Mayo Clinic deploys NVIDIA DGX SuperPOD to accelerate pathology foundation models
Mayo Clinic deployed an NVIDIA DGX SuperPOD with NVIDIA DGX B200 systems to support foundation model development for pathomics, drug discovery and precision medicine. In partnership with Aignostics, Mayo Clinic built the Atlas pathology foundation model, trained on more than 1.2 million histopathology whole-slide images. The new infrastructure is reducing four weeks of pathology slide analysis work to one week.
Overview
Mayo Clinic deployed an NVIDIA DGX SuperPOD with NVIDIA DGX B200 systems to support foundation model development for pathomics, drug discovery and precision medicine. In partnership with Aignostics, Mayo Clinic built the Atlas pathology foundation model, trained on more than 1.2 million histopathology whole-slide images. The new infrastructure is reducing four weeks of pathology slide analysis work to one week.
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Inspect the highlighted sourceThe challenge
Mayo Clinic sought to meaningfully improve patient outcomes by detecting disease early enough to intervene, which required advanced compute infrastructure capable of processing the large, high-resolution imaging essential for training AI foundation models in pathomics, drug discovery and precision medicine.
The solution
Mayo Clinic deployed NVIDIA DGX SuperPOD with NVIDIA DGX B200 (Blackwell-powered) systems, collaborating with NVIDIA to support foundation model development for pathomics, drug discovery and precision medicine. In partnership with Aignostics, Mayo Clinic developed the Atlas pathology foundation model, trained on more than 1.2 million histopathology whole-slide images, building on Mayo's platform data of over 20 million digitized pathology slides.
Reported business value
The Blackwell infrastructure is reducing four weeks of pathology slide analysis and foundation model development work to just one week. With the Atlas foundation model, Mayo Clinic clinicians and researchers can improve accuracy and reduce administrative tasks.
Sources
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