An industry-funded engagement with the Clinical Research Unit of Nestlé. Using a completed study as the worked example, we show the team what anonymization can achieve: how to assess re-identification risk, how to choose suitable methods and how much analytical utility can be kept. The focus is on learning, so that the team can make these decisions for future studies themselves.
The work follows the EU GDPR/EDPB framework. It starts from a formal disclosure-risk assessment and tests both identity and attribute disclosure (who is in the data, and what can be learned about them), not k-anonymity alone. Pseudonymized data remains personal data, so anonymization is the goal wherever the analytical purpose allows; pseudonymization is optimized where utility genuinely requires it.
The engagement runs alongside our anonymization of a clinical study for Nestlé. It is led by Prof. Dr. Matthias Templ (FHNW), with Roman Müller and Oscar Thees on the project team.