Personalized Medicine, Personalized Health Research Project funded by the Strategic Focus Area Personalized Health and Related Technologies (PHRT) of the ETH Board.

Video

This is an overview video of DPPH where Prof. Jean-Pierre Hubaux explains the highlights of the project.

Privacy and Security in P4 Medicine

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.

Project Mission

DPPH seeks to address the main scalability, privacy, security and ethical 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. The target result of the project will be a platform composed of software packages that seamlessly enable clinical and genomic data sharing and exploitation across a federation of medical institutions, hospitals and research laboratories across Switzerland in a scalable, secure, responsible and privacy-conscious way, and that can seamlessly integrate widespread cohort exploration tools (e.g., i2b2, TranSMART or SHRINE).
Read the Abstract

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