Predictive Biomarkers from Real-World Data to Enable AI-Driven Personalized Care in Bladder and Prostate Cancer

Bladder and prostate cancers are among the most common chronic non-communicable diseases in Europe, characterized by long disease trajectories, repeated treatment decisions, and substantial heterogeneity in both clinical outcomes and quality-of-life impact. Despite advances in surgery, radiotherapy, and systemic therapies, current risk stratification tools and biomarkers remain insufficient to support truly personalized care. As a result, patients are frequently overtreated or undertreated, with significant consequences for survival, functional outcomes, and health-related quality of life.

Current tools inadequately support shared decision-making and fail to provide patients with clear, personalized predictions of outcomes and prognosis.

Large-scale real-world data (RWD) collected through routine clinical care offer an unprecedented opportunity to address these gaps. When combined with advanced AI methodologies, RWD can enable the development of predictive biomarkers that reflect real patient populations, real treatment pathways, and outcomes that matter to patients, including survival, functional outcomes, as well as overall well-being.

We aim to develop and validate AI-driven predictive biomarkers for disease progression, treatment response, and quality-of-life outcomes in bladder and prostate cancer using large-scale real-world data. By integrating longitudinal clinical data, patient-reported outcomes, imaging, digital pathology, and molecular biomarkers, the project will deliver explainable, clinically actionable tools to support shared decision-making and personalized treatment strategies. The resulting digital decision-support solutions will empower patients and clinicians to balance oncologic outcomes with quality of life