{"id":29145,"date":"2024-03-01T20:27:36","date_gmt":"2024-03-01T19:27:36","guid":{"rendered":"https:\/\/sovanta.com\/ressourcenplanung-mit-machine-learning\/"},"modified":"2026-07-22T15:33:08","modified_gmt":"2026-07-22T14:33:08","slug":"resource-planning-for-clinical-trials","status":"publish","type":"post","link":"https:\/\/sovanta.com\/en\/resource-planning-for-clinical-trials\/","title":{"rendered":"Resource Planning for Clinical Trials"},"content":{"rendered":"\n

Increasing the predictive accuracy of clinical trials with an optimized ML model<\/strong>.<\/p>\n\n\n\n

Managers often face challenges when planning and managing resources, especially in time-intensive and complex projects. A platform that collects historical data from the data warehouse as well as from various SAP systems and enables users to clearly visualize current resource requirements and allocations through robust predictions helps here.\u00a0<\/p>\n\n\n\n

Cross-project and optimal visualization of the required resources<\/h2>\n\n\n\n

Three success factors of the<\/strong> Resource Planning for Clinical Trials<\/strong>:<\/p>\n\n\n\n

    \n
  1. Anticipation of resource requirements with the help of predictions supported by machine learning and simulations\u200b<\/li>\n\n\n\n
  2. Reduction of overheads in project planning while improving overall results\u200b<\/li>\n\n\n\n
  3. \u200bModern solution with user-friendly UI<\/li>\n<\/ol>\n\n\n\n
    \n\t\n\n
    \n\t\t\t\n\n
    \n \n\n<\/path>\n<\/path>\n<\/svg>\n<\/span><\/div>\n\n\n

    Proof-Point<\/strong>
    Healthcare<\/p>\n\n\t<\/div>\n\n\n\n

    \n\t\t\t\n\n
    \n \n\n<\/path>\n<\/path>\n<\/path>\n<\/path>\n<\/svg>\n<\/span><\/div>\n\n\n

    User<\/strong>
    Ressource Manager, \u200b
    Manager,\u200b
    Planner<\/p>\n\n\t<\/div>\n\n\n\n

    \n\t\t\t\n\n
    \n \n\n<\/path>\n<\/path>\n<\/path>\n<\/path>\n<\/path>\n<\/svg>\n<\/span><\/div>\n\n\n

    Technology<\/strong>
    SAP BTP, 3rd Party Tools<\/p>\n\n\t<\/div>\n\n<\/div>\n<\/div><\/div>\n\n\n\n

    Noch Fragen offen zur Resource Planning for Clinical Trials<\/strong>?<\/h2>\n\n\n\n

    We would be happy to talk to you about use use cases<\/a><\/a>, that are not only exciting, but can also be successfully implemented.<\/p>\n\n\n\n

    \n\n
    \n\n
    \n\n
    \n\n \n\n
    \n \"Akin <\/div>\n
    \n Akin Aritmac <\/div>\n
    \n Chief Sales Officer, Executive Board Member <\/div>\n \n \n <\/div>\n\n <\/div>\n\n
    \n\n

    Your Contact<\/h2>\n \n \n
    \n With passion and cross-industry knowledge, Akin Aritmac supports his customers on their way to successful digitization. <\/div>\n \n \n Direct Contact <\/a>\n \n \n <\/div>\n\n <\/div>\n\n<\/div>","protected":false},"excerpt":{"rendered":"

    Increasing the predictive accuracy of clinical trials with an optimized ML model.<\/p>\n","protected":false},"author":3,"featured_media":72789,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[673],"tags":[],"competence":[],"Industry":[526],"line_of_business":[572],"resource":[491,645],"systems-and-technologies":[],"class_list":["post-29145","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-ai-2","industry-healthcare","line_of_business-sourcing-and-procurement-en","resource-use-cases-en","resource-sap-ai-bdc-use-cases-en"],"yoast_head":"\nResource Planning for Clinical Trials - sovanta AG<\/title>\n<meta name=\"description\" content=\"Resource Planning for Clinical Trials: Increasing the predictive accuracy of clinical trials with an optimized ML model.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sovanta.com\/en\/resource-planning-for-clinical-trials\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Resource Planning for Clinical Trials - 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