Europe still sees a quarter of the world's cancer cases each year, making cancer the second leading cause of death and illness in the region after cardiovascular diseases. Unless we take decisive action, lives lost to cancer in the EU are set to increase by more than 24% by 2035, making it the leading cause of death in the EU. Cross-border collaboration can address this challenge by combining data from various modalities and sources, extracting meaningful insights to deepen our understanding of cancer. However, ethical, legal, and national regulations, along with data access processes, including differing interpretations of the EU GDPR create significant hurdles. Technical interoperability issues across European cancer RIs, and patients' and citizens' rights to control who uses their personal information and for what purposes further complicate data sharing. The project will provide European researchers, SMEs, and innovators with a decentralized collaborative network, “UNCAN-CONNECT,” for cancer research. It consists of both technical components, a governance, compliance, and operational framework based on the UNCAN blueprint, with the goal of operationalizing it. The objective is to facilitate access to cancer data, promote open science, and revolutionize cancer research and treatment by co-creating an open-source federation of federations platform. It will be developed using specific use cases focused on six major cancer types: Paediatric, Lymphoid malignancies, Pancreatic cancer, Ovarian, Lung, and Prostate cancers and active collaboration with a diverse range of stakeholders, including researchers, SMEs, industrial end users, and citizens. It will build on existing European RIs such as BBMRI as well as initiatives like EOSC4CANCER, CanSERV, EUCAIM, to enable seamless storage, access, sharing, and processing of data across Member States and associated countries. This approach will foster interoperability and collaboration, accelerating progress in cancer research. This action is part of the Cancer Mission clusters of projects 'Understanding' established in 2022.

There were 17 million new cases of cancer diagnosed worldwide in 2018. Survival rates of cancer patients were rather poor until recent decades, when diagnostic techniques have been improved and novel therapeutic options have been developed. It is estimated that more than 50% of adult patients diagnosed with cancer live at least 5 years in the US and Europe. This situation leads to a new challenge: to increase the cancer patients’ post-treatment quality of life and well-being. This proposal aims at identifying cancer survivors from three prevalent types of cancer, including breast, lung and lymphomas. The patient data will be collected from different Spanish hospitals and the selection will be based on ongoing health and supportive care needs of the particular patient types. We will determine the personalised factors that predict poor health status after specific oncological treatments. For this aim, Big Data and Artificial Intelligence techniques will be used to integrate all available patient´s information with publicly available relevant biomedical databases as well as information from wearable devices used after the treatment. To predict patient-specific risk of developing secondary effects and toxicities of their cancer treatments, we will build novel models based on statistical relational learning and explainable AI techniques on top of the integrated knowledge graphs. The models will utilise background knowledge of the associated cancer biology and thus will help clinicians to make evidence-based post-treatment decisions in a way that is not possible at all with any existing approach. In summary, CLARIFY proposes to integrate and analyse large volumes of heterogenous multivariate data to facilitate early discovery of risk factors that may deteriorate a patient condition after the end of oncological treatment. This will effectively help to stratify cancer survivors by risk in order to personalize their follow-up by better assessment of their needs.