Star Metro - Onco-Innovations' Inka Health Innovative AI-Driven Oncology Study Paves the Way for New Research

The study, entitled, "External Control Arm with Synthetic Real-world Data for Comparative Oncology using Single Trial Arm Evidence (ECLIPSE): A Case Study using Lung-MAP S1400I" is led by Dr. Winson Cheung, Medical Advisor at Inka Health and Professor of Medicine at the University of Calgary, and brought together an esteemed team of oncology experts, including Inka Health co-founders Dr. Paul Arora and Dr. Alind Gupta, along with a consortium of world-renowned cancer researchers and private sector partners (Subsalt and Quantify Health). This exciting initiative seeks to develop synthetic patient cohorts using AI technology, a core element of digital twin technology, to address gaps in oncology research and accelerate clinical trial design by quickly generating comparator arms for trials. The Company believes that this is particularly critical in the rare cancer setting where randomizing patients to control arms (comparison groups without the new treatment)² is often infeasible. Ultimately, this approach aims to improve the pace and effectiveness of cancer treatments.

This study, led by Inka Health, has the potential to impact not only Onco-Innovation's cancer research but also the broader healthcare landscape by providing a scalable, data-driven solution to the challenges of studying rare and hard-to-treat cancers. As part of this ongoing initiative, Inka is working to expand its proprietary AI-driven platform, SynoGraph, which enhances patient stratification, improves clinical trial efficiency, and advances precision oncology solutions. By incorporating synthetic real-world data, SynoGraph aims to offer the pharmaceutical and biotech industries a powerful tool to speed up drug development and regulatory processes.

"The ability to create synthetic patient models using AI is an exciting milestone for oncology research. Traditional data limitations have long hindered progress, especially for rare cancers where patient data is scarce. With this technology, we can simulate diverse patient populations, with the potential to improve how clinical trials are designed," said Paul Arora, CEO of Inka Health.

"AI-driven synthetic patient models represent a potentially major leap in oncology research. By generating high-fidelity digital replicas of real patients, we can overcome data gaps that have historically slowed advancements, particularly for rare cancers and underrepresented populations. This approach has the potential to enhance clinical trial design, optimize treatment strategies, and accelerate the development of life-saving therapies, " said Winson Cheung, Professor of Medicine at the University of Calgary and Medical Advisor at Inka Health.

About Onco-Innovations Limited

Onco-Innovations is a Canadian-based company dedicated to cancer research and treatment, specializing in oncology. Onco's mission is to prevent and cure cancer through pioneering research and innovative solutions. The company has secured an exclusive worldwide license to patented technology that targets solid tumours, setting new standards in cancer treatment. Onco's commitment to excellence and innovation drives it to develop advanced therapies that improve patient outcomes and offer hope in the fight against cancer.

ON BEHALF OF ONCO-INNOVATIONS LIMITED,

"Thomas O'Shaughnessy"
Chief Executive Officer

For more information, please contact:

Thomas O'Shaughnessy
Chief Executive Officer
Tel: + 1 888 261 8055
[email protected]

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Forward-Looking Statements Caution. This news release contains forward-looking statements relating to the further development, potential commercialization and benefits of SynoGraph, and the Company's other research initiatives, and the prospects of the Company, including its ability to safeguard its technologies, and the Company's business and plans generally, and other statements that are not historical facts. Forward-looking statements are often identified by terms such as "will", "may", "potential", "should", "anticipate", "expects" and similar expressions. All statements other than statements of historical fact, included in this release are forward-looking statements that involve risks and uncertainties. There can be no assurance that such statements will prove to be accurate and actual results and future events could differ materially from those anticipated in such statements. Important factors that could cause actual results to differ materially from the Company's expectations include the failure to further develop, prove out or commercialize SynoGraph or any of the Company's other technologies, the failure to receive a patent or to otherwise safeguard the Company's intellectual property rights, the failure to successfully complete further trials and studies, and other risks detailed from time to time in the filings made by the Company with securities regulators. The reader is cautioned that assumptions used in the preparation of any forward-looking information may prove to be incorrect. Events or circumstances may cause actual results to differ materially from those predicted, as a result of numerous known and unknown risks, uncertainties, and other factors, many of which are beyond the control of the Company. The reader is cautioned not to place undue reliance on any forward-looking information. Such information, although considered reasonable by management at the time of preparation, may prove to be incorrect and actual results may differ materially from those anticipated. Forward-looking statements contained in this news release are expressly qualified by this cautionary statement. The forward-looking statements contained in this news release are made as of the date of this news release and the Company will update or revise publicly any of the included forward-looking statements as expressly required by applicable law.

¹ External Control Arm with Synthetic Real-world Data for Comparative Oncology using Single Trial Arm Evidence (ECLIPSE): A Case Study using Lung-MAP S1400I | medRxiv - website: www.medrxiv.org/content/10.1101/2024.09.10.24313417v1

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P.Beaulieu--SMC