Lynkeus is an independent research and consultancy firm specialized on clinical implementation of computerized applications in healthcare. In collaboration with hospitals and labs, the group designs decision support solutions, large-scale biomedical data sharing platforms and simulations systems for biomedical R&D, guiding their development, validation and clinical implementation. With over 15 years of experience in large scale, EU-funded projects, Lynkeus delivers tangible innovation by integrating deep clinic, technological, managerial and legal competencies.

Role in the project

Lynkeus leads WP1 working on legal and ethical analyses from which technical specifications for the platform will be generate, developing in a privacy-by-design fashion the system architecture. LYN also implements the Blockchain based data access control system and AI passport. Finally, LYN leads exploitation and innovation planning tasks in WP7.


The University of Pisa (UNIPI) is among the oldest and most prestigious universities in Europe. In this project UNIPI is represented by the Department of Translational Research and New Technologies in Medicine and Surgery. It is one of the main departments of the medical area of UNIPI, with 91 faculty, 28 postdoctoral researchers and 53 office workers. The Department includes the following academic units: Clinical Oncology, Surgery, Pathology, Microbiology, Molecular Biology, Internal medicine, Radiology, Radiation Oncology and Clinical Pharmacology. Those academic units are also part of the Imaging Department of the Pisa University Hospital. The Imaging Department groups two Academic Units of Diagnostic Radiology and one Academic in Neuroradiology, one Academic Unit of Nuclear Medicine, one Interventional Radiology Unit and one Breast Unit. An Academic Unit of radiation Oncology Unit is linked with the Diagnostic Radiology and Nuclear Medicine in the management of oncologic patients.

Role in the project

UNIPI is involved in WP2, for new cancer imaging data depositions, as well as for defining clinical requirements and validating the AI solutions for the liver, colorectal and liver cancer use cases. UNUIPI also participates in defining criteria and methods for assessing clinical effectiveness in WP7.