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Successful development, validation, and deployment of an AI-based, biomarker-detection algorithm could reduce screening cost and accelerate patient recruitment. Here, we develop a deep-learning algorithm using\u2009&gt;3000 H&amp;E-stained whole slide images from patients with advanced urothelial cancers, optimized for high sensitivity to avoid ruling out trial-eligible patients. The algorithm is validated on a dataset of 350 patients, achieving an area under the curve of 0.75, specificity of 31.8% at 88.7% sensitivity, and projected 28.7% reduction in molecular testing. We successfully deploy the system in a non-interventional study comprising 89 global study clinical sites and demonstrate its potential to prioritize\/deprioritize molecular testing resources and provide substantial cost savings in the drug development and clinical settings.<\/jats:p>","DOI":"10.1038\/s41467-024-49153-9","type":"journal-article","created":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T13:01:54Z","timestamp":1717246914000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial"],"prefix":"10.1038","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8443-2841","authenticated-orcid":false,"given":"Albert","family":"Juan Ramon","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaitanya","family":"Parmar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oscar M.","family":"Carrasco-Zevallos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos","family":"Csiszer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen S. 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They are, or were formerly, salaried and owners of stock in Johnson & Johnson companies. PR owns Paige stock and is a member of the College of American Pathologists\u2019 Digital and Computational Pathology Committee.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"4690"}}