The main objective of the project is to utilize modern high-resolution molecular data (genetics, metabolomics, etc.) with the aim of integrating them (unifying) into patient registries, so that in combination with clinical and epidemiological data they can form an integrated environment of an innovative Smart-Electronic Health Record (E-EHR) with integrated clinical decision support/prediction subsystems to support the physician and the personalized therapeutic approach. Utilizing modern technologies for the management of large volumes of data and by constructing new algorithmic methods, the project focuses on improving the prognosis and clinical management of diseases, through understanding the genetic background of the disease in each patient individually, in order to determine the risk of developing both rare and common diseases such as cardiovascular diseases, metabolic diseases, various cancers, etc. The resulting robust predictive models are then expected to lead to optimized clinical decisions through personalized diagnosis utilizing e-prescribing data, thereby supporting policy and regulatory processes in a comprehensive manner.
Specifically, the project objectives are:
The development of models to define the clinical management of rare and common diseases through the combined analysis of genetic, genomic, clinical and epidemiological data
The application of the models to data of Greek patients. The models that will be developed will be potentially applicable to a wide range of diseases. The project will focus on the following diseases: rare diseases, hereditary cancer, and common multifactorial diseases with a focus on cardiovascular diseases, breast/ovarian cancer and colorectal cancer, for which members of the research team have extensive data.
Validation of models with external and internal data as well as experimental validation/functional analysis of selected findings.
The integration of available data as well as generated secondary data into a single ecosystem of disease registries.
The development of an integrated environment of an innovative Smart-Electronic Health Record (E-EHR) with integrated clinical decision support/prediction subsystems to support the physician and the personalized therapeutic approach as well as integrated secondary data analysis functions for research purposes and health technology assessments.
The creation of an interdisciplinary Precision Medicine Data Analysis Hub nationwide, in which Clinicians and Bioscientists will collaborate with IT Scientists, for the benefit of patients.
The interconnection with other Precision Medicine actions in Greece that could directly benefit from the produced work as well as the dissemination of new analysis capabilities to the research and medical community and to patient associations.