Literature DB >> 35188638

In Silico Models for Skin Sensitization and Irritation.

Gianluca Selvestrel1, Federica Robino2, Matteo Zanotti Russo2.   

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.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Cosmetics; In silico methods; Risk assessment; Skin irritation; Skin sensitization; Topical products

Mesh:

Substances:

Year:  2022        PMID: 35188638     DOI: 10.1007/978-1-0716-1960-5_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  15 in total

Review 1.  Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

Authors:  Alexander Tropsha; Alexander Golbraikh
Journal:  Curr Pharm Des       Date:  2007       Impact factor: 3.116

2.  Identification of mechanisms of toxic action for skin sensitisation using a SMARTS pattern based approach.

Authors:  S J Enoch; J C Madden; M T D Cronin
Journal:  SAR QSAR Environ Res       Date:  2008       Impact factor: 3.000

Review 3.  Dermal sensitization quantitative risk assessment (QRA) for fragrance ingredients.

Authors:  Anne Marie Api; David A Basketter; Peter A Cadby; Marie-France Cano; Graham Ellis; G Frank Gerberick; Peter Griem; Pauline M McNamee; Cindy A Ryan; Robert Safford
Journal:  Regul Toxicol Pharmacol       Date:  2007-10-24       Impact factor: 3.271

4.  Optimizing predictive performance of CASE Ultra expert system models using the applicability domains of individual toxicity alerts.

Authors:  Suman K Chakravarti; Roustem D Saiakhov; Gilles Klopman
Journal:  J Chem Inf Model       Date:  2012-09-18       Impact factor: 4.956

Review 5.  Generic development of topical dermatologic products: formulation development, process development, and testing of topical dermatologic products.

Authors:  Rong-Kun Chang; Andre Raw; Robert Lionberger; Lawrence Yu
Journal:  AAPS J       Date:  2012-10-09       Impact factor: 4.009

6.  Effectiveness of CASE Ultra Expert System in Evaluating Adverse Effects of Drugs.

Authors:  Roustem Saiakhov; Suman Chakravarti; Gilles Klopman
Journal:  Mol Inform       Date:  2013-01-14       Impact factor: 3.353

7.  Development, validation and integration of in silico models to identify androgen active chemicals.

Authors:  Serena Manganelli; Alessandra Roncaglioni; Kamel Mansouri; Richard S Judson; Emilio Benfenati; Alberto Manganaro; Patricia Ruiz
Journal:  Chemosphere       Date:  2018-12-19       Impact factor: 7.086

8.  Skin sensitization in silico protocol.

Authors:  Candice Johnson; Ernst Ahlberg; Lennart T Anger; Lisa Beilke; Romualdo Benigni; Joel Bercu; Sol Bobst; David Bower; Alessandro Brigo; Sarah Campbell; Mark T D Cronin; Ian Crooks; Kevin P Cross; Tatyana Doktorova; Thomas Exner; David Faulkner; Ian M Fearon; Markus Fehr; Shayne C Gad; Véronique Gervais; Amanda Giddings; Susanne Glowienke; Barry Hardy; Catrin Hasselgren; Jedd Hillegass; Robert Jolly; Eckart Krupp; Liat Lomnitski; Jason Magby; Jordi Mestres; Lawrence Milchak; Scott Miller; Wolfgang Muster; Louise Neilson; Rahul Parakhia; Alexis Parenty; Patricia Parris; Alexandre Paulino; Ana Theresa Paulino; David W Roberts; Harald Schlecker; Reinhard Stidl; Diana Suarez-Rodrigez; David T Szabo; Raymond R Tice; Daniel Urbisch; Anna Vuorinen; Brian Wall; Thibaud Weiler; Angela T White; Jessica Whritenour; Joerg Wichard; David Woolley; Craig Zwickl; Glenn J Myatt
Journal:  Regul Toxicol Pharmacol       Date:  2020-07-01       Impact factor: 3.271

9.  Global QSAR models of skin sensitisers for regulatory purposes.

Authors:  Qasim Chaudhry; Nadège Piclin; Jane Cotterill; Marco Pintore; Nick R Price; Jacques R Chrétien; Alessandra Roncaglioni
Journal:  Chem Cent J       Date:  2010-07-29       Impact factor: 4.215

10.  Pred-Skin: A Web Portal for Accurate Prediction of Human Skin Sensitizers.

Authors:  Joyce V B Borba; Rodolpho C Braga; Vinicius M Alves; Eugene N Muratov; Nicole Kleinstreuer; Alexander Tropsha; Carolina Horta Andrade
Journal:  Chem Res Toxicol       Date:  2020-08-05       Impact factor: 3.739

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