Evidence map›Paper›PMID 40388032›Full record

ArticleEnvironmental and molecular mutagenesis2025

Applicability of In Silico New Approach Methods for the Risk Assessment of Tattoo Ink Ingredients.

Prachi Pradeep, Stefanie Seifert, Ajay Vikram Singh, Peter Laux, Ralph Pirow

Abstract read
In one paragraph

Article in Environmental and molecular mutagenesis, 2025. 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. New Approach Methods in Genetic Toxicology.Environmental and molecular mutagenesis · 2026
    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

5 authors.

Prachi PradeepGerman Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin, Germany.ORCID 0000-0002-9219-4249
Stefanie SeifertGerman Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin, Germany.
Ajay Vikram SinghGerman Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin, Germany.
Peter LauxGerman Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin, Germany.
Ralph PirowGerman Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tattoo inks contain several substances, including organic and inorganic pigments, additives, and solvents, which may pose a health risk to not only the tattooed skin but also to other parts of the human body due to intradermal exposure. Substances in tattoo inks are regulated by entry 75 in Annex XVII of REACH Regulation (EC) No. 1907/2006. However, despite these legal requirements, a well-defined criterion for the safety assessment of tattoo inks remains lacking. In this context, 2021 BfR opinion titled "Tattoo inks: minimum requirements and test methods" proposed a comprehensive risk assessment of pigments using in vitro/in-chemico data in accordance with OECD Guidelines and CLP Regulations. In the absence of experimental data, new approach methodologies (NAMs) may be used for data-gap filling. Therefore, this work evaluates the applicability of in silico NAMs for data-gap filling for a list of tattoo ink ingredients identified by the Joint Research Centre (JRC) and BfR for genotoxicity assessment. Experimental in vitro genotoxicity data were acquired from the International Uniform Chemical Information Database (IUCLID) which makes non-confidential REACH Study Results publicly accessible. The specific aims of this analysis were the evaluation of in silico genotoxicity predictions from publicly available QSAR tools and structural alerts, the development and validation of new QSAR models specific to tattoo ink ingredients, and the application of in silico models for categorization and prioritization of data-poor ingredients for further screening. Based on the workflow developed in this study, 4 high priority, 18 medium priority, and 2 low priority substances were identified for further assessment.

Indexed as

Coloring AgentsComputer SimulationInkTattooingHumansMutagenicity TestsRisk AssessmentColoring AgentsNAMspigmentsQSARstattoo ink safety

Identifiers

PMID40388032
PMCPMC12087733

What OpenQuestion 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 OpenQuestion graph.