Latest news

2020-04-15 We have provisioned a PEP testing environment to the Chronic Pain Network. We will work together with IVIDO to develop an infrastructure for privacy-friendly sharing of patient data for research purposes.

2020-02-14 All data from the Personalized Parkinson Project have been moved to Google Cloud Storage. This milestone marks Version 2 of the PEP Research data Repository. The system can now accomodate more then 1 petabyte of data.

2019-09-09 The Healthy Brain Study has started using the PEP system, which has been adapted to this project. The first participants have been included in the study - and thus in the PEP-system - today.

2019-07-18 The Healthy Brain Study has started testing the PEP system, in preparation for the start of the data collection phase.

2019-07-15 The Personalized Parkinson Project has uploaded the entire backlog of clinical data and study-watch data to the PEP research data repository. From now on data will be uploaded on a regular basis while they are collected.

2019-02-27 The Healthy Brain Study has decided to use the PEP-data repository, starting with the data collection phase of the project. A final decision on use of the system for data sharing as well will be made on a later date.

Welcome to the PEP project page. This project is about privacy friendly exchange of medical data for specific medical research purposes. The PEP methodology combines advanced encryption with distributed pseudonymisation, and distribution of trusted data with fine-grained access management. The first pilot project is a research data repository for a large scale Parkinson's Disease research project.


The collection and analysis of medical data on a big data scale is becoming an essential approach to understand complicated diseases. In order to gain new insights it is important that international researchers can cooperate: they will have to access each other's data and contribute to the data sets. In many cases, such medical research involves privacy sensitive data about patients. Patients should be able to count on preservation of their privacy and on secure storage of their data. All this should comply with European privacy regulations, which are the most stringent in the world.

The PEP project builds on the Polymorphic Encryption and Pseudonymisation technique developed by Bart Jacobs and Eric Verheul. This technique stores pseudonymised data in encrypted form. Researchers working on the data can only decrypt the parts of the data for which they have access rights.

Pilot:Personalized Parkinson Project ("Parkinson op Maat")

The first case study performed with the PEP technique is Personalized Parkinson Project, a large scale Parkison's Disease research project by the medical centre from Radboud University, together with Verily (see their blog). This case study involves monitoring 650 patients over a period of two years, using amongst others wearable devices. The data collected this way will be shared, in pseudonymised form, with top research institutes world wide.


For more details, see our PEP whitepaper (PDF), or this shorter article from the Nieuw Archief voor Wiskunde. For a quick overview, see these slides.

For the positioning of PEP as a privacy-enabling technology in a medical research context see this paper.


The PEP project has its own funding from public sources, with a current budget of 1.6M Euro; 760K Euro is funded by the Province of Gelderland, and the remainder by Radboud University. Eventually the software will be made publicly available under an open source license.