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Applicability of In Silico New Approach Methods for the Risk Assessment of Tattoo Ink Ingredients
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  • Prachi Pradeep,
  • Stefanie Seifert,
  • Ralph Pirow,
  • Ajay Singh,
  • Peter Laux
Prachi Pradeep
German Federal Institute for Risk Assessment (BfR)

Corresponding Author:[email protected]

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Stefanie Seifert
German Federal Institute for Risk Assessment (BfR)
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Ralph Pirow
German Federal Institute for Risk Assessment (BfR)
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Ajay Singh
German Federal Institute for Risk Assessment (BfR)
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Peter Laux
German Federal Institute for Risk Assessment (BfR)
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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 the OECD Guidelines and CLP Regulation. However, in the absence of experimental data, new approach methodologies (NAMs) can be used for data-gap filling. This work evaluates the applicability of in silico NAMs for data-gap filling to a list of tattoo ink ingredients identified by the JRC and BfR for genotoxicity assessment. The experimental in vitro genotoxicity data was acquired from the International Uniform ChemicaL Information Database (IUCLID) which makes the non-confidential REACH Study Results publicly accessible. The specific aims of this analysis were evaluation of in silico genotoxicity predictions from publicly available QSAR tools and structural alerts, development and validation of new QSAR models specific to tattoo ink ingredients, and 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, 11 medium priority and 2 low priority substances were identified for further assessment.
28 Oct 2024Submitted to Environmental and Molecular Mutagenesis
28 Oct 2024Submission Checks Completed
28 Oct 2024Assigned to Editor
28 Oct 2024Review(s) Completed, Editorial Evaluation Pending
01 Nov 2024Reviewer(s) Assigned