UT Southwestern Medical Center Propels AI-Driven Medical Research with IBM Fusion to Support Researchers, Doctors, and Patients
ARMONK, N.Y., Nov. 4, 2025 /PRNewswire/ — IBM (NYSE: IBM) today announced that IBM Fusion has delivered one of the industry’s first implementations of the NVIDIA AI Data Platform reference design, featuring NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, NVIDIA Networking and NVIDIA AI Enterprise software.
UT Southwestern Medical Center is the first client to deploy this reference design with IBM Fusion, unlocking new capabilities for large-scale training and inferencing – enabling bigger models, more complex datasets, and fast semantic query responses with precision.
IBM Advances Data Storage and Compute to Propel AI Forward with NVIDIA
NVIDIA AI Data Platform is a customizable reference design for the increased demands of AI infrastructure that integrates enterprise storage with accelerated computing to power AI agents with near-real-time business insights. Leveraging NVIDIA AI infrastructure with IBM Fusion’s content-aware data services, clients can continuously process, index, and vectorize unstructured and semi-structured data to create AI-ready data for agents and derive insights to enhance the value of AI applications. IBM Fusion’s content-aware data services integrate with NVIDIA NeMo Retriever Microservices to deliver AI agents that also use that data indexing, providing clients with a full stack experience and fast-tracked path to inferencing capabilities.
NVIDIA AI Data Platform with IBM Fusion Leverages Data for AI Use
UT Southwestern, a leading academic medical center in the United States, is one of the first clients in the world using IBM Fusion to implement the NVIDIA AI Data Platform reference design, leveraging content-aware services to automatically prepare the medical center’s data for AI use. IBM Fusion is engineered to unlock new possibilities for training and inferencing at scale and built to give clients the ability to run larger models, process more complex datasets, and obtain fast and accurate responses to semantic queries.
IBM Fusion supports different types of deep research use cases that could benefit drug research, clinical training, and researcher productivity. Specific areas of use include:
- Drug Discovery Acceleration: Using NVIDIA BioNeMo™ open-source framework integrated with IBM Fusion, researchers can build and train deep learning models for biomolecular discovery, with the goal of researchers bringing novel therapeutics to patients faster.
- Patient Digital Avatars: Clients internal data and medical literature are securely ingested into IBM Fusion to power an innovative training environment where AI-driven patient avatars simulate clinical scenarios, empowering students to formulate, validate, and deliver diagnoses more efficiently.
- Helixa AI Assistant: Enhance BioHPC researcher productivity with secured, contextual support by leveraging research data processed by IBM Fusion.
“IBM Fusion is engineered to help organizations conduct deep research by unifying applications and access to data across hybrid clouds to help simplify discovery and data activation that is AI-ready,” said Sam Werner, GM of IBM Storage. “Our integrations with NVIDIA is built to help clients unlock hidden insights from data to supercharge AI and analytics initiatives.”
“AI is opening transformative opportunities in healthcare research—from decoding genomics to interpreting complex medical imaging and accelerating translational breakthroughs,” said Anne Hecht, Senior Director, Enterprise Platforms at NVIDIA. “The context-aware IBM Fusion platform, built with the NVIDIA AI Data Platform reference design, is making diverse, multimodal datasets available to researchers and healthcare providers using AI to accelerate discovery.”
