MEDA-PKD: a dynamic, real-time analytics platform for precision care in autosomal dominant polycystic kidney disease

The use of medical real-world data is constrained by fragmented data infrastructures and the absence of tools integrating longitudinal clinical with molecular data at scale. Autosomal dominant polycystic kidney disease (ADPKD), the most common monogenic cause of kidney failure, exemplifies this gap given its phenotypic complexity and the need for individualized treatment decisions. We present MEDA-PKD (MEdical DAta translation service of Polycystic Kidney Disease), an interactive, near-real-time analytics platform that integrates clinical routine with research data from the German AD(H)PKD Tolvaptan Registry (NCT02497521, DRKS00008910) into a harmonized database ( https://doi.org/10.18716/adpkd_registry ). MEDA-PKD provides automated near-real-time analysis and dynamic visualization, replacing traditional static approaches to clinical cohorts. As of March 2026, MEDA-PKD visualized data from 1735 patients (mean follow-up 796 days). eGFR slope analysis of data from patients initiating tolvaptan therapy (332 patients) demonstrates the platform's capacity to evaluate real-world therapeutic impact in real-time. Other tabs include family history, medication, lifestyle, quality of life and a wide array of lab values (20,894 entries). Besides, MEDA-PKD integrates proteomics data and allows for secure individual patient-level data access. MEDA-PKD represents a paradigm shift by transforming static cohort data into a living, actionable knowledge resource in ADPKD and will serve as a template for other diseases.