Abstract
The assessment of skin irritation, and in particular of skin sensitization, has undergone an evolution process over the last years, pushing forward to new heights of quality and innovation. Public and commercial in silico tools have been developed for skin sensitization and irritation, introducing the possibility to simplify the evaluation process and the development of topical products within the dogma of the computational methods, representing the new doctrine in the field of risk assessment.
The possibility of using in silico methods is particularly appealing and advantageous due to their high speed and low-cost results.
The most widespread and popular topical products are represented by cosmetics. The European Regulation 1223/2009 on cosmetic products represents a paradigm shift for the safety assessment of cosmetics transitioning from a classical toxicological approach based on animal testing, towards a completely novel strategy, where the use of animals for toxicity testing is completely banned. In this context sustainable alternatives to animal testing need to be developed, especially for skin sensitization and irritation, two critical and fundamental endpoints for the assessment of cosmetics.
The Quantitative Risk Assessment (QRA) methodology and the risk assessment using New Approach Methodologies (NAM) represent new frontiers to further improve the risk assessment process for these endpoints, in particular for skin sensitization.
In this chapter we present an overview of the already existing models for skin sensitization and irritation. Some examples are presented here to illustrate tools and platforms used for the evaluation of chemicals.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chang RK, Raw A, Lionberger R et al (2013) Generic development of topical dermatologic products: formulation development, process development, and testing of topical dermatologic products. AAPS J 15(1):41–52. https://doi.org/10.1208/s12248-012-9411-0
OECD (2015) Test No. 404: acute dermal irritation/corrosion, OECD guidelines for the testing of chemicals, section 4. OECD Publishing, Paris. https://doi.org/10.1787/9789264242678-en
EU Regulation 1272/2008 (CLP) Annex I-3.4.1.2. https://eur-lex.europa.eu/legalcontent/IT/TXT/?uri=CELEX:02008R1272-20201114
OECD (2014) The adverse outcome pathway for skin sensitisation initiated by covalent binding to proteins, OECD series on testing and assessment, no. 168. OECD Publishing, Paris. https://doi.org/10.1787/9789264221444-en
Api AM, Basketter DA, Cadby PA et al (2008) Dermal sensitization quantitative risk assessment (QRA) for fragrance ingredients. Regul Toxicol Pharmacol 52(1):3–23. https://doi.org/10.1016/j.yrtph.2008.05.011
SCCS - Scientific Committee on Consumer Safety (2021) SCCS notes of guidance for the testing of cosmetic ingredients and their safety evaluation 11th revision, 30–31 March 2021, SCCS/1628/21. https://ec.europa.eu/health/sites/health/files/scientific_committees/consumer_safety/docs/sccs_o_250.pdf
Johnson C, Ahlberg E, Anger LT et al (2020) Skin sensitization in silico protocol. Regul Toxicol Pharmacol 116:104688. https://doi.org/10.1016/j.yrtph.2020.104688
Chaudhry Q, Piclin N, Cotterill J et al (2010) Global QSAR models of skin sensitisers for regulatory purpose. Chem Cent J 4:S5. https://doi.org/10.1186/1752-153X-4-S1-S5
R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.r-project.org/
Therneau TM, Atkinson EJ (2015) An introduction to recursive partitioning using the RPART routines. Mayo Foundation, Rochester. https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf
Kode srl (2017) Dragon (software for molecular descriptor calculation) Version 7.0.8. https://chm.kode-solutions.net/
Manganelli S, Roncaglioni A, Mansouri K et al (2019) Development, validation and integration of in silico models to identify androgen active chemicals. Chemosphere 220:204–215. https://doi.org/10.1016/j.chemosphere.2018.12.131
Enoch SJ, Madden JC, Cronin MTD (2008) Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach. SAR QSAR Environ Res 19(5–6):555–578. https://doi.org/10.1080/10629360802348985
Borba JVB, Braga RC, Alves VM et al (2021) Pred-skin: a web portal for accurate prediction of human skin sensitizers. Chem Res Toxicol 34(2):258–267. https://doi.org/10.1021/acs.chemrestox.0c00186
Tropsha A, Golbraikh A (2007) Predictive QSAR modeling workflow, model applicability domains, and virtual screening. Curr Pharm Des 13(34):3494–3504. https://doi.org/10.2174/138161207782794257
SciQSAR (2009) Reference guide: statistical analysis and molecular descriptors. Included within the SciMatics SciQSAR software. https://qsardb.food.dtu.dk/db/index.html
Klopman G (1992) MULTICASE 1. A hierarchical computer automated structure evaluation program. Quant Struct Act Relat 11:176–184. https://doi.org/10.1002/qsar.19920110208
Chakravarti SK, Saiakhov RD, Klopman G (2012) Optimizing predictive performance of CASE ultra expert system models using the applicability domains of individual toxicity alerts. J Chem Inf Model 52:2609–2618. https://doi.org/10.1021/ci300111r
Saiakhov RD, Chakravarti SK, Klopman G (2013) Effectiveness of CASE ultra expert system in evaluating adverse effects of drugs. Mol Inform 32:87–97. https://doi.org/10.1002/minf.201200081
Roberts G, Myatt GJ, Johnson WP et al (2000) LeadScope: software for exploring large sets of screening data. Chem Inf Comput Sci 40:1302–1314. https://doi.org/10.1021/ci0000631
Roberts DW (2015) Estimating skin sensitization potency from a single dose LLNA. Regul Toxicol Pharmacol 71(3):437–443. https://doi.org/10.1016/j.yrtph.2015.01.009
Golden E, Macmillan DS, Dameron G et al (2020) Evaluation of the global performance of eight in silico skin sensitization models using human data. ALTEX 38(1):033–048. https://doi.org/10.14573/altex.1911261
Patlewicz G, Dimitrov SD, Low LK et al (2007) TIMES-SS--a promising tool for the assessment of skin sensitization hazard. A characterization with respect to the OECD validation principles for (Q)SARs and an external evaluation for predictivity. Regul Toxicol Pharmacol 48(2):225–239. https://doi.org/10.1016/j.yrtph.2007.03.003
Gerner I, Schlegel K, Walker JD et al (2004) Use of physicochemical property limits to develop rules for identifying chemical substances with no skin irritation or corrosion potential. QSAR Comb Sci 23(9):726–733. https://doi.org/10.1002/qsar.200430880
Hulzebos E, Walker JD, Gerner I et al (2004) Use of structural alerts to develop rules for identifying chemical substances with skin irritation or skin corrosion potential. QSAR Comb Sci 24(3):332–342. https://doi.org/10.1002/qsar.200430905
Selvestrel G, Robino F, Baderna D et al (2021) SpheraCosmolife: a new tool for the risk assessment of cosmetic products. ALTEX. https://doi.org/10.14573/altex.2010221
SCCS - Scientific Committee on Consumer Safety (2018) SCCS notes of guidance for the testing of cosmetic ingredients and their safety evaluation 10th revision, 24-25 October 2018, SCCS/1602/18. https://ec.europa.eu/health/sites/health/files/scientific_committees/consumer_safety/docs/sccs_o_224.pdf
Dusefante A, Mauro M, Belloni Fortina A et al (2019) (2019). Contact allergy to methylchloroisothiazolinone/methylisothiazolinone in North-Eastern Italy: a temporal trend from 1996 to 2016. J Eur Acad Dermatol Venereol 33(5):912–917. https://doi.org/10.1111/jdv.15453
Raymond J, Konya J, Bakis-Petsoglou S (2016) Lichenoid contact dermatitis secondary to methylisothiazolinone (MI). JAAD Case Rep 2(5):380–383. https://doi.org/10.1016/j.jdcr.2016.06.001
EC- European Commission (2009) Regulation (EC) No.1223/2009 of the European Parliament and of the Council of 30 November 2009 on cosmetic products. Official Journal of European Union. L. 342:59-209. http://data.europa.eu/eli/reg/2009/1223/2020-05-01
IdeaConsult (2009) Toxtree user manual. IdeaConsult. https://eurl-ecvam.jrc.ec.europa.eu/laboratories-research/predictive_toxicology/doc/Toxtree_user_manual.pdf. Accessed March 2021
De Groot A, Herxheimer A (1989) Isothiazolinone preservative: cause of a continuing epidemic of cosmetic dermatitis. Lancet 333(8633):P314–P316. https://doi.org/10.1016/S0140-6736(89)91318-4
Magdaleno-Tapial J, Valenzuela-Oñate C, Ortiz-Salvador JM et al (2019) Contact allergy to isothiazolinones epidemic: current situation. Contact Dermatitis 82(2):83–86. https://doi.org/10.1111/cod.13396
Acknowledgements
The research for this paper was financially supported by the LIFE VERMEER project (LIFE16 ENV/IT/OOO167).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Selvestrel, G., Robino, F., Russo, M.Z. (2022). In Silico Models for Skin Sensitization and Irritation. In: Benfenati, E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 2425. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1960-5_13
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1960-5_13
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-1959-9
Online ISBN: 978-1-0716-1960-5
eBook Packages: Springer Protocols