The Global Ovarian Cancer Research Consortium has announced the recipients of its inaugural AI Accelerator Grant, awarding $1 million in global research funding alongside a further $1 million in compute support provided by Microsoft’s AI for Good Lab. The funding will support an international research team examining whether artificial intelligence (AI) can improve predictions of survival and treatment response in ovarian cancer.
The AI Accelerator Grant was first unveiled in 2025 as the Consortium’s first major initiative, signalling a new collaborative approach to advancing ovarian cancer research through the use of AI. The global call for proposals attracted 21 applications from international research partnerships, reflecting strong interest in applying AI to clinical challenges in ovarian cancer care.
Following a detailed review by an international panel of experts, one project was selected. Titled AI to Predict Exceptional and Poor Survival from Real-World Biomarkers for Clinical Application, the research focuses on high-grade serous ovarian cancer (HGSOC), which is the most common and deadly form of the disease. Despite progress in treatment options, clinicians still face major limitations in predicting how an individual patient’s cancer will progress or which therapies are most likely to work.
The successful team brings together specialists from four countries — the United States, United Kingdom, Canada and Australia — spanning epidemiology, molecular oncology, artificial intelligence and clinical medicine. The group will work with one of the largest and most detailed international collections of ovarian cancer data assembled to date. This dataset brings together tumour samples, clinical records, immune characteristics, genetic data and lifestyle factors from thousands of patients drawn from research groups across several countries.
Using AI methods, the researchers will examine these datasets collectively to identify patterns linked to patient survival and responses to treatment that are not detectable using existing analytical tools. The models developed through the project will be tested in both historical patient groups and those treated more recently, including individuals receiving modern therapies. The stated aim is to produce practical decision-support tools that can be used alongside existing hospital tests to inform clinical care.
The project is intended to support more tailored treatment decisions and improve how patients are matched to appropriate therapies and clinical trials. By doing so, the researchers aim to reduce avoidable side effects, support more personalised care pathways and, ultimately, help improve survival outcomes for people living with ovarian cancer.
“While new therapies have generated a lot of enthusiasm, we have not been able to reliably predict who is likely to benefit long-term from these treatments and who is not. We urgently need new tools to more accurately predict survival and guide clinical decision-making to improve overall patient outcomes,” said principal investigator Leigh Pearce, Ph.D., M.P.H., Professor of Epidemiology at the University of Michigan School of Public Health and co-leader of the Cancer Control and Population Sciences Program at the University of Michigan Rogel Cancer Center.
“This grant reflects exactly why we created the Global Ovarian Cancer Research Consortium — to bring together outstanding global partners to tackle the challenges that have stalled progress in ovarian cancer for far too long,” said Audra Moran, President and CEO of Ovarian Cancer Research Alliance. “Artificial intelligence has the potential to accelerate breakthroughs across the ovarian cancer continuum, from prediction to treatment selection.
By pairing global collaboration with the compute support generously provided through Microsoft’s AI for Good Lab, the Consortium and its AI Accelerator Grant are enabling researchers to analyze complex international datasets at a scale that has not previously been possible, helping to move promising ideas closer to real-world impact for patients worldwide. Microsoft is generously partnering on this grant through its AI for Good Lab, donating up to $1 million in in-kind Azure compute credits to the project. This computing support will enable the research team to accelerate large-scale data analysis essential to the project’s goals.
“New discoveries are urgently needed to unlock lifesaving treatments for ovarian cancer,” said Juan Lavista Ferres, Microsoft Chief Data Scientist and Director of Microsoft’s AI for Good Lab. “This work demonstrates what becomes possible when deep scientific expertise is paired with cutting edge AI. By equipping leading researchers around the world with advanced AI tools and computing resources, we can accelerate their critical efforts that have the potential to save lives.”
