AI Accelerator Grant

The AI Accelerator Grant is administered by the Ovarian Cancer Research Alliance as part of the Global Ovarian Cancer Research Consortium, a collaboration that includes partner organizations in the United States, United Kingdom, Canada, and Australia. These organizations collectively fund and support global ovarian cancer research initiatives aimed at improving patient outcomes. The program reflects a coordinated international effort to accelerate scientific breakthroughs by combining expertise, resources, and infrastructure across multiple countries. The purpose of the AI Accelerator Grant is to support large-scale, data-intensive research collaborations that apply artificial intelligence and machine learning techniques to advance ovarian cancer research. The grant specifically targets innovative projects that can improve understanding, detection, treatment, and overall patient survival. Emphasis is placed on interdisciplinary collaboration, particularly between computational scientists and clinical researchers, and on projects that demonstrate strong scientific rigor and potential for meaningful impact in the field. The funding structure provides up to 1000000 USD in total support over a three-year period to the institution of the Principal Investigator. In addition to direct financial support, applicants may request in-kind cloud computing resources through Amazon Web Services, with support of up to 200000 USD per year and up to 600000 USD total. These resources must be used within a designated research environment, specifically OCRA’s Discovery Lab Trusted Research Environment, and cannot be applied to other computational platforms. The grant includes requirements for data sharing, including depositing generated datasets into the designated platform, subject to privacy and consent conditions. Eligibility is limited to collaborative teams composed of at least four senior investigators representing the United States, United Kingdom, Canada, and Australia. The team must include a designated Principal Investigator and at least one specialist in artificial intelligence or a related computational field. All investigators must hold full-time faculty or equivalent appointments at accredited non-profit research institutions and possess a doctoral degree at the time of application. Funding is not available to for-profit entities, consulting organizations, or non-research-focused nonprofits. Additional expectations include the inclusion of patient or public partners where appropriate and a strong preference for clinical expertise within the team. The application process begins with the submission of a Letter of Intent through the SmartSimple grant management system. Required components include a scientific abstract, an AI-specific summary, a patient involvement summary, biosketches for all key personnel, and a high-level budget estimate. Following peer review of LOIs by a scientific advisory committee, a subset of applicants is invited to submit full proposals. The review process emphasizes innovation, scientific rigor, and the effective application of AI technologies to ovarian cancer research. Only a limited proportion of applicants advance beyond the LOI stage. The timeline for the grant cycle includes an LOI submission deadline of June 23, 2026, followed by notification of results in early August 2026. Invited full proposals are due in September 2026, with final funding decisions communicated in mid-November 2026. The anticipated project start date is February 1, 2027. The program operates on an annual cycle, with LOIs typically opening in the first quarter of each year. Throughout the grant period, recipients are required to submit annual progress and financial reports and are expected to produce peer-reviewed publications acknowledging the funding consortium. Applicants may direct technical questions regarding submission to the program’s designated email, and general inquiries about eligibility or program details can also be addressed through the same contact channel. The review process is confidential, and all reviewers are required to adhere to strict conflict-of-interest and confidentiality standards.

Focus on strong AI integration and clear relevance to ovarian cancer; demonstrate innovation scientific rigor and collaborative international team strength; ensure compliance with team composition and data sharing requirements