Evidence map›Paper›PMID 42369402›Full record

ArticleNAM journal2025

Determination of acceptable margins of exposure (MoE) for NAM-based skin sensitisation risk assessment.

Joe Reynolds, Maja Aleksic, Nicola Gilmour, Georgia Reynolds

Abstract read
In one paragraph

Article in NAM journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Joe ReynoldsSafety, Environmental and Regulatory Sciences (SERS), Unilever, UK.
Maja AleksicSafety, Environmental and Regulatory Sciences (SERS), Unilever, UK.
Nicola GilmourSafety, Environmental and Regulatory Sciences (SERS), Unilever, UK.
Georgia ReynoldsSafety, Environmental and Regulatory Sciences (SERS), Unilever, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin sensitisation safety decisions for consumer goods predominantly use approaches such as Quantitative Risk Assessment (QRA) to judge whether a dermal exposure is low risk by comparing a point of departure (PoD) against an expected consumer exposure. Traditionally, the no-expected-sensitisation-induction level (NESIL), derived from human or murine studies, has provided this PoD. Safety Assessment Factors (SAFs) are used to adjust the NESIL to derive an Acceptable Exposure Level (AEL). Exposures are considered low risk when the AEL exceeds the Consumer Exposure Level (AEL:CEL > 1). An equivalent approach evaluates the Margin of Exposure (MoE), defined as the PoD/CEL, and deems exposure low risk when the MoE exceeds a predetermined threshold. As new approach methodologies (NAMs) increasingly supply PoDs, a key question is whether MoE and SAFs, established for human and murine NESILs, are appropriate for NAM-based PoDs, or whether recalibration is required to maintain protectiveness. We propose a statistical framework that converts precedent MoE and SAFs used with traditional NESILs into statistically equivalent thresholds for NAM-derived PoDs. The framework uses benchmark consumer exposure scenarios for skin-sensitising ingredients and proposes a risk-matching approach that enables conversion of traditional acceptable MoEs/SAFs to NAM PoD-appropriate equivalents. Assuming a risk assessor can specify the desired MoE or SAF for a traditional NESIL, the output is a simple conversion table for NAM PoD-appropriate equivalent values. We provide a conversion table for PoDs from SARA-ICE, the GARDskin dose-response assay, and the multiple-regression approach and illustrate application with a simple, illustrative case study.

Indexed as

Next generation risk assessment (NGRA)Risk assessmentSafety decisionSkin allergy

Identifiers

PMID42369402
PMCPMC13289206

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.