Cancer is assumed to be one of the most prevalent and fast spreading diseases, and is proven to be the main cause of death in developed countries like Cyprus and Greece during the last years. The cancer occupies an increasing proportion of health services according to many international studies and data. Some forms of cancer are associated with the exposure to environmental factors such as smoking, alcohol, chemicals and certain types of viruses. Cancer strongly influences the psychophysical condition of an individual, and can cause many different symptoms, depending on the location and character of the malignancy and certain types of metastases. The scientific community follows a variety of approaches to study cancer, from which a new promising approach is the use of computational methods and modeling. Thus, the main objective of this project is to create an integrated platform for managing, analyzing and processing medical data in order to better manage patients with cancer. This platform includes tools for visualization of medical data, methods of data analysis and dynamic simulation models of tumor development, able to predict which treatment scenarios would yield the best results for a specific patient. In addition, it will create a repository, hosting computational tools and models, providing web-access to remote medical experts and researcher form Greece and Cyprus. The ultimate scientific goal of this project is to improve our current understanding of complex underlying biological mechanisms of cancer, combining existing knowledge and new computational tools and models that will be developed. Thus, the estimated growing research area of this project will become a standard in conducting research in a very important issue, such as cancer treatment, whose results can be extended and exploited in other relevant international areas of research. The aim of research is the predictive oncology, namely the application of computational models for predicting tumor growth in space and time. If the predictive oncology can effectively take into account the specific parameters of individual patient (treatment plan, age, physical condition, etc.), it will become a powerful tool for doctors, who will be able to predict which treatment plan is appropriate for each different case. This work will enforce and strengthen local research institutions, with the synergy and cooperation between technical and clinical scientific parties. By the end of the project it is expected a new research pole to be developed for the study and treatment of one of the most important and major health problems worldwide.