Providence, Microsoft Research, University of Washington unveil GigaTIME, an AI-powered pathology breakthrough set to transform cancer immunotherapy research
RENTON, Wash., Dec. 9, 2025 — A recent joint study from Providence, Microsoft Research and the University of Washington showed that GigaTIME — a new AI-powered pathology model — can analyze tumor microenvironments to help reveal how individual immune cells interact with tumors. This can potentially unlock improved treatment response for millions of patients who receive targeted immunotherapies for cancer.
The GigaTIME study was recently published in Cell, a leading medical journal.
"GigaTIME is about unlocking insights that were previously out of reach," explained Carlo Bifulco, MD, chief medical officer of Providence Genomics and medical director of cancer genomics and precision oncology at the Providence Cancer Institute. “By analyzing the tumor microenvironment of thousands of patients, GigaTIME has the potential to accelerate discoveries that will shape the future of precision oncology and improve patient outcomes."
The team built the GigaTIME model using multiplex immunofluorescence (mIF), a leading-edge imaging technology that can positively identify tumor and different immune cell types in a tissue biopsy. mIF is currently low-throughput and costly, so the team used mIF to train GigaTIME to generate accurate virtual mIF images from standard histopathology slides, which are produced for any tissue biopsy reviewed by pathologists.
GigaTIME was then used to create a total of about 300,000 virtual mIF images from these patients, spanning 24 cancer types and 306 cancer subtypes, to find more than 1,200 statistically significant associations in mIF proteins with key factors including biomarkers, staging and patient survival. Key applications of GigaTIME include helping to efficiently assess tumor-immune interactions, predict immunotherapy response, and identify mechanisms of immune evasion that inform strategies to overcome resistance.
“GigaTIME is a testament to what’s possible when cutting-edge AI meets real-world clinical data at scale,” explained Hoifung Poon, General Manager of Real-World Evidence, Microsoft Redmond. “By working closely with Providence and University of Washington, we’ve shown how multimodal AI can turn routine pathology slides into rich, spatial proteomics—unlocking discoveries that were once out of reach. Our hope is that by making GigaTIME openly available, we can accelerate research and help the entire field move toward more precise, personalized cancer care.”
This is the first population-scale study of tumor immune microenvironment based on virtual spatial proteomics, enabling systematic discovery across large patient cohorts that was previously impossible due to the cost and scarcity of mIF data.
GigaTIME builds on GigaPath, published in Nature in 2024 by the same Providence-Microsoft-UW collaboration. GigaPath analyzes whole-slide patterns to predict mutations and cancer subtypes. GigaTIME extends this work by generating virtual spatial proteomics images that reveal how individual immune cells interact with tumors - critical information for predicting and improving immunotherapy response.
“This work enables population-scale analysis of tumor-immune interactions that was previously impossible due to cost and scalability constraints," said Brian Piening, Ph.D., director of research for Providence Genomics. "GigaTIME allows us to identify patterns across thousands of patients that inform strategies to reprogram 'cold' tumors into 'hot' tumors more susceptible to immunotherapy.”
