{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T04:48:08Z","timestamp":1769834888322,"version":"3.49.0"},"reference-count":28,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Regulatory Toxicology and Pharmacology"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.yrtph.2026.106028","type":"journal-article","created":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T16:45:41Z","timestamp":1767631541000},"page":"106028","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Development and evaluation of a novel consensus in silico model within the OECD GL497 defined approach for skin sensitization prediction"],"prefix":"10.1016","volume":"166","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1148-9016","authenticated-orcid":false,"given":"Mika","family":"Imamura","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryoichi","family":"Murakami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masakazu","family":"Tateshita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasushi","family":"Hikida","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.yrtph.2026.106028_bib1","series-title":"Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","article-title":"Optuna: a next-generation hyperparameter optimization framework","author":"Akiba","year":"2019"},{"issue":"2","key":"10.1016\/j.yrtph.2026.106028_bib2","doi-asserted-by":"crossref","DOI":"10.1093\/toxsci\/kfac078","article-title":"PreS\/MD: predictor of sensitization hazard for chemical substances released from medical devices","volume":"189","author":"Alves","year":"2022","journal-title":"Toxicol. Sci."},{"issue":"9","key":"10.1016\/j.yrtph.2026.106028_bib3","doi-asserted-by":"crossref","DOI":"10.1021\/tx050075m","article-title":"Skin sensitization: reaction mechanistic applicability domains for structure-activity relationships","volume":"18","author":"Aptula","year":"2005","journal-title":"Chem. Res. Toxicol."},{"issue":"2","key":"10.1016\/j.yrtph.2026.106028_bib4","doi-asserted-by":"crossref","DOI":"10.1021\/acs.chemrestox.0c00186","article-title":"Pred-Skin: a web portal for accurate prediction of human skin sensitizers","volume":"34","author":"Borba","year":"2021","journal-title":"Chem. Res. Toxicol."},{"key":"10.1016\/j.yrtph.2026.106028_bib5","volume":"No.40","year":"2023"},{"issue":"6","key":"10.1016\/j.yrtph.2026.106028_bib6","doi-asserted-by":"crossref","DOI":"10.1021\/acs.chemrestox.2c00368","article-title":"Augmenting expert knowledge-based toxicity alerts by statistically mined molecular fragments","volume":"36","author":"Chakravarti","year":"2023","journal-title":"Chem. Res. Toxicol."},{"key":"10.1016\/j.yrtph.2026.106028_bib7","doi-asserted-by":"crossref","DOI":"10.1016\/j.yrtph.2020.104721","article-title":"Development of a next generation risk assessment framework for the evaluation of skin sensitisation of cosmetic ingredients","volume":"116","author":"Gilmour","year":"2020","journal-title":"Regul. Toxicol. Pharmacol."},{"issue":"1","key":"10.1016\/j.yrtph.2026.106028_bib8","article-title":"An assessment of mutagenicity of chemical substances by (Quantitative) structure-activity relationship","volume":"42","author":"Honma","year":"2020","journal-title":"Gene Environ."},{"issue":"7","key":"10.1016\/j.yrtph.2026.106028_bib9","doi-asserted-by":"crossref","DOI":"10.1002\/jat.4283","article-title":"Applicability of amino acid derivative reactivity assay (4 MM) for the prediction of skin sensitization by combining multiple alternative methods to evaluate key events","volume":"42","author":"Imamura","year":"2022","journal-title":"J. Appl. Toxicol."},{"key":"10.1016\/j.yrtph.2026.106028_bib10","series-title":"Advances in Neural Information Processing Systems","article-title":"LightGBM: a highly efficient gradient boosting decision tree","author":"Ke","year":"2017"},{"key":"10.1016\/j.yrtph.2026.106028_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.comtox.2025.100348","article-title":"Consensus model for skin sensitization assessment using a rule-based model and LLNA and GPMT statistics-based models","volume":"34","author":"Murakami","year":"2025","journal-title":"Computational Toxicol."},{"key":"10.1016\/j.yrtph.2026.106028_bib15","doi-asserted-by":"crossref","DOI":"10.1016\/j.yrtph.2018.04.014","article-title":"In Silico toxicology protocols","volume":"96","author":"Myatt","year":"2018","journal-title":"Regul. Toxicol. Pharmacol."},{"key":"10.1016\/j.yrtph.2026.106028_bib16","series-title":"OECD Guidelines for the Testing of Chemicals, Section 4. Test No.429: Skin Sensitization: Local Lymph Node Assay","year":"2010"},{"key":"10.1016\/j.yrtph.2026.106028_bib17","series-title":"OECD Series on Testing and Assessment No.255","year":"2017"},{"key":"10.1016\/j.yrtph.2026.106028_bib18","series-title":"OECD Guidelines for the Testing of Chemicals, Section 4. Guideline No. 497: Defined Approaches on Skin Sensitisation","year":"2021"},{"key":"10.1016\/j.yrtph.2026.106028_bib19","series-title":"OECD Guidelines for the Testing of Chemicals, Section 4. Test No.406: Skin Sensitisation Guinea Pig Maximisation Test and Buehler Test","year":"2022"},{"key":"10.1016\/j.yrtph.2026.106028_bib20","series-title":"OECD Guidelines for the Testing of Chemicals, Section 4. Test No. 442E: in Vitro Skin Sensitisation","year":"2024"},{"key":"10.1016\/j.yrtph.2026.106028_bib21","series-title":"Guideline No. 497: Defined Approaches on Skin Sensitisation","year":"2025"},{"key":"10.1016\/j.yrtph.2026.106028_bib22","series-title":"OECD Guidelines for the Testing of Chemicals, Section 4. Test No. 442C: in Chemico Skin Sensitisation Assay (DPRA)","year":"2025"},{"issue":"9","key":"10.1016\/j.yrtph.2026.106028_bib23","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.1222878110","article-title":"Genomic responses in mouse models poorly mimic human inflammatory diseases","volume":"110","author":"Seok","year":"2013","journal-title":"Proc. Natl. Acad. Sci. U. S. A"},{"key":"10.1016\/j.yrtph.2026.106028_bib24","doi-asserted-by":"crossref","DOI":"10.3389\/fphar.2021.655771","article-title":"In silico prediction of skin sensitization: quo vadis?","volume":"12","author":"Ta","year":"2021","journal-title":"Front. Pharmacol."},{"issue":"1","key":"10.1016\/j.yrtph.2026.106028_bib25","doi-asserted-by":"crossref","DOI":"10.1186\/s13321-021-00557-5","article-title":"FP-ADMET: a compendium of fingerprint-based ADMET prediction models","volume":"13","author":"Venkatraman","year":"2021","journal-title":"J. Cheminf."},{"issue":"1","key":"10.1016\/j.yrtph.2026.106028_bib26","doi-asserted-by":"crossref","DOI":"10.1186\/s13321-017-0194-2","article-title":"SkinSensDB: a curated database for skin sensitization assays","volume":"9","author":"Wang","year":"2017","journal-title":"J. Cheminf."},{"issue":"10","key":"10.1016\/j.yrtph.2026.106028_bib27","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btac192","article-title":"Interpretable-ADMET: a web service for ADMET prediction and optimization based on deep neural representation","volume":"38","author":"Wei","year":"2022","journal-title":"Bioinformatics"},{"issue":"19","key":"10.1016\/j.yrtph.2026.106028_bib28","doi-asserted-by":"crossref","DOI":"10.3390\/ijms20194833","article-title":"Skin doctor: machine learning models for skin sensitization prediction that provide estimates and indicators of prediction reliability","volume":"20","author":"Wilm","year":"2019","journal-title":"Int. J. Mol. Sci."},{"issue":"8","key":"10.1016\/j.yrtph.2026.106028_bib29","doi-asserted-by":"crossref","DOI":"10.3390\/ph14080790","article-title":"Predicting the skin sensitization potential of small molecules with machine learning models trained on biologically meaningful descriptors","volume":"14","author":"Wilm","year":"2021","journal-title":"Pharmaceuticals"},{"issue":"2","key":"10.1016\/j.yrtph.2026.106028_bib30","doi-asserted-by":"crossref","DOI":"10.1021\/acs.chemrestox.0c00253","article-title":"Skin doctor CP: conformal prediction of the skin sensitization potential of small organic molecules","volume":"34","author":"Wilm","year":"2021","journal-title":"Chem. Res. Toxicol."},{"issue":"W1","key":"10.1016\/j.yrtph.2026.106028_bib31","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkab255","article-title":"ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties","volume":"49","author":"Xiong","year":"2021","journal-title":"Nucleic Acids Res."}],"container-title":["Regulatory Toxicology and Pharmacology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0273230026000012?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0273230026000012?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T15:17:38Z","timestamp":1769786258000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0273230026000012"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":28,"alternative-id":["S0273230026000012"],"URL":"https:\/\/doi.org\/10.1016\/j.yrtph.2026.106028","relation":{},"ISSN":["0273-2300"],"issn-type":[{"value":"0273-2300","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Development and evaluation of a novel consensus in silico model within the OECD GL497 defined approach for skin sensitization prediction","name":"articletitle","label":"Article Title"},{"value":"Regulatory Toxicology and Pharmacology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.yrtph.2026.106028","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106028"}}