ARUP Laboratories Joined Redtail AI Challenge

The laboratory will utilize state supercomputing power to build a clinical diagnostic tool for flow cytometry.

Updated on Oct. 6, 2026 in Artificial Intelligence

Isometric editorial illustration of a server rack and scientific equipment in a sterile research laboratory. — ARUP Laboratories has joined the second cohort of the Redtail AI Factory challenge to develop a foundation model for clinical flow cytometry. AI Illustration. Upload story photo >

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ARUP Laboratories has been selected to join the second cohort of the Redtail AI Factory challenge. The team will use Utah's supercomputing infrastructure to develop a foundation model designed to assist pathologists in analyzing complex flow cytometry data.

Why it matters

This partnership aims to integrate high-performance computing into clinical diagnostics, potentially improving the accuracy and speed of identifying rare disease patterns. It highlights an initiative to expand advanced AI resources for critical healthcare research across Utah.

The Redtail system, which secured $50 million in public-private funding, ranks 159th on the Top 500 list and 76th on the Green 500 for energy efficiency.

The players

ARUP Laboratories

This Salt Lake City-based national clinical and anatomic pathology reference laboratory provides diagnostic testing services.

University of Utah

This public research university manages the Redtail supercomputing infrastructure and oversees the initiative.

David Ng

He is a member of the project team working on the development of the clinical foundation model.

Muir Morrison

He is part of the research team utilizing the supercomputing infrastructure for the Redtail challenge.

Mattia Medina Grespan

He serves as a team member on the project focused on flow cytometry diagnostic modeling.

The details

The project, titled Scaling EventHorizon with Redtail: A Foundation Model for Clinical Flow Cytometry, was chosen through a competitive review process. By accessing the University of Utah-managed system, the research team aims to streamline data analysis workflows for pathologists.

October 6, 2026: ARUP Laboratories was selected for the Redtail challenge cohort.

The Big Picture

This project follows the pattern of state-funded technological initiatives by applying high-performance computing to solve specific, complex clinical diagnostics problems. It serves as an example of how large-scale AI infrastructure can be leveraged to address targeted, critical health research.

For patients, this development may lead to faster diagnosis of rare diseases and improved accuracy in pathology reports. It represents a potential shift in how diagnostic labs manage complex data to provide more timely medical information.

The takeaway

This partnership demonstrates the increasing reliance on supercomputing to process large-scale diagnostic data in medicine. As these models evolve, patients should expect faster turnaround times for complex lab results that previously required more intensive manual review.