2026-10-14T11:04:14Z https://api.figshare.com/v2/oai

oai:figshare.com:article/5933323 2026-09-16T13:49:05Z category_13 category_16 category_21 category_272 category_46 category_734 category_931 category_106 portal_87 item_type_3 month_year_09_2026

Non-animal methods to predict skin sensitization (II): an assessment of defined approaches Nicole C. Kleinstreuer (218465) Sebastian Hoffmann (2524810) Nathalie Alépée (4898248) David Allen (310381) Takao Ashikaga (4898260) Warren Casey (4898245) Elodie Clouet (4898254) Magalie Cluzel (4898242) Bertrand Desprez (4898266) Nichola Gellatly (4898239) Carsten Göbel (4898233) Petra S. Kern (2476147) Martina Klaric (4898251) Jochen Kühnl (4898263) Silvia Martinozzi-Teissier (4898230) Karsten Mewes (4898236) Masaaki Miyazawa (181482) Judy Strickland (4017959) Erwin van Vliet (586202) Qingda Zang (1866157) Dirk Petersohn (4898257) Genetics Physiology Biotechnology Environmental Sciences not elsewhere classified Immunology Biological Sciences not elsewhere classified Information Systems not elsewhere classified Science Policy Skin sensitization defined approaches hazard assessment potency assessment integrated testing strategy human reference data LLNA reference data new approach methodologies adverse outcome pathway Skin sensitization is a toxicity endpoint of widespread concern, for which the mechanistic understanding and concurrent necessity for non-animal testing approaches have evolved to a critical juncture, with many available options for predicting sensitization without using animals. Cosmetics Europe and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods collaborated to analyze the performance of multiple non-animal data integration approaches for the skin sensitization safety assessment of cosmetics ingredients. The Cosmetics Europe Skin Tolerance Task Force (STTF) collected and generated data on 128 substances in multiple in vitro and in chemico skin sensitization assays selected based on a systematic assessment by the STTF. These assays, together with certain in silico predictions, are key components of various non-animal testing strategies that have been submitted to the Organization for Economic Cooperation and Development as case studies for skin sensitization. Curated murine local lymph node assay (LLNA) and human skin sensitization data were used to evaluate the performance of six defined approaches, comprising eight non-animal testing strategies, for both hazard and potency characterization. Defined approaches examined included consensus methods, artificial neural networks, support vector machine models, Bayesian networks, and decision trees, most of which were reproduced using open source software tools. Multiple non-animal testing strategies incorporating in vitro, in chemico, and in silico inputs demonstrated equivalent or superior performance to the LLNA when compared to both animal and human data for skin sensitization. 2018-03-08T10:59:15Z Dataset Dataset 10.6084/m9.figshare.5933323.v3 https://figshare.com/articles/dataset/Non-animal_methods_to_predict_skin_sensitization_II_an_assessment_of_defined_approaches_sup_sup_/5933323 CC BY 4.0