Professor of Medicine/Nephrology, in particular Kidney Transplantation - Vice-chair Leiden Transplant Center - Chair Transplant Working Group NEFRO-NL - Eurotransplant Delegate - Passed Chair Dutch National Kidney Advisory Committee - Passed (Non-executive) board member Netherlands Federation of Nephrology - Passed (Non-executive) board member Nefrovision

More information about Aiko de Vries

Professor of Medicine/Nephrology, in particular Kidney Transplantation

- Vice-chair Leiden Transplant Center
- Chair Transplant Working Group NEFRO-NL
- Eurotransplant Delegate

- Passed Chair Dutch National Kidney Advisory Committee
- Passed (Non-executive) board member Netherlands Federation of Nephrology
- Passed (Non-executive) board member Nefrovision

Sustainably advance kidney transplant outcome

Chronic kidney disease is globally a leading cause of non-communicable disease. Organ transplantation is the best kidney replacement therapy for longevity and quality of life. Yet kidney transplants have a limited lifespan. The mission of the chair is to sustainably advance kidney transplant outcome

The clinical and translational research, in line with the moonshot One Graft for Life,  focuses on improving long-term graft survival from immunological and non-immunological causes through personalized and regenerative medicine.

Academic career

Aiko P.J. de Vries MD, PhD is an internist-transplant nephrologist trained at University of Groningen (MSc; PhD; residency), University of Pennsylvania, and Leiden University (nephrology and transplant fellowship). He obtained his PhD in 2011 on metabolic consequences of kidney transplantation. Currently, he investigates novel immunosuppressive strategies (phase 1-4 clinical trials) and curates the granular multidisciplinary Leiden Transplant Database and Biobank. In close collaboration with partners, he studies novel biomarkers, the immunology of rejection through (spatial) molecular pathology, late complications of transplantation, and novel health delivery concepts using remote monitoring, prediction modelling and artificial intelligence to sustainably advance transplant outcome.