[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-spots-liver-toxicity-in-drug-tests-before-experts-do":10,"sections":34},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":29,"feedback":33,"feedback_at":22,"cost_usd":33,"total_tokens":33},3155,"ai-spots-liver-toxicity-in-drug-tests-before-experts-do","AI Spots Liver Toxicity in Drug Tests Before Experts Do","A new anomaly detection framework for whole-slide tissue images catches drug-induced liver damage with a false negative rate under 0.2 percent.","An AI system trained to read mouse liver slides can flag toxic tissue damage — including pathology types it has never seen before — with a false negative rate of just 0.16 percent.\n\nResearchers built the framework around a fine-tuned Vision Transformer (DINOv2), adapted using Low-Rank Adaptation (LoRA) and trained on a newly assembled dataset of pixel-annotated rodent liver slides. Once trained, the system classifies tissue at the pixel level and uses Mahalanobis distance — a statistical measure of how far a data point sits from a known distribution — to flag samples that fall outside its training categories. That out-of-distribution capability matters: the model was tested on apoptosis and staining artifacts, two tissue states it had never been trained on, and still correctly identified 89.38 percent of those novel findings.\n\nDrug-induced toxicity is one of the most common reasons compounds fail in preclinical and early clinical trials, and the current standard — expert pathologist review of histopathology slides — does not scale to the volume of candidates that modern drug pipelines generate. A system that can screen whole-slide images automatically, and that errs decisively on the side of not missing lesions, could shrink both the time and cost of that bottleneck.\n\nThe results are a proof of concept on mouse liver tissue, not a cleared clinical tool, and rodent slides are a narrower domain than the full range of tissues and species a drug development program touches — but the architecture's ability to generalize to unseen pathology types is the detail worth watching.","[\"ai\",\"drug-discovery\",\"histopathology\",\"anomaly-detection\"]","2026-07-01T04:00:00.000Z","2026-07-01T08:34:33.979Z","2026-07-01T08:34:36.894Z","published",null,[],"ai",[24,26,27,28],"drug-discovery","histopathology","anomaly-detection",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2602.02124",0,{"sections":35},[36,40,45,50,55,60,65,70,75,80,85,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",2590,"2026-07-16T04:00:00.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",294,"2026-07-15T19:59:48.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Deals","deals",179,"2026-06-29T20:02:07.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Policy","policy",158,"2026-07-16T00:02:48.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",122,"2026-07-14T19:46:26.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",93,"2026-07-13T13:20:48.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Software","software",70,"2026-07-13T19:52:25.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Science","science",66,"2026-07-10T10:29:37.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":79},"Dev Tools","dev-tools",59,"2026-07-07T04:00:00.000Z",{"name":81,"slug":82,"count":83,"latest_published_at":84},"Gaming","gaming",41,"2026-07-09T04:00:00.000Z",{"name":86,"slug":87,"count":83,"latest_published_at":88},"Startups","startups","2026-06-29T20:55:50.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",29,"2026-07-10T22:28:58.000Z",{"name":95,"slug":96,"count":97,"latest_published_at":98},"Reviews","reviews",20,"2026-06-24T12:00:01.000Z",{"name":100,"slug":101,"count":102,"latest_published_at":103},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]