{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/toxicblend-virtual-screening-of-toxic","title":"ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors","arxiv_id":"1806.04449","date":"2018-06-12","proceeding":null,"authors":["Mikhail Zaslavskiy","Simon Jégou","Eric W. Tramel","Gilles Wainrib"],"abstract":"Timely assessment of compound toxicity is one of the biggest challenges\nfacing the pharmaceutical industry today. A significant proportion of compounds\nidentified as potential leads are ultimately discarded due to the toxicity they\ninduce. In this paper, we propose a novel machine learning approach for the\nprediction of molecular activity on ToxCast targets. We combine extreme\ngradient boosting with fully-connected and graph-convolutional neural network\narchitectures trained on QSAR physical molecular property descriptors, PubChem\nmolecular fingerprints, and SMILES sequences. Our ensemble predictor leverages\nthe strengths of each individual technique, significantly outperforming\nexisting state-of-the art models on the ToxCast and Tox21 toxicity-prediction\ndatasets. We provide free access to molecule toxicity prediction using our\nmodel at http://www.owkin.com/toxicblend.","url_abs":"http://arxiv.org/abs/1806.04449v1","url_pdf":"http://arxiv.org/pdf/1806.04449v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"drug-discovery","task_name":"Drug Discovery"},{"task_slug":"prediction","task_name":"Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/drug-discovery-on-tox21","task":"Drug Discovery","dataset":"Tox21","model":"Ensemble predictor","rank_in_archive_order":4,"of":11,"metrics":{"AUC":"0.862"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}