Combination therapies are often needed to improve treatment outcomes of cancer patients. However, we lack systematic approaches to identify maximally effective and safe combinatorial treatments for individual patients. This project will test a predictive platform that identifies patient-tailored treatment options in terms of its technical feasibility and clinical relevance (improved efficacy and reduced adverse effects). A pilot study will evaluate the platform's predictions against clinical outcomes of leukemia patients treated with combination therapies. A close collaboration with clinicians, computational and cancer researchers make it possible to implement a widely applicable therapy prediction platform and to provide ground-breaking impacts to patients and society. The project is expected to lead to increased treatment efficacy, and reduced use of ineffective therapies and adverse effects, which currently lead to enormous individual suffering and economic burden for the society.

2026

2027