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Collaborative Research Development Grant - Microsoft AI for Health is a grant from the Ovarian Cancer Research Alliance (OCRA) and the Global Ovarian Cancer Research Consortium that funds AI-driven research to personalize ovarian cancer care. The inaugural AI Accelerator Grant awards $1 million in research funding plus an additional $1 million in compute support from Microsoft's AI for Good Lab to international research teams.
The program supports projects examining whether artificial intelligence can improve prediction of survival and treatment response in ovarian cancer. Eligible applicants include academic and clinical researchers with the capacity to lead large-scale international collaborative AI studies in oncology. Check OCRA's grant portal for future cycles and letter of intent requirements.
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AI Accelerator Grant for Ovarian Cancer Research | OCRA Global Ovarian Cancer Research Consortium Awards Inaugural AI Accelerator Grant with Microsoft’s AI for Good Lab Posted on February 18, 2026 $1 million global research award, plus an additional $1 million in compute support, advances AI-driven efforts to personalize ovarian cancer care The Global Ovarian Cancer Research Consortium today awarded its inaugural AI Accelerator Grant to an international team of researchers to examine whether artificial intelligence (AI) can improve how survival and treatment response are predicted in ovarian cancer.
The AI Accelerator Grant is a $1 million global research award, with an additional $1 million in compute support from Microsoft’s AI for Good Lab. The AI Accelerator Grant was first announced in 2025 as the inaugural initiative of the Global Ovarian Cancer Research Consortium , marking a new, collaborative approach to accelerating ovarian cancer research through the use of artificial intelligence.
The international call for applications for the grant attracted 21 applications from collaborative teams around the globe, highlighting the interest and potential in this line of research. AI-Driven Research Targets the Most Common and Deadly Form of Ovarian Cancer Following a comprehensive review process by an international panel of experts, the successful research project has been decided.
AI to Predict Exceptional and Poor Survival from Real-World Biomarkers for Clinical Application focuses on high-grade serous ovarian cancer (HGSOC), the most common and deadly form of the disease. Despite advances in treatment, clinicians still have limited ability to predict how an individual patient’s cancer will behave or which therapies are most likely to be effective.
The research team behind the project is a group of experts from four countries—the United States, United Kingdom, Canada and Australia—representing epidemiology, molecular oncology, artificial intelligence, and clinical medicine.
Together, the team will analyze one of the largest and most comprehensive international collections of ovarian cancer data assembled to date, integrating tumor samples, clinical records, immune features, genetic information, and lifestyle factors from thousands of patients across international research groups.
Using AI, the researchers will analyze these data collectively to identify patterns linked to survival and treatment response that cannot be detected using current tools. The models will be tested in both historical and more recently treated patient groups, including those receiving modern therapies, with the goal of developing practical decision-support tools that can be used alongside existing hospital tests.
Improving Treatment Matching and Clinical Decision-Making with AI By improving how patients are matched to treatments and clinical trials, the project aims to reduce unnecessary side effects, support more personalized care, and ultimately help improve survival outcomes for people 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.
” Leading International Researchers Collaborating Through the Consortium The grant team includes: Pearce , Professor and Rogel Scholar, Department of Epidemiology, University of Michigan, United States; Professor Susan Ramus , Professor in the School of Clinical Medicine and Lead, Molecular Oncology Group, University of New South Wales, Australia; Dr. Ali Bashashati , Director of Artificial Intelligence Research, Ovarian Cancer Research Program (OVCARE), University of British Columbia, Canada; and Professor James Brenton , Professor of Ovarian Cancer Medicine, Senior Group Leader and Honorary Consultant in Medical Oncology, University of Cambridge, United Kingdom.
Formed in 2024, the Consortium unites four leading ovarian cancer research organizations from around the world—Ovarian Cancer Research Alliance (United States), Ovarian Cancer Research Foundation (Australia) , Ovarian Cancer Canada , and Ovarian Cancer Action (United Kingdom ).
Together, the partners are combining resources, data, and determination to accelerate progress in a disease where survival rates have seen limited improvement for decades. About Ovarian Cancer Research Alliance (OCRA) Ovarian Cancer Research Alliance is the largest global organization in the fight against ovarian and other gynecologic cancers, driving progress through innovative research , comprehensive support programs , and advocacy .
Since 1994, OCRA has invested $140 million in scientific breakthroughs, supports more than 110,000 individuals annually, and—as the only organization solely dedicated to advancing ovarian and gynecologic cancer priorities on Capitol Hill—has helped secure $3. 8 billion in federal funding. Learn more at ocrahope.
org . OCRA President & CEO Audra Moran Named Crain’s 2026 Notable Leader in Health Care Audra Moran, President and CEO of Ovarian Cancer Research Alliance (OCRA), has been recognized as a Crain’s New York Business 2026 Notable Leader in Health Care. Crain’s annual recognition spotlights health care executives whose leadership, innovation, and community commitment set a high bar for the field.
Honorees are selected based on demonstrated impact, both within … Continued OCRA Sponsors NCCN Guidelines for Cervical, Ovarian, and Uterine Cancer Patients This article was updated in April 2026 to reflect NCCN’s release of the 2026 Guidelines for Uterine Cancer Patients. OCRA is a proud sponsor of the 2026 Patient Guidelines for Cervical Cancer and Uterine Cancer, and the 2025 Patient Guidelines for Ovarian.
We believe ensuring access to clear, understandable information is critical.
NCCN provides wonderful … Continued FDA Approves Lifyorli Plus Abraxane for Platinum-Resistant Ovarian Cancer On March 25, 2026, the U.S. Food and Drug Administration (FDA) approved Lifyorli (relacorilant), made by Corcept Therapeutics, in combination with Abraxane (nab-paclitaxel) for adults with platinum-resistant epithelial ovarian, fallopian tube, or primary peritoneal cancer who have received one to three prior lines of treatment, including prior Avastin (bevacizumab).
The approval follows last month’s FDA … Continued
Based on current listing details, eligibility includes: Applicants for collaborative research development. Specific details on the Microsoft AI for Health collaboration would be in the full LOI. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Varies Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
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-Purpose. This Funding Opportunity Announcement (FOA) encourages Small Business Innovation Research (SBIR) grant applications from small business concerns (SBCs) that propose to develop, standardize, and validate new and innovative assays, integrated strategies, or batteries of assays that determine or predict specific organ toxicities (e.g., ocular, dermal, hematotoxicity, cardiotoxicity, gastrointestinal toxicity, hepatotoxicity, nephrotoxicity, ototoxicity, olfactory loss, bladder toxicity, neurotoxicity, pulmonary toxicity, endocrine toxicity, and pancreatic beta cell toxicity), resulting from both acute and chronic exposures to various chemicals, environmental pollutants, biologics and therapeutic molecules or drugs. In addition, this FOA encourages the development, standardization, and validation of new models of arthritis, convulsion, infection and shock. New approaches for high throughput toxicity screening that involves the use of molecular endpoints, computer modeling, proteomics, genomics and epigenomics and the development of virtual tissues are also encouraged as are development of 3-dimensional organ models for toxicity evaluation. -Mechanism of Support. This FOA will utilize the SBIR (R43/R44) grant mechanisms for Phase I, Phase II, and Fast-Track applications and runs in parallel with a FOA of identical scientific scope, PA-09-007, which encourages applications under the Small Business Technology Transfer (STTR) (R41/R42) grant mechanisms. Funding Opportunity Number: PA-09-006. Assistance Listing: 93.113,93.173,93.361,93.389,93.837,93.846,93.847,93.848,93.849,93.859,93.867. Funding Instrument: G. Category: ED,ENV,FN,HL.
Purpose. This Funding Opportunity Announcement (FOA), issued by the National Cancer Institute (NCI), National Institutes of Health (NIH), invites Small Business Innovation Research (SBIR) cooperative agreement applications from small business concerns (SBCs) that propose to develop new, or to improve existing application(s) of nanotechnology-based therapeutics or/and in vivo diagnostics. This FOA will specifically support pre-clinical optimization and testing of these cancer-relevant nanotechnology applications against the intended cancer type. The proposed projects must be milestone-driven and must be clearly directed toward development of an ultimate commercial product. The outcomes are expected to advance the discovery and pre-clinical optimization phase so that an Investigational New Drug (IND) or Investigational Device Exemptions (IDE) application could be submitted to the Food and Drug Administration (FDA) by the end or shortly after completion of the Phase II project period. To facilitate these steps, the NCI will assist the awardees in various ways, including the support through the NCI-sponsored Nanotechnology Characterization Laboratory. This FOA will NOT support basic research projects, studies on disease mechanisms, and clinical trials. Mechanism of Support. This FOA will utilize the SBIR (U43/U44) cooperative agreement mechanisms for Phase I and Phase II applications. Funds Available and Anticipated Number of Awards. Awards issued under this FOA are contingent upon the availability of funds and the submission of a sufficient number of meritorious applications. The total amount awarded and the number of awards will depend upon the quality, duration, and costs of the applications received. Funding Opportunity Number: PAR-10-286. Assistance Listing: 93.393,93.394,93.395,93.396. Funding Instrument: CA. Category: ED,HL. Award Amount: Up to $150K per award.