New platform unites polycystic kidney disease data for near-real-time analysis
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The medical sector generates vast amounts of valuable data. However, this information is often stored in different systems and is only analyzed in isolated instances for research projects. The opportunity to pool data for the purpose of improving patient care and research is often overlooked.
In response to this missed opportunity, a research team led by Dr. Roman-Ulrich Müller, group leader at the University of Cologne's CECAD Cologne Cluster of Excellence on Aging and Aging-associated Diseases and director of the Department of Nephrology at Düsseldorf University Hospital (UKD), has developed the digital platform MEDA-PKD (MEdical DAta translation service of Polycystic Kidney Disease). Among other things, it links clinical follow-up data, laboratory results, imaging, information on medication and quality of life, as well as initial molecular data on new biomarkers.
The researchers have published a paper on the development and potential applications of this platform, entitled "MEDA-PKD: A Dynamic, Real-Time Analytics Platform for Precision Care in Autosomal Dominant Polycystic Kidney Disease" in the journal npj Digital Medicine.
Bringing kidney disease data together
Using the example of the most common genetic kidney disorder—polycystic kidney disease, which affects more than 7 million people worldwide—this study demonstrates how data from clinical practice and research can be automatically collated and made available almost in real time for research purposes and, in the future, for individual patient care as well.
"Registry and cohort data often remain hidden within hospital systems and on individual computers, and are inaccessible to those affected. MEDA-PKD makes them visible—in consolidated form and in real time," explains Dr. Philipp Antczak, head of the Computational Biology of Aging group at the Center for Molecular Medicine Cologne (CMMC). "This enables us to learn more quickly from the experiences of large numbers of patients and, in the long term, to put this knowledge to use in providing more personalized care," adds group leader Müller.
Real-world treatment insights and faster consultations
The researchers have shown that this approach not only works from a technical standpoint but that it also yields medically relevant insights, demonstrating this using, among other things, tolvaptan, the only medicine specifically authorized for the treatment of polycystic kidney disease. Based on data from routine clinical practice, they have been able to show that the treatment slows down the loss of kidney function. This demonstrates that MEDA-PKD enables the ongoing assessment of the efficacy of treatments under real-world conditions.
This benefit has already become apparent in the area of patient counseling: in an initial study, seven experienced doctors rated MEDA-PKD as very user-friendly. For example, the time required to compile information for a consultation on tolvaptan therapy was reduced by approximately 72%. Patients can also use the platform to read more about the statistics and analyses for themselves.
"With MEDA-PKD, we have developed a tool based on patient registry data collected over many years, which is already helping us to advise our patients. This is the first practical example of an approach that could also be applied to other conditions in the future," says Dr. Sita Arjune of University Hospital Cologne.
Dr. Franziska Grundmann, a nephrologist at University Hospital Cologne, adds, "MEDA-PKD helps us live up to our own high standards when it comes to providing personalized medical advice and support to patients."
Extending the framework to other diseases
In principle, the basic technical framework can be adapted to further medical conditions, such as other chronic kidney diseases, heart failure, cystic fibrosis or cancer. The long-term goal is therefore to create a 'learning health care system' in which data from health care provision are not only collected, but also continuously yield new insights.
Researchers from the CECAD Cluster of Excellence and the CMMC at the University of Cologne, as well as from University Hospital Cologne, Heinrich Heine University and Düsseldorf University Hospital, have collaborated on the development and testing of MEDA-PKD.
Publication details
Franziska Grundmann et al., MEDA-PKD: a dynamic, real-time analytics platform for precision care in autosomal dominant polycystic kidney disease, npj Digital Medicine (2026). DOI: 10.1038/s41746-026-03267-0
Journal information: npj Digital Medicine
Key medical concepts
Polycystic Kidney, Autosomal Dominant
Clinical categories
Nephrology Provided by University of Cologne Who's behind this story?
Gaby Clark
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