Onco-Innovations Limited (CBOE CA: ONCO) (OTCQB: ONNVF) (Frankfurt: W1H) (WKN: A3EKSZ) and Redwood AI (CSE: AIRX) (OTCQB: RDWCF), in collaboration with Canada’s Michael Smith Genome Sciences Centre and Centre de recherche du CHU de Québec-Université Laval, have been awarded a competitive Digital Health Innovation Fund grant administered by the Terry Fox Research Institute. The grant supports the development of the Onco SynoGraph AI-driven oncology platform, a project that aims to predict first-in-human clinical outcomes from preclinical studies and real-world clinico-genomic data.
The reimbursement-based grant covers up to 25% of an estimated $3.5 million project budget. The platform will leverage federated learning and causal AI, with each partner contributing distinct expertise. Redwood AI will provide proprietary data integration and physicochemical modelling methods, while the academic partners will supply clinico-genomic and imaging data. Onco-Innovations will contribute its causal AI methods and federated pipeline development.
This collaboration matters because it seeks to address a critical bottleneck in oncology drug development: the high failure rate of translating preclinical findings into successful human therapies. By using advanced AI to better predict clinical outcomes, the project could reduce the time and cost associated with bringing new cancer treatments to market, ultimately benefiting patients and the healthcare system.
For investors, the grant validates the potential of Onco-Innovations’ technology and its collaborative approach. The company holds an exclusive worldwide licence to patented technology directed to the therapeutic inhibition of PNKP, a novel clinical target in DNA damage response. Redwood AI, a technology company developing AI and cybersecurity solutions for defence, public safety, and life sciences, brings additional AI expertise to the table.
The project’s use of federated learning is particularly noteworthy, as it allows multiple institutions to train AI models on decentralized data without sharing sensitive patient information, addressing privacy concerns while enabling large-scale analysis. This approach could set a precedent for future AI-driven medical research collaborations.
As the project progresses, stakeholders can follow updates via Onco-Innovations’ newsroom at https://ibn.fm/ONNVF. The full press release is available at https://ibn.fm/ySIj9.
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