PersonalizeAF will focus on the development of medical technologies for atrial characterization in order to improve the sensitivity and specificity of atrial biomarkers. This will be achieved by developing new diagnostic tools to support the design of the best patient-specific treatment. This will help to gain insight into the sub-classification of AF patients, as well as the relationship of these disease sub-phenotypes with the treatment outcome. With these expectations, new knowledge, new skills and new approaches are required to first address the complex medical and technological issue of AF patients management, and therefore to train new professionals in the academic, medical and industrial sectors with these skills.
The need for a new generation of researchers is growing and consequently also for institutions that will be able to set the future AF research and educational agenda. PersonalizeAF takes up this challenge and targets to deliver an innovative multinational, multi-sectorial, and multidisciplinary research and training programme in cardiac genetics, cardiac ion channels, stem cells, signal and image processing, computer modelling and patient management with the focus to investigate AF mechanisms with a translational-oriented approach, develop more effective therapies aiming at terminating the disease mechanisms, and finally personalize AF treatments.
To open the field of AF personalization management, PersonalizeAF will implement a variety of technologies addressing these problems:
1) Characterization technologies to describe the patient-specific mechanisms that intervene in cardiac arrhythmia and assess the conditions behind its development. We aim to develop a novel genetic and transcriptomic profiling workbench, able to identify the specific determinant beyond AF apparition and progression. PersonalizeAF also intends to construct novel technologies for tissue description, in terms of fibrosis extent, based on both intracardiac measurements by impedance catheters and non-invasive measures through MRI analysis. We will also characterize the atrial mechanic degradation involved in the AF progression by novel echocardiographic markers, as well as by mathematical simulations. PersonalizeAF will also characterize the individual electric manifestation of the cardiac arrhythmia in each patient both by intracardiac analysis through electric catheters and by non-invasive electrical mapping through electrocardiographic imaging. The information obtained from these technologies will be integrated, making use of artificial intelligence techniques, to generate a specific profile of the patient.
2) Technologies for the assessment of the effect of each therapy option for each disease sub-phenotype. Nowadays, the lack of sub-phenotype disease division prevents a patient-specific classification of the therapy and its success based on characterization of the disease. To achieve it, PersonalizeAF will develop novel technologies for AF therapy characterization and monitoring and the associated technology to identify atrial-specific characteristics that will allow a patient-efficient treatment selection and application. On top of this technological development, PersonalizeAF will test these potential individualized therapies in patient-specific simulations based on the patient disease phenotype, in order to confirm the therapy assignment.
3) Decision support systems for individualized best therapy selection. Once the individualized AF markers for each patient have been obtained, as well as the therapies classified according to their degree of success in each disease sub-phenotype, a high-level analysis is necessary in order to first identify the sub-group of AF which each patient belongs to, as well as to assign the best therapy.
