The UCSF Information Commons is pleased to announce the beta release of Information Commons on FAC (IC FAC), a new on-premises computing environment designed to support secure, interactive data science and AI-enabled research. 

IC FAC extends Information Commons research data assets onto the Academic Research Services (ARS) Facility for Advanced Computing (FAC), providing researchers with a modern, responsive environment for exploring data, developing analytical pipelines, and prototyping AI and machine learning models. The environment is designed to reduce technical overhead while enabling high-performance, data-local analysis. 

IC FAC offers interactive CPU and GPU computing, PHI-compliant storage for sensitive research data, and a performance-tuned database optimized for fast, iterative querying of large clinical datasets. Pre-configured software environments and support for AI and large language model workflows further streamline research setup and experimentation. 

In addition to structured clinical and genomic data assets, IC FAC now provides access to Imaging Commons data and associated exploration tools. Imaging Commons includes de-identified radiology images across multiple modalities (e.g., MRI, CT), linked with patient demographics, diagnoses, and procedural information, along with rich metadata such as imaging sequences, acquisition parameters, DICOM headers, and image pixels. Imaging Commons data and tools have been fully migrated from the IC on Wynton environment and are now available to research users through IC FAC, enabling scalable, compute-local imaging analysis alongside other multimodal clinical data. 

IC FAC complements existing ARS computing services by focusing on interactive, researcher-driven workflows, while CoreHPC continues to support large-scale, batch-oriented and long-running high-performance computing workloads. 

The IC FAC beta program will run through February and has limited user capacity. During beta, access is being prioritized for researchers transitioning from the IC on Wynton environment. A broader general release for all research users is planned for March, with a subscription-based pricing model aligned with other research computing environments. 

The launch of IC FAC reflects close collaboration across Academic Research Services, with critical contributions from the ARS Information Commons, FAC and CoreHPC teams, whose focus on user experience, infrastructure expertise and operational support were essential to the successful implementation. This transition also represents a strong partnership with the Center for Intelligent Imaging in the Department of Radiology, whose expertise and leadership were instrumental in migrating Imaging Commons data and tools and ensuring continuity of access for imaging researchers.