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Inka Health Co-Founders Publish New Study Advancing Real-World Applicability of Lung Cancer Clinical Trial Outcomes

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Onco-Innovations Limited announced that co-founders of its subsidiary Inka Health Corp. published a study examining the applicability of lung cancer clinical trial outcomes to real-world populations. The study, titled 'Global Transportability of Clinical Trial Outcomes to Real-World Lung Cancer Populations,' demonstrated strong predictive performance with less than 1% variation in matching real-world outcomes over 30 months. The research supports the development of SynoGraph, Inka Health's causal AI platform, which aims to enhance drug development through real-world analytics. The study's methodology focuses on optimizing trial design and defining relevant populations to reduce development pipeline risks.
Onco-Innovations Limited ha annunciato che i co-fondatori della sua controllata Inka Health Corp. hanno pubblicato uno studio che analizza l'applicabilità dei risultati degli studi clinici sul cancro ai polmoni alle popolazioni reali. Lo studio, intitolato "Trasportabilità Globale dei Risultati degli Studi Clinici alle Popolazioni Reali con Cancro ai Polmoni", ha dimostrato un'elevata capacità predittiva con una variazione inferiore all'1% nel confronto con i risultati reali in un arco di 30 mesi. La ricerca supporta lo sviluppo di SynoGraph, la piattaforma di intelligenza artificiale causale di Inka Health, che mira a migliorare lo sviluppo dei farmaci tramite analisi basate su dati reali. La metodologia dello studio si concentra sull'ottimizzazione del disegno degli studi clinici e sulla definizione delle popolazioni rilevanti per ridurre i rischi nella pipeline di sviluppo.
Onco-Innovations Limited anunció que los cofundadores de su subsidiaria Inka Health Corp. publicaron un estudio que examina la aplicabilidad de los resultados de ensayos clínicos de cáncer de pulmón a poblaciones del mundo real. El estudio, titulado "Transportabilidad Global de los Resultados de Ensayos Clínicos a Poblaciones Reales con Cáncer de Pulmón", demostró un alto desempeño predictivo con menos del 1% de variación al comparar con resultados reales durante 30 meses. La investigación respalda el desarrollo de SynoGraph, la plataforma de IA causal de Inka Health, que busca mejorar el desarrollo de medicamentos mediante análisis basados en datos reales. La metodología del estudio se enfoca en optimizar el diseño de los ensayos y definir poblaciones relevantes para reducir riesgos en la cadena de desarrollo.
Onco-Innovations Limited은 자회사인 Inka Health Corp.의 공동 창립자들이 폐암 임상시험 결과를 실제 환자 집단에 적용 가능성을 검토한 연구를 발표했다고 밝혔습니다. "임상시험 결과의 실제 폐암 환자 집단에 대한 글로벌 전이 가능성"이라는 제목의 이 연구는 30개월 동안 실제 결과와의 일치율이 1% 미만의 변동으로 높은 예측 성능을 보였습니다. 이 연구는 Inka Health의 인과 AI 플랫폼인 SynoGraph 개발을 지원하며, 실제 데이터를 활용한 분석을 통해 신약 개발을 향상시키는 것을 목표로 합니다. 연구 방법론은 임상시험 설계 최적화와 관련 환자 집단 정의에 중점을 두어 개발 위험을 줄이는 데 기여합니다.
Onco-Innovations Limited a annoncé que les cofondateurs de sa filiale Inka Health Corp. ont publié une étude examinant l'applicabilité des résultats des essais cliniques sur le cancer du poumon aux populations réelles. L'étude, intitulée « Transportabilité globale des résultats des essais cliniques aux populations réelles atteintes de cancer du poumon », a démontré une performance prédictive solide avec une variation inférieure à 1 % lors de la correspondance avec les résultats réels sur 30 mois. Cette recherche soutient le développement de SynoGraph, la plateforme d'IA causale d'Inka Health, qui vise à améliorer le développement des médicaments grâce à l'analyse des données réelles. La méthodologie de l'étude se concentre sur l'optimisation de la conception des essais et la définition des populations pertinentes afin de réduire les risques dans le pipeline de développement.
Onco-Innovations Limited gab bekannt, dass die Mitbegründer seiner Tochtergesellschaft Inka Health Corp. eine Studie veröffentlicht haben, die die Anwendbarkeit von Ergebnissen klinischer Studien zu Lungenkrebs auf reale Populationen untersucht. Die Studie mit dem Titel „Globale Übertragbarkeit von Ergebnissen klinischer Studien auf reale Lungenkrebspopulationen“ zeigte eine starke Vorhersageleistung mit weniger als 1 % Abweichung bei der Übereinstimmung mit realen Ergebnissen über einen Zeitraum von 30 Monaten. Die Forschung unterstützt die Entwicklung von SynoGraph, der kausalen KI-Plattform von Inka Health, die darauf abzielt, die Arzneimittelentwicklung durch Analysen realer Daten zu verbessern. Die Methodik der Studie konzentriert sich auf die Optimierung des Studiendesigns und die Definition relevanter Populationen, um Risiken in der Entwicklungspipeline zu reduzieren.
Positive
  • Study demonstrated strong predictive performance with less than 1% variation in matching real-world outcomes
  • Research supports development of SynoGraph, a next-generation causal AI platform for drug development
  • Methods can help de-risk development pipelines through advanced trial design optimization
Negative
  • None.

VANCOUVER, BC / ACCESS Newswire / June 20, 2025 / Onco-Innovations Limited(CBOE CA:ONCO)(OTCQB:ONNVF)(Frankfurt:W1H,WKN:A3EKSZ) ("Onco" or the "Company") is pleased to announce that the Co-Founders of its wholly-owned subsidiary, Inka Health Corp. ("Inka Health"), have authored a significant new study titled Global Transportability of Clinical Trial Outcomes to Real-World Lung Cancer Populations: A Case Study using Lung-MAP S1400I1 (the "Study"), published in medRxiv in June 2025. The Study examines a key challenge in global cancer research by exploring how clinical trial results can be made more applicable to the diverse patient populations treated in routine clinical practice across different countries and healthcare systems. In this case, the approach demonstrated strong predictive performance, matching real-world outcomes within less than one percent over a 30-month period.2

Practical Implications and Strategic Value of the Study:

By simulating patient outcomes in advance to optimize trial design and define more relevant populations, these methods can de-risk development pipelines. These approaches directly inform SynoGraph, Inka Health's next-generation causal AI platform, which is designed to support faster, more transparent, and globally applicable drug development through advanced real-world analytics.

About the Study:

The Study presents a novel approach to improving the global applicability of clinical trial outcomes by assessing how well results from controlled trials translate to real-world patient populations. The research specifically examined whether findings from Lung-MAP S1400I, a leading randomized clinical trial for advanced non-small cell lung cancer (NSCLC), could accurately predict outcomes for patients receiving routine care in the United States, Germany, and France.

Clinical trials often have strict eligibility criteria, meaning many patients seen in daily practice would not qualify to participate. This can limit the ability to apply trial results to broader, more diverse patient populations. In this Study, the researchers used advanced modeling techniques and external clinical knowledge to bridge the gap between trial participants and real-world patients-including those typically excluded from trials due to age, comorbidities3, or other factors.

The results demonstrated meaningful progress in aligning clinical trial findings with real-world outcomes. When adjusting only for measured clinical factors, the alignment between trial and real-world results improved but remained incomplete. Incorporating additional external knowledge about patient groups excluded from the original trial further enhanced the model, resulting in predicted outcomes that closely mirrored actual survival observed among real-world patients in the United States, Germany, and France, with an average discrepancy of just 0.27 months (8.2 days) over a 30-month period. In other words, the model was able to match real-world outcomes with an error of less than one percent over the full timeframe, underscoring its potential to improve the relevance of trial findings for everyday clinical practice.

"This work represents a significant step forward in making clinical trial results more relevant to real-world cancer care globally. By bringing in external data and expert knowledge, we can better account for the diversity of patients who receive cancer treatments every day, helping to improve clinical decision-making, informing regulatory approvals, and ultimately expanding patient access to innovative therapies," said Paul Arora, Co-Founder of Inka Health.

The ability to robustly translate clinical trial results to diverse real-world populations is increasingly critical as regulators, payers, and clinicians seek evidence that reflects actual patient outcomes. Methodologies such as those demonstrated in this Study offer a scalable, scientifically rigorous path toward this goal especially in cancers like NSCLC where patient populations are highly heterogeneous.

Among the Study's notable co-authors is Dr. Vivek Subbiah, an oncologist and leader in early-phase drug development. Dr. Subbiah currently serves as Chief of Early-Phase Drug Development at the Sarah Cannon Research Institute, where he oversees one of the largest early oncology clinical trial networks globally.4 He has served as principal investigator on more than 100 Phase I and Phase II clinical trials and has played a pivotal role in several tissue-agnostic drug approvals, including therapies targeting BRAF5 and RET6 genetic alterations7. His work has contributed directly to regulatory approvals by both the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA).8 Dr. Subbiah has authored over 400 peer-reviewed publications in leading journals such as The New England Journal of Medicine (NEJM), Nature Medicine, and JAMA Oncology.

"The ability to model outcomes for patient groups who wouldn't typically be included in clinical trials is not just a technical achievement-it's a clinical and strategic one. It opens the door to faster trial design, smarter expansion decisions, and better evidence for patients who are often overlooked. These kinds of tools will be essential as we push toward more globally inclusive and data-driven drug development," said Dr. Subbiah.

About Inka Health

Inka Health is an AI-driven analytics company revolutionizing oncology research and drug development through advanced causal AI. Its proprietary platform, SynoGraph, leverages AI-powered causal inference to identify which cancer patients are most likely to respond to specific treatments, advancing precision medicine. By integrating diverse multimodal medical data-including genomics, transcriptomics, and proteomics-SynoGraph uncovers hidden insights that can optimize treatment decisions and clinical trial design. With this cutting-edge technology, Inka Health aims to help pharmaceutical companies accelerate drug development, reduce trial failures, and bring life-saving therapies to market faster.

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 pursue the prevention and treatment of cancer through pioneering research and innovative solutions. The company has secured an exclusive worldwide license to patented technology that targets solid tumours.

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
investors@oncoinnovations.com

Forward-Looking Statements Caution. This news release contains forward-looking statements, including in relation to the prospects of the Company, 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. 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 https://doi.org/10.1101/2025.05.30.25328679

2 https://doi.org/10.1101/2025.05.30.25328679

3 Comorbidities refer to additional medical conditions or diseases that a patient may have alongside their primary illness. In the context of cancer, common comorbidities might include conditions such as diabetes, heart disease, or chronic respiratory illnesses, which can affect treatment choices and outcomes. (see https://my.clevelandclinic.org/health/articles/comorbidities for more)

4 https://sarahcannon.com/about/newsroom/vivek-subbiah-md-joins-scri-to-advance-early-phase-clinical-research?

5 BRAF is a gene that, when mutated, can drive cancer growth. Targeted therapies for BRAF mutations are approved for several cancers, including melanoma and lung cancer. (see https://www.cancer.gov/publications/dictionaries/cancer-terms/def/braf-gene for more)

6 RET is a gene involved in cell signaling. Abnormal RET gene changes can lead to cancer, and targeted RET inhibitors have been approved for cancers such as lung and thyroid cancer. (See https://www.cancer.gov/news-events/cancer-currents-blog/2023/selpercatinib-ret-lung-medullary-thyroid#:~:text=Selpercatinib%20is%20approved%20for%20treating,proteins%20involving%20parts%20of%20RET. for more)

7 https://oncodaily.com/drugs/45235?

8 https://www.nursingcenter.com/journalarticle?Article_ID=6696238&Issue_ID=6696154&Journal_ID=401957&

SOURCE: Onco-Innovations Limited



View the original press release on ACCESS Newswire

FAQ

What is the significance of Inka Health's new lung cancer study published in June 2025?

The study demonstrates how clinical trial results can be made more applicable to diverse patient populations, showing less than 1% variation in matching real-world outcomes over 30 months

How does the study benefit Onco-Innovations (ONNVF) drug development process?

The study's methods help de-risk development pipelines by simulating patient outcomes and optimizing trial design, supporting their SynoGraph AI platform for faster drug development

What is SynoGraph and how does it relate to Inka Health's research?

SynoGraph is Inka Health's causal AI platform designed to support faster and more transparent drug development through advanced real-world analytics

What was the accuracy rate of the predictive performance in the Lung-MAP S1400I study?

The study's approach matched real-world outcomes within less than one percent over a 30-month period
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