Methodology Objectives

  • Develop algorithms and tools for 360º patient monitoring using multi-source RWD
  • Develop the statistical models and methodology for use of RWD in clinical studies on cancer-related CCC
  • Develop and apply methods for causal modelling to perform inference, prediction and counterfactual reasoning on real-world observational data using deep latent confounder models
  • Develop a methodology for integrating detailed monitoring into existing clinical workflows, to improve management of patients with cancer-related chronic conditions

Technology Objectives

  • Define a common, interoperable data representation and implement a federated learning mechanism for cross-country data exchange on breast cancer and its comorbidities
  • Integrate the REBECCA advanced data management and analysis platform

Validation Objectives

  • Demonstrate the value of REBECCA RWD for advancing understanding of CCC in 3 studies on breast cancer comorbidities
  • Demonstrate the use of REBECCA advanced monitoring mechanism as a means of supporting clinical decisions, improving clinical outcomes and quality of life

Impact Objectives

  • Disseminate project methodologies, technology and study outcomes to research scientists, clinicians, public health bodies and stakeholders from the pharmaceutical and health insurance sectors around Europe
  • Develop and implement a plan for the sustainability and uptake of the project’s technical and methodology outcomes by clinicians and public health policy makers