The KATY project pursues the following objectives:

  • Linking genomics repositories securely across the EU in a Distributed Knowledge Graph
  • Demonstrating the potential and benefits of eXplainable AI technologies by applying them to Europe’s relevant genomic repositories in personalised medicine
  • Providing a predictive system to clinicians for AI-based treatment recommendations to support them in their process of selecting the treatment best suited to each patient
  • Setting up a proof-of-concept application of AI-models and knowledge graphs in the context of a clinical pilot in renal cancer
  • Reducing the burden of disease for renal cancer patients by applying existing treatments in a more targeted way
  • Cataloguing the set of biological, molecular and clinical public knowledge needed to organize data relating to patients treated with targeted therapy by applying cutting-edge computational infrastructures
  • Enhancing the diagnostic capacity overall for complex diseases by using AI-based models to predict patient response to targeted therapies and the identification of molecular evidence to support these predictions.