Grand Challenge: Cancer Digital Intelligence (CDI): From AI Algorithm to Implementation

Request for Applications

Princess Margaret Cancer Centre Grand Challenges supports bold, innovative, and high impact projects across the spectrum of cancer care. At Princess Margaret (PM), we aspire to be a global leader in the application of digital intelligence to enable the best care possible for people affected by cancer. As part of the Cancer Digital Intelligence Program (CDI), the Princess Margaret Cancer Centre is pleased to open the call for applications for the 2025-2026 Grand Challenge: From AI Algorithm to Implementation.

Artificial Intelligence (AI) refers to the use of software systems and machines to perform tasks such as understanding natural language, recognizing patterns, solving problems, and learning from experience. In cancer care, AI can be used for discovery and clinical decision support or for:

• Data analysis and pattern recognition
• Real-time optimization
• Automation of routine tasks
• Efficiency enhancements
• Cancer detection and diagnosing
• Cancer treatment recommendations

However, without thoughtful development, there is a risk that AI systems may dis-serve the societies that created them by exacerbating existing health inequities that undermine compassionate care.

This opportunity is open to applicants from the University Health Network (UHN) across all cancer disciplines and scientists from the University of Waterloo. All applications must include at least one investigator from UHN. Projects should be bold with clearly defined milestones, a realistic endpoint, and clear impact achievable within a 12-month time-period and sustainable thereafter.

Projects must involve artificial intelligence or address risks adopting AI in Cancer Care and have a plan for implementation during the Grand Challenge period or independently afterwards. Preference will be given to applications that feature AI technologies which have already been developed, evaluated, and are ready for implementation.

Evaluation Criteria Considerations:

1. Explicitly addressing a “need” within the Cancer community:

• What is the “need” explicitly being addressed?
• What are the existing, AI and non-AI solutions available?
• How is your project addressing the “need”?
• How have users been involved in defining the “need”?
• Why are you the best group to address this “need”?
• How is this “need” related to inequity or compassionate care practices?

2. Responsible and Compassionate Care:

• Will this project improve equitable and compassionate care? If so, will it occur only within the PM patient population, or more broadly?
• What steps will be taken to understand equality of care in the population of interest? Or what inequalities are already known to exist?
• What steps will be taken to mitigate inequality of care, and improve compassionate care in the population of interest with your solution?
• Who will maintain and audit your solution after deployment?
• Will patients and users be consulted during the development of your solution?

3. Implementation

• What is the cost to adopt and maintain the solution?
• Do you have appropriate institutional approval for your AI solution rollout? What additional approvals, if any, will you need?
• What clinical systems will your AI solution need to integrate with?
• How do you plan to ensure easy adoption and uptake of your AI solution by clinical end users?
• How will you support the sustainability of your AI solutions?

Resource Allocation:

• Funding will be awarded in the form of resources equivalent of up to $250,000 provided by the CDI Program (project management, analysts, developers, data scientists, product, and service design) dedicated to support the execution of the proposed work.
• Resources will be assigned based on the project scope, resources requirements, timelines and could be subject to adjustments based on discussions with successful applicants.
• Resources to support the project will be limited to 12 months. Projects with a timeline not exceeding 12 months will be preferred.

Eligibility:

• Applicants from UHN and the University of Waterloo are eligible.
• An individual can be the principal applicant for only one proposal.
• At least one of the applicants must have a faculty appointment as a clinician or scientist at UHN.
• Applications across the full spectrum of clinical, translation, and basic research are eligible.
• Applications will be evaluated on their impact and contribution to the PM community, ease of implementation, scientific quality, alignment with the CDI priorities, ability for project deliverables to be completed in 12 months, and resource requirements.

Application:

• Full applications must be completed using the application form.
• A maximum of two (2) pages of figures can be appended to the application form.
• The project schedule and required resources should be justified and appended.
• References are not required.

How to Apply

Full applications are due on Friday, September 26th, 2025 at 5pm EST via email to pmcdi@uhn.ca. as a single PDF. Late applications will not be accepted.
The winner will be announced in late October 2025

More Information

Direct questions about funding opportunity details and eligibility to alejandro.berlin@rmp.uhn.ca, Medical Director, CDI or benjamin.haibe-kains@uhnresearch.ca, Scientific Director, CDI.

Direct questions about the application process to pmcdi@uhn.ca

Previous Grand Challenge winners:

2024-2025 Project Winners:

An AI-Driven Intraoperative Diagnostic Tool for Cancer Surgery

Dr. Scott Hopkins at the University of Waterloo, Dr. Arash Zarrine-Afsar at UHN, and their respective teams for their project.

Artificial Intelligence for Risk Stratification of Liver and Ovarian Lesions (LI-RADS and O-RADS MRI) from Radiology Reports

Dr. Rajesh Bhayana and his team at the Princess Margaret Cancer Centre for their project.

2023-2024 Project Winners:

Computational & Bench Scientist Ecosystem (CoBE)

CoBE is a web portal recommendation engine allowing scientists to rapidly find or contribute self-contained, fully reproducible software tools & bioinformatic pipelines that address the most pressing analytical needs for computational biology at the Princess Margaret Cancer Centre and UHN.

Scalable Integrated Radiation Therapy Autosegmentation and Decision-Support for Individualized Cancer Care (SIRTADICC)

The SIR TADICC project will provide new tools to safely automate the way doctors identify the areas that need radiation treatment for head-and-neck cancers and assist doctors in making high quality treatment decisions. These segmentation tools and decision supports will allow for rapid adjustments to patient radiation plans according to the tumor response or other factors.

2022-2023 Project Winner:

Clinical Trial Integrated Matching System (CTIMS)

CTIMS intoduces an innovative approach to harnessing a patient’s ‘digital fingerprint’ to pinpoint trials they may be eligible for. CTIMS offers a new trial match process that significantly minimizes the time and resources required to identify patients eligible for clinical trials.