Between 2011 and 2030, the number of new cancer cases in Germany is expected to rise by 23%. This requires an increase in efficiency, integration and personalisation of care for this vulnerable group, from diagnostics to therapy recommendations and application through to home care.

In this sub-project, specific measures from molecular diagnostics, the collection of psychosocial, pathological, histological and radiological data and data integration to therapy recommendations and implementation in the home environment are being investigated. The integration of new biomarkers and exposomics, which are collected in the routine care of cancer patients, are of crucial importance for the molecular tumour board and therapy recommendations. In addition, new developments have made the therapeutic landscape almost impossible for individual practitioners to keep track of. With the help of artificial intelligence (AI), it is possible to use predominantly unstructured hospital data as well as molecular, pathological, histological and radiological data to better structure the tumour board and support tumour board decisions.

The aim is the interdisciplinary, interprofessional, multidimensional characterisation of oncological patients as a basis for AI-supported multilevel data integration to optimise tumour board decisions and inpatient and home care. In addition, closer networking of the oncological centres of the UMO at the Oldenburg Clinic and the PIUS Hospital is to be achieved. The selection of the three model entities non-small cell lung cancer (NSCLC), colorectal cancer (CRC) and malignant melanoma (MM) is based on their high prevalence, the high clinical expertise of the applicants and the high regional coverage of over 80% by the cancer centres of the UMO in the northwest metropolitan region.

The planned study will involve interdisciplinary, interprofessional, multidimensional characterisation of oncological patients as a basis for AI-supported multilevel data integration to optimise tumour board decisions and inpatient and home care. Specific measures in molecular, radiological and immunological diagnostics, data integration and therapy recommendations and their implementation will increase efficiency, achieve intersectoral integration and personalise the care of oncological patients. Three videos are available to illustrate the individual work packages: