Prospects Fund
Prospects Oncology Fund
FACIT’s Prospects Fund is designed to support early stage proof-of-concept (POC) studies within Ontario academic institutions and start-ups that fit with FACIT’s Ontario First Investment Strategy and have the potential to act as deal flow for the Compass Rose Fund. Prospects funding ranges between $50,000 and $200,000.
Funding is governed by a research contract which grants certain rights to FACIT. FACIT receives no financial consideration on Prospects awards of $50,000 or less (***new limit as of September 2019***). On all other awards, FACIT receives an option to make an investment at the Compass Rose level and act as the agent for commercialization, if mutually agreed. If the option is exercised, funding received from the Prospects Fund will be credited towards FACIT's Compass Rose investment.
How to apply:
The Prospects Fund is accepting pre-submission forms twice yearly on the following dates:
- March 31
- September 30
The pre-submission form can be downloaded here.
Late applications will not be considered.
Selected applicants will then be invited to prepare a Prospects funding application which is subject to due diligence by FACIT.
Select Prospects Funded Projects
Prospects Fund (Other)
Hand-held device for detecting tumour margins during lumpectomies
Multi-Magnetics is developing a hand-held device that uses photoacoustic imaging to detect tumour margins and residual disease in the surgical cavity during breast-conserving (lumpectomy) surgery.
Small-molecule inhibitors that target cancer cell mitochondria
Development of novel small-molecule inhibitors that target cancer cell mitochondria, a fuel source that many cancer cells rely on during chemotherapy.
Scaling clinical expertise with AI to automate and improve the delivery of cancer care
Bridge7 uses AI to automate & improve the efficiency, consistency & quality of delivering cancer care.
Modeling software to create synthetic data based on real clinical datasets
Replica Analytics is developing modeling software to create synthetic data based on real clinical datasets.
