Healthcare is changing due to social challenges in the area of tension between cost efficiency through standardization and therapy effectiveness through personalization. Therapy-relevant information, for example in interdisciplinary oncological treatment, covers the entire range from omics data, imaging and laboratory values to the inclusion of living conditions. For efficient healthcare, the data must be available in daily clinical practice and decision support systems must seamlessly integrate into established clinical workflows.
The aim of the project is therefore to create a scientific and methodological basis for model-based, personalized cancer treatments that can be used in a large variety of clinical settings. The project addresses scientific questions in the field of knowledge modeling and data semantics as a starting point for the development of applications for personalized tumor therapy. So that we can provide a common understanding of work processes, patient data and decision-making processes as the basis for integration into clinical practice. The complexity of medical data and clinical processes requires the development of tailored applications for the respective clinical scenarios and user groups along the tumor treatment chain. The project demonstrates the applicability and added value of selected assistance systems as well as the integration of these applications based on interoperable models in cooperation with regional SME-partners and the clinical users.