[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-ai-model-predicts-drug-combination-risks-before-human-trials":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},7943,"ai-model-predicts-drug-combination-risks-before-human-trials","AI Model Predicts Drug Combination Risks Before Human Trials","A multimodal AI model trained on lab and patient data predicts which drug combinations are risky or effective before clinical testing.","A new AI model predicts how dangerous or effective a drug combination will be in patients, using only lab-scale data collected before anyone runs a clinical trial.\n\nThe model, called Madrigal, learns from four types of preclinical data: molecular structure, biological pathways, cell-viability tests, and gene-expression readouts. It aligns these signals for 21,842 compounds into a shared representation, then trains on 158 expert-curated and 795 patient-reported combination outcomes. In testing, it beat models that rely on a single data type or on other multimodal approaches, and it flagged elevated danger for combinations that share the same membrane transporters. Across 28 head-to-head trial comparisons, it picked the arm with more reported neutropenia, anemia, hair loss, or low blood sugar as the riskier one in 25 cases.\n\nMost drug-interaction models still lean almost entirely on chemical structure and known drug targets, which misses how a compound actually behaves inside a cell. Folding in cell-viability and transcriptomic data lets Madrigal catch combination risks that structure alone would not flag, and do it before a single patient is enrolled. That is the expensive part of drug development that keeps producing late-stage failures.\n\nStill, this is a retrospective analysis run on existing cohorts, not a live clinical decision tool, and getting the risk ranking right in 25 of 28 comparisons leaves real room for the misses that matter most.","[\"ai\",\"drug-discovery\",\"healthcare\",\"biotech\"]","2026-09-25T04:00:00.000Z","2026-09-26T07:58:22.235Z","2026-09-26T07:58:26.724Z","published",null,[],"ai",[24,26,27,28],"drug-discovery","healthcare","biotech",[30],{"name":31,"url":32},"arXiv cs.AI","https:\u002F\u002Farxiv.org\u002Fabs\u002F2503.02781",0,{"sections":35},[36,40,45,50,55,60,64,69,74,79,84,89,94,99],{"name":37,"slug":24,"count":38,"latest_published_at":39},"AI",4624,"2026-09-25T21:57:05.000Z",{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",748,"2026-09-26T01:30:00.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Policy","policy",392,"2026-09-25T18:44:30.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Deals","deals",258,"2026-09-26T09:00:00.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",185,"2026-09-25T15:00:22.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":54},"Science","science",144,{"name":65,"slug":66,"count":67,"latest_published_at":68},"Consumer Tech","consumer-tech",133,"2026-09-26T07:30:06.000Z",{"name":70,"slug":71,"count":72,"latest_published_at":73},"Software","software",90,"2026-09-25T20:55:00.000Z",{"name":75,"slug":76,"count":77,"latest_published_at":78},"Dev Tools","dev-tools",84,"2026-09-26T04:20:58.000Z",{"name":80,"slug":81,"count":82,"latest_published_at":83},"Startups","startups",76,"2026-09-25T18:33:59.000Z",{"name":85,"slug":86,"count":87,"latest_published_at":88},"Gaming","gaming",48,"2026-09-25T18:35:21.000Z",{"name":90,"slug":91,"count":92,"latest_published_at":93},"General","general",46,"2026-09-25T02:12:57.000Z",{"name":95,"slug":96,"count":97,"latest_published_at":98},"Reviews","reviews",30,"2026-09-24T20:07:31.000Z",{"name":100,"slug":101,"count":102,"latest_published_at":103},"How-To","how-to",6,"2026-06-16T09:00:00.000Z"]