P4 (Predictive, Preventive, Personalized and Participatory) medicine is called to revolutionize healthcare by providing better diagnoses and targeted preventive and therapeutic measures. However, to accelerate its adoption and maximize its potential, clinical and research data on large numbers of individuals must be efficiently shared between all stakeholders. The privacy risks stemming from disclosing medical data raise serious concerns, and have become a barrier that can hold back the advances in P4 medicine if effective privacy-preserving technologies are not adopted to enable privacy-conscious medical data sharing. The evolution of the regulation towards further guarantees (e.g., HIPAA in USA and the new GDPR in EU) reflects this urgent need.

Pairing privacy-conscious data sharing with recent advances in the field of *omics and, in particular, in high-throughput sequencing technology, leads to an explosive growth in the amounts of available data; this big data scale can usually not be handled with current hospital computing facilities, hence the need for elastic computing resources that can cope with huge amounts of data in a secure and privacy-aware infrastructure, supporting data processing and sharing.

We will focus on the main scalability, privacy and security challenges of data sharing for enabling effective P4 medicine, by defining an optimal balance between usability, scalability and data protection, and deploying an appropriate set of computing tools to make it happen. We will also address other aspects such as data integrity.

The “Health” application vertical will allow unprecedented synergies between computer scientists and the personalized health community. Researchers involved in all Technology Pillars will work in close collaboration with clinicians, medical researchers and hospital IT specialists to imagine, develop and deploy innovative technical solutions that will make it possible to perform cutting-edge biomedical research in a privacy-conscious way.