Redwood AI Corp. (CSE: AIRX) (OTCQB: RDWCF) (Frankfurt: Y0N) (WKN: A422EZ) Joins Canadian Research Consortium in Terry Fox-Funded Oncology AI Project

Disseminated on behalf of Redwood AI Corp.and may include paid advertising.

• The company has been named a co-applicant in a competitive Terry Fox Research Institute grant awarded to advance Onco-Innovations’ SynoGraph(TM) oncology platform.
• The project will investigate whether causal AI can improve predictions of first-in-human clinical outcomes using preclinical and real-world clinico-genomic data.
• Redwood AI will contribute proprietary data integration and physicochemical modelling methods to expand SynoGraph’s predictive capabilities.
• The grant supports a project with an estimated budget of $3.5 million and reimburses eligible costs up to 25% of that amount.
• Academic partners will provide clinico-genomic and imaging data for research using federated learning, which is intended to support analysis while protecting data privacy.

Redwood AI (CSE: AIRX) (OTCQB: RDWCF) (Frankfurt: Y0N, WKN: A422EZ), developer of an AI-powered platform for real-world applications across multiple critical industries, is joining a Canadian research collaboration backed by the Terry Fox Research Institute, contributing its data integration and chemical modelling expertise to the development of SynoGraph(TM), an artificial intelligence platform being developed by Onco-Innovations Limited (CBOE CA: ONCO) (OTCQB: ONNVF) (Frankfurt: W1H, WKN: A3EKSZ) for oncology research.

A September 22 announcement names Onco as lead applicant, with Redwood AI, the Michael Smith Genome Sciences Centre and the Centre de recherche du CHU de Québec-Université Laval as co-applicants. The project, titled “Causal AI to Predict First-in-Human Clinical Outcomes from Preclinical and Real-World Clinico-Genomic Data,” will explore how AI methods can help researchers estimate clinical outcomes before therapies enter human trials (https://ibn.fm/pdO4u).

The Digital Health Innovation Fund award is structured as a reimbursement-based grant covering up to 25% of an estimated $3.5 million project budget. Each co-applicant is an individual recipient under the grant, with participation governed by contribution agreements. The announcement does not specify the amount allocated to Redwood AI or the timing of reimbursements.

The project adds a life-sciences application to Redwood AI, which also develops AI and cybersecurity technologies for defense and public safety. The company’s stated chemistry platform is designed to support molecule design, chemical synthesis planning and analysis of complex chemical data.

Under the collaboration, Redwood AI will provide proprietary methods for data integration, feature engineering and physicochemical property evaluation. These capabilities are intended to complement Onco’s work in causal AI and federated pipeline development.

Onco is developing SynoGraph through its subsidiary Inka Health, while Redwood AI is contributing tools focused on chemical and data modelling. The academic institutions will provide clinico-genomic and imaging data to support the research.

A key component is federated learning, an approach that allows participating institutions to train or evaluate models across distributed datasets without necessarily pooling sensitive patient-level information in one central repository. The project aims to combine this approach with causal AI, which seeks to distinguish relationships that may be predictive from those that may reflect underlying causes.

The intended application is to improve predictions of how investigational therapies may perform in people, using evidence gathered before clinical testing alongside real-world clinical and genomic information. Such predictions could inform decisions about which candidates warrant further study, although the grant announcement does not report validated accuracy measures or clinical outcomes from SynoGraph.

The research also reflects a broader challenge in drug development: preclinical findings do not always translate into successful human trials. AI systems that integrate different types of biological and clinical evidence are being investigated as tools to support research decisions, but their value depends on data quality and performance in settings beyond the data used to build them.

Redwood AI said its contribution could potentially expand SynoGraph’s predictive core by applying its experience in chemical modelling to complex, multimodal data. The company’s chief executive, Louis Dron, described the collaboration as an opportunity to combine its technology with Onco’s causal-AI expertise.

“Redwood AI will contribute proprietary data integration and physicochemical modelling methods that can potentially expand the predictive core of SynoGraph. By combining our technology and experience with chemical modelling with Onco’s expertise in causal AI, this project aims to demonstrate how Canadian AI companies can work together with complex multimodal data sources to advance therapeutic innovation,” said Dron.

Onco’s own development program includes ONC010, a preclinical candidate based on a PNKP inhibitor and a licensed nanoparticle delivery system. The company says it is designed to exploit synthetic lethality in biomarker-selected tumors and potentially sensitize them to DNA-damaging therapies. Onco has indicated that it expects clinical translation in mid-2027; that timeline is separate from the SynoGraph grant project.

The Terry Fox Research Institute, established in 2007, funds collaborative cancer research across Canada. Its Digital Health Innovation Fund operates within the broader Digital Health and Discovery Platform, a pan-Canadian initiative supported by a $49 million allocation through Innovation, Science and Economic Development Canada.

The award provides a concrete example of Redwood AI applying its technology in a collaborative research setting, with a defined contribution and a project supported by a national cancer research organization. It does not, by itself, establish that SynoGraph can reliably predict clinical outcomes or that Redwood AI will receive material commercial revenue from the work. The project’s progress will depend on execution across the consortium, access to usable datasets and evidence that the combined methods deliver reproducible predictive improvements. 

For more information, visit the company’s website at www.RedwoodAI.com.

NOTE TO INVESTORS: The latest news and updates relating to RDWCF are available in the company’s newsroom at https://ibn.fm/RDWCF

About TechMediaWire

TechMediaWire (“TMW”) is a specialized communications platform with a focus on pioneering public and private companies driving the future of technology. It is one of 75+ brands within the Dynamic Brand Portfolio @ IBN that delivers: (1) access to a vast network of wire solutions via InvestorWire to efficiently and effectively reach a myriad of target markets, demographics and diverse industries; (2) article and editorial syndication to 5,000+ outlets; (3) enhanced press release enhancement to ensure maximum impact; (4) social media distribution via IBN to millions of social media followers; and (5) a full array of tailored corporate communications solutions. With broad reach and a seasoned team of contributing journalists and writers, TMW is uniquely positioned to best serve private and public companies that want to reach a wide audience of investors, influencers, consumers, journalists, and the general public. By cutting through the overload of information in today’s market, TMW brings its clients unparalleled recognition and brand awareness. TMW is where breaking news, insightful content and actionable information converge.

To receive SMS alerts from TechMediaWire, text “TECH” to 888-902-4192 (U.S. Mobile Phones Only)

For more information, please visit https://www.TechMediaWire.com

Please see full terms of use and disclaimers on the TechMediaWire website applicable to all content provided by TMW, wherever published or re-published: https://www.TechMediaWire.com/Disclaimer

TechMediaWire
Austin, Texas
www.TechMediaWire.com
512.354.7000 Office
Editor@TechMediaWire.com

TechMediaWire is powered by IBN