A highly diverse team imagining the undiscovered

RENAL RESEARCH INSTITUTE

Transforming
patient care
through data-driven
innovation

ABOUT THE RENAL RESEARCH INSTITUTE

The heart of RRI’s capacity for innovation is our ability to examine complex problems through multiple lenses.

The Renal Research Institute (RRI) is an internationally recognized incubator of ideas, treatment processes, and technologies to improve the lives of kidney patients. RRI’s leadership in data analytics, computational biomedicine and AI, as well as our access to a large patient population, accelerates the pace of scientific discoveries and their translation into applied medicine. Our team includes some of the brightest minds from around the world, who, along with their disciplinary expertise, bring a deep understanding of global healthcare issues and challenges.

 

Our Research

We operate at the intersection of clinical data, machine data, and real-world practice, with access to a large patient population and one of the world's largest and richest renal datasets. Our deep connection to the scientific community and to med-tech innovators gives us the rare ability to translate insight into action—quickly, precisely, and meaningfully.

 

Latest Research & News

Latest Research

  • Doris H Fuertinger, Felix J Meigel, Aiyuan Wang, Sabrina Casper, Sheng-Han Yueh, Kevin Ho

    Background: Ultrafiltration (UF) during hemodialysis is typically prescribed as a fixed treatment goal and delivered using a largely constant ultrafiltration rate throughout the session. We evaluated whether Adaptive Ultrafiltration (Adaptive UF), a physiological closed-loop control strategy guided by continuous relative blood volume (RBV) monitoring, could improve RBV target attainment while individualizing fluid removal within predefined treatment constraints. Methods: We performed a paired patient-specific in silico study using 119,472 historical hemodialysis treatments from 11,246 U.S. patients. Treatment-specific plasma refill rate profiles were derived from recorded RBV and ultrafiltration data. For each historical treatment, a corresponding Adaptive UF treatment was simulated and compared with the corresponding originally delivered treatment. Outcomes included the percentage of time within a predefined favorable RBV target region, UF delivery, and operational performance. Results: Mean time within the RBV target region increased from 36.3% with historically delivered treatments to 56.4% with Adaptive UF, showing an absolute improvement of 20.2 percentage points (95% CI, 19.9-20.5); target attainment improved in 90.0% of patients. Mean area outside the target range decreased from 280.7 to 139.5 RBV %-minutes. Mean achieved UF volume increased by 296.4 mL, although treatment-level UF delivery was bidirectional, increasing in 83.1% and decreasing in 16.9% of treatments. UF rates remained below 13 mL/kg/h in all simulations, and 99.4% of treatments remained within predefined UF volume limits. Conclusions: Adaptive UF improved intradialytic RBV target attainment and individualized UF delivery within predefined treatment constraints. Prospective studies are required to determine whether these physiological improvements translate into clinical benefit.

No Results Found

Latest News

No Results Found

Program

LATEST EPISODE

Beyond the Equation | Dr. Amaka Eneanya on Kidney Function, Clinical Change, and Communication

March 2, 2026

In this episode of Frontiers in Kidney Medicine and Biointelligence, host Len Usvyat, MD, is joined by Amaka Eneanya, MD, MPH, FASN, Adjunct Professor of Medicine at Emory University School of Medicine and former Chief Transformation Officer at Emory Healthcare. Dr. Eneanya reflects on kidney function estimation, the evolution of clinical tools in nephrology, and the role of communication, patient perspectives, and digital platforms in shaping medical discourse. This episode offers an in-depth discussion on how research findings move from theory into real-world clinical practice.