{"id":2197,"date":"2026-08-28T10:31:30","date_gmt":"2026-08-28T10:31:30","guid":{"rendered":"https:\/\/amm-journal.org\/?p=2197"},"modified":"2026-08-28T10:36:13","modified_gmt":"2026-08-28T10:36:13","slug":"dstox-mutagen-profiler-mutagenicity-prediction","status":"publish","type":"post","link":"https:\/\/amm-journal.org\/index.php\/2026\/08\/28\/dstox-mutagen-profiler-mutagenicity-prediction\/","title":{"rendered":"Development and validation of DSTOX: an integrated QSAR platform adhering to ICH M7 guidelines for mutagenicity assessment of drug impurities"},"content":{"rendered":"<p>Announcing a new publication for <em>Acta Materia Medica<\/em> journal. \u00a0The assessment of a compound\u2019s potential DNA reactivity (mutagenicity) is a critical component of its safety evaluation. The biological activity of a compound is generally understood to be closely associated with its chemical structure. Because computer-aided quantitative structure-activity relationship (QSAR) models can provide high-throughput and rapid evaluation of compounds, the development of robust computational prediction models has substantial practical value. The authors of this article developed the Decrypt Substance Toxicity (DSTOX) Mutagen Profiler software through a multi-strategy fusion approach. By integrating statistical rule-based models, expert knowledge rule-based models, analogue search, carcinogenicity data search, and International Council for Harmonisation (ICH) classification determination, the software generates mutagenicity assessment classification reports adhering to ICH M7 guidelines. Internal validation of the DSTOX statistical model indicated an accuracy of 92.0%. When combined with expert knowledge rule-based models and analogue cross-referencing, the DSTOX model exhibited robust mutagenicity prediction performance. External validation achieved an accuracy of 84.0% and a sensitivity (recall) of 82.8% for mutagenic compounds. The model\u2019s performance metrics were generally comparable to those of current internationally recognized mainstream prediction tools.<\/p>\n<p>Read more:<a href=\"https:\/\/www.scienceopen.com\/hosted-document?doi=10.15212\/AMM-2026-0033\"> https:\/\/www.scienceopen.com\/hosted-document?doi=10.15212\/AMM-2026-0033<\/a><\/p>\n<p><strong># # # # # #<\/strong><\/p>\n<p><em>Acta Materia Medica<\/em> welcomes the submission of research articles, review articles, databases, mini reviews, commentaries, editorials, short communications, case report articles and study protocols.<\/p>\n<p><strong>Submission Process<\/strong><\/p>\n<p>Submissions <em>to Acta Materia Medica<\/em> are made using ScholarOne, the online submission and peer review system. Registration and access are available at <a href=\"https:\/\/mc04.manuscriptcentral.com\/ammed\">https:\/\/mc04.manuscriptcentral.com\/ammed<\/a><\/p>\n<p>Queries about the journal can be sent to editorialoffice@amm-journal.org.<\/p>\n<p>Please visit <a href=\"https:\/\/amm-journal.org\/\">https:\/\/amm-journal.org\/<\/a> to learn more about the journal.<\/p>\n<p><strong>Editorial Board:<\/strong> <a href=\"https:\/\/amm-journal.org\/index.php\/editorial-board\/\">https:\/\/amm-journal.org\/index.php\/editorial-board\/<\/a><\/p>\n<p>There are no author submission or article processing fees.<\/p>\n<p>Follow <strong><em>Acta Materia Medica <\/em><\/strong>on Twitter <a href=\"https:\/\/twitter.com\/AMM_journal\">https:\/\/twitter.com\/AMM_journal<\/a>; <a href=\"https:\/\/www.facebook.com\/Zoonoses-Journal-100462755574114\">Facebook<\/a> (<a href=\"https:\/\/www.facebook.com\/AMMjournal\">https:\/\/www.facebook.com\/AMMjournal<\/a>)<\/p>\n<p><strong>eISSN <\/strong>2737-7946<\/p>\n<p><strong># # # # # #<\/strong><\/p>\n<p>Guo Yu, Tiantian Xu and Siyao Fan et al. Development and validation of DSTOX: an integrated QSAR platform adhering to ICH M7 guidelines for mutagenicity assessment of drug impurities.\u00a0<em>Acta Materia Medica.\u00a0<\/em>2026. Vol. 5(2):211-220. DOI: 10.15212\/AMM-2026-0033<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Announcing a new publication for Acta Materia Medica journal. \u00a0The assessment of a compound\u2019s potential DNA reactivity (mutagenicity) is a critical component of its safety evaluation. The biological activity of a compound is generally understood to be closely associated with its chemical structure. Because computer-aided quantitative structure-activity relationship (QSAR) models can provide high-throughput and rapid [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":2202,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[587,586,588,583,584,585],"class_list":["post-2197","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-events","tag-ames-tests","tag-dstox","tag-hazard-assessment","tag-ich-m7","tag-mutagenicity","tag-qsar"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Development and validation of DSTOX: an integrated QSAR platform adhering to ICH M7 guidelines for mutagenicity assessment of drug impurities<\/title>\n<meta name=\"description\" content=\"This study introduces DSTOX Mutagen Profiler, a fusion model for 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