Decision support systems for real-time patient monitoring and treatment optimization

Even if targeted therapies have revolutionized the treatment of many cancers, most patients develop resistance, have severe side-effects or relapse during treatment. Therefore, there is a clinical need to tailor optimal therapy for each patient to prevent ineffective treatment and toxic effects.  This project will identify multi-marker panels and implement AI-based clinical decision support systems to guide treatment decisions for individual patients. We expect this will lead to increased treatment efficacy, individualization of therapy and reduced drug use and side effects. In addition, the multi-omics guided predictions will improve future trial designs and biomarker-based therapy selection.

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