, USA.
Gang HanDepartment of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX, 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

Under the European Union’s REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals) regulation, the European Chemicals Agency (ECHA) is required to assess the compliance of safety data submitted by chemical registrants. ECHA must check a proportion of registration dos­siers for compliance. From 2010 to 2023, 4,854 compliance checks (CCHs) were conducted. When dossiers lack required studies or use inappropriate adaptations, ECHA issues decisions that are publicly available. As of April 2, 2024, 2,311 such decisions had been published. This study sys­tematically analyzed these published CCH decisions, focusing on ECHA’s findings of non-compliant REACH registrations and the use of adaptations to standard information requirements. We found that over 70% of published CCH decisions included at least one adaptation, with “read-across” being the most common (48%). Among these, 83 documents contained read-across adaptations with jus­tifications that ECHA deemed plausible. To understand what made these read-across hypotheses acceptable, we evaluated them using 17 assessment elements that capture specific arguments regis­trants proposed to justify the adaptation. Elements of “acceptable” read-across hypotheses included strong evidence of (i) toxicokinetic similarity between the registered substance and its analogues, and (ii) toxicodynamic similarity, supported by bridging studies. Additional support from in vitro studies and QSAR predictions further strengthened the accepted read-across hypotheses. Overall, this analysis provides insights into what constitutes a successful read-across under REACH data requirements. By identifying and evaluating accepted cases or read-across adaptations, we high­light best practices for establishing scientifically robust justifications for chemical similarity that can meet ECHA’s high regulatory standards.

Indexed as

Animal Testing AlternativesHazardous SubstancesAnimalsEuropean UnionHumansHazardous SubstancesadaptationsECHAOECD test guideline studiesREACHread-across

Identifiers

PMID40745925
PMCPMC12831182

What OpenQuestion holds

Textmetadata
LicenceTDM
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.