Development of the dynamic consent interface, aimed at enabling data subjects to allow, refuse and withdraw access to their data according to different types of potential usage.

Build-up of a blockchain-based software infrastructure in which individual data exchanges are governed by peer-to-peer relationships between all the stakeholders.

Implementation of the personal data account, a personal cloud allowing data subjects for direct access to their whole clinical data from any personal device through the blockchain.

Use of smart contracts to assist data subjects in their right to access, erase, modify delete or even “be forgotten”.

Analysis of the current legislation applicable to the processing of health data and other personal information, definition of a proper legal and regulatory framework and creation of new rules and best practices for uncovered processes, solutions and methodologies.


Application of the blockchain model, a resilient and decentralised secure control system to monitor and assess the legitimacy of data transactions and detect fraudulent activities in real time.

Identification and system implementation of the most suitable and robust de-identification and encryption technologies needed to secure different types of information.

Evaluation of the overall security of the system architecture by testing it through dedicated re-identification and penetration self-hacking simulations and public hacking challenges.


Profiling and classification of sensitive data based on their informational, scientific and economic value.

Implementation of normalisation services able to process, harmonize and semantically consolidate all authorized data allowing rapid merging of heterogeneous sources.

Creation of a unique application programming interface (API) to facilitate lawful data access to all registered stakeholders with a user-friendly registration process, supporting development of a proper Big Data analytical framework.

Exploring potential ways to make use of anonymised or pseudonymised data with advanced data analytics and patient-specific model-based prediction applications, accelerating discoveries, fostering technological innovation and improving clinical care.