Salt Lake City – October 06, 2026 -- ARUP Laboratories has secured a spot in the second cohort of challenge projects on Utah's Redtail AI Factory, gaining access to a supercomputer ranked No. 159 globally to accelerate a proprietary diagnostic AI model for blood cancer detection.
ARUP's EventHorizon model targets faster, more accurate blood cancer diagnosis
The project, titled "Scaling EventHorizon with Redtail: A Foundation Model for Clinical Flow Cytometry," aims to build a foundation model that helps pathologists interpret complex flow cytometry data used to diagnose blood cancers and other hematologic diseases. The tool is being developed by a team at the ARUP Institute for Research and Innovation in Diagnostic and Precision Medicine, including David Ng, MD, FCAP, and research data scientists Muir Morrison and Mattia Medina Grespan.
Redtail computing power cuts development timelines from months to a fraction of that
Robert Ohgami, MD, PhD, MBA, FCAP, vice president of the ARUP R&I Institute, said access to Redtail's computational capacity could compress model development that would otherwise take months into a far shorter window. Training on larger datasets with more extensive computational iterations could help the model flag rare, diagnostically challenging disease patterns, improve diagnostic accuracy, reduce turnaround times, and help patients start appropriate therapies sooner, according to Ohgami.
Redtail ranks No. 159 on the Top 500 global supercomputer list
The Redtail AI Factory also placed No. 76 on the Green 500 list for energy efficiency and ranks fifth among U.S. public universities for supercomputing performance, according to the University of Utah. The infrastructure was built through a $50 million public-private partnership involving the University of Utah, the state of Utah, Brynn Ballard and Peter Huntsman, and the Huntsman Family Foundation, with hardware supplied by Hewlett Packard Enterprise and NVIDIA.
ARUP's project was selected through a competitive review process
Manish Parashar, the University of Utah's chief AI officer and executive director of its Scientific Computing and Imaging Institute, said the challenge winners, including ARUP, will serve as early users of the Redtail system. Proposals were evaluated on readiness, innovation potential, anticipated impact, and ability to leverage Redtail's computing capabilities.