Can AI help predict outcomes in ovarian cancer?

ANN ARBOR, Michigan – An international team of researchers has received $2 million in support to understand how artificial intelligence can improve prediction of ovarian cancer survival and treatment response.

New treatments for high-grade serous ovarian cancer, the most common form of ovarian cancer, have been introduced over the last decade, but still 70% of patients will relapse and more than half of patients die within five years.

With this grant, researchers will use state-of-the-art AI to help predict survival and guide treatment selection and clinical trial recommendations. The award includes a $1 million AI Accelerator Grant from the Global Ovarian Cancer Research Consortium, founded by the Ovarian Cancer Research Alliance (United States),Ovarian Cancer Action (United Kingdom), Ovarian Cancer Canada and Ovarian Cancer Research Foundation (Australia),and another $1 million in compute power from Microsoft’s AI for Good Lab.

The researchers represent the Multidisciplinary Ovarian Cancer Outcomes Group, or MOCOG, which was founded in 2012 with a goal to identify the factors associated with long-term survival of high-grade serous ovarian cancer. The group includes investigators and patient advocates from Australia, Canada, the United Kingdom and the United States.

“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. 

The team will analyze one of the largest and most comprehensive international collections of ovarian cancer data assembled to date, integrating tumor images and molecular data, clinical records, immune features, genetic information and lifestyle factors from patients across international research groups. 

Despite the robust data, conventional statistical models have had limited success identifying distinct markers of longer survival. The goal is to use AI to uncover more complex patterns and develop robust tools to predict treatment response that will directly guide treatment choices.

The research team leaders include experts from four countries, representing epidemiology, molecular oncology, artificial intelligence, and clinical medicine: Leigh Pearce, University of Michigan, United States; Susan Ramus, University of New South Wales, Australia; Ali Bashashati, University of British Columbia, Canada; and James Brenton, University of Cambridge, United Kingdom. Additional U.S. partners include Elizabeth Slocum, University of Michigan; Andrew Berchuck, Duke University; and Jean Richardson, patient advocate and emeritus professor, University of Southern California.

“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.

”Microsoft is partnering on this grant through its AI for Good Lab, donatingnearly$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 find lifesaving treatments for ovarian cancer,” said Juan Lavista Ferres, Microsoft Chief Data Scientist and Director of Microsoft’s AI for Good Lab. “Equipping leading researchers around the globe with powerful AI tools and computing resources will help accelerate their critical work and drive progress toward breakthroughs that could save lives.”