Onco-Innovations’ Inka Health Publishes Roche-Sponsored Study Advancing Real-World Oncology Research
Onco-Innovations' (ONNVF) subsidiary Inka Health has published a groundbreaking study in JAMA Network Open, sponsored by Roche, addressing methodological gaps in real-world oncology research. The study, titled 'Quantitative Bias Analysis for the Assessment of Bias in Comparisons between Synthetic Control Arms,' introduces Q-BASEL, a novel approach to improve the validity of clinical comparisons from real-world data.
The research, led by Inka Health co-founder Alind Gupta, conducted 15 treatment comparisons in advanced non-small cell lung cancer (aNSCLC) using real-world patient data. The study demonstrated that applying Quantitative Bias Analysis (QBA) significantly improved the alignment between real-world emulations and original randomized trial outcomes.
This methodology will be integrated into Inka's SynoGraph platform, enhancing support for pharmaceutical partners in optimizing real-world evidence strategies, particularly in scenarios where traditional randomized trials are not feasible.
La sussidiaria di Onco-Innovations (ONNVF), Inka Health, ha pubblicato uno studio innovativo su JAMA Network Open, sponsorizzato da Roche, che affronta le lacune metodologiche nella ricerca oncologica nel mondo reale. Lo studio, intitolato 'Analisi del Bias Quantitativo per la Valutazione del Bias nei Confronti tra Bracci di Controllo Sintetici,' introduce Q-BASEL, un nuovo approccio per migliorare la validità dei confronti clinici basati su dati reali.
La ricerca, guidata dal co-fondatore di Inka Health, Alind Gupta, ha condotto 15 confronti di trattamento in pazienti con cancro polmonare non a piccole cellule avanzato (aNSCLC) utilizzando dati reali. Lo studio ha dimostrato che l'applicazione dell'Analisi del Bias Quantitativo (QBA) ha migliorato significativamente l'allineamento tra le emulazioni del mondo reale e i risultati degli studi clinici randomizzati originali.
Questa metodologia sarà integrata nella piattaforma SynoGraph di Inka, migliorando il supporto per i partner farmaceutici nell'ottimizzazione delle strategie di evidenza del mondo reale, in particolare in scenari in cui gli studi clinici randomizzati tradizionali non sono fattibili.
La subsidiaria de Onco-Innovations (ONNVF), Inka Health, ha publicado un estudio innovador en JAMA Network Open, patrocinado por Roche, que aborda las lagunas metodológicas en la investigación oncológica del mundo real. El estudio, titulado 'Análisis de Sesgo Cuantitativo para la Evaluación del Sesgo en Comparaciones entre Brazos de Control Sintéticos,' introduce Q-BASEL, un nuevo enfoque para mejorar la validez de las comparaciones clínicas basadas en datos del mundo real.
La investigación, dirigida por el cofundador de Inka Health, Alind Gupta, realizó 15 comparaciones de tratamiento en cáncer de pulmón no microcítico avanzado (aNSCLC) utilizando datos de pacientes del mundo real. El estudio demostró que la aplicación del Análisis de Sesgo Cuantitativo (QBA) mejoró significativamente la alineación entre las emulaciones del mundo real y los resultados de los ensayos aleatorizados originales.
Esta metodología se integrará en la plataforma SynoGraph de Inka, mejorando el apoyo a los socios farmacéuticos en la optimización de estrategias de evidencia del mundo real, especialmente en escenarios donde los ensayos aleatorizados tradicionales no son viables.
온코-이노베이션스(ONNVF)의 자회사인 인카 헬스가 로슈의 후원을 받아 JAMA 네트워크 오픈에 혁신적인 연구를 발표했습니다. 이 연구는 실제 세계의 종양학 연구에서의 방법론적 격차를 다루고 있습니다. '합성 대조군 간 비교의 편향 평가를 위한 정량적 편향 분석'이라는 제목의 이 연구는 실제 데이터에서 임상 비교의 유효성을 개선하기 위한 새로운 접근 방식인 Q-BASEL을 소개합니다.
인카 헬스의 공동 창립자인 알린 굽타가 이끄는 이 연구는 실제 환자 데이터를 사용하여 진행성 비소세포 폐암(aNSCLC)에서 15개의 치료 비교를 수행했습니다. 연구 결과, 정량적 편향 분석(QBA)을 적용함으로써 실제 세계의 에뮬레이션과 원래의 무작위 시험 결과 간의 정렬이 크게 개선된 것으로 나타났습니다.
이 방법론은 인카의 SynoGraph 플랫폼에 통합되어, 전통적인 무작위 시험이 불가능한 상황에서 제약 파트너들이 실제 증거 전략을 최적화하는 데 도움을 줄 것입니다.
La filiale d'Onco-Innovations (ONNVF), Inka Health, a publié une étude révolutionnaire dans JAMA Network Open, sponsorisée par Roche, qui aborde les lacunes méthodologiques dans la recherche oncologique en monde réel. L'étude, intitulée 'Analyse de biais quantitatif pour l'évaluation des biais dans les comparaisons entre bras de contrôle synthétiques,' introduit Q-BASEL, une nouvelle approche visant à améliorer la validité des comparaisons cliniques à partir de données du monde réel.
La recherche, dirigée par Alind Gupta, co-fondateur d'Inka Health, a réalisé 15 comparaisons de traitement dans le cancer du poumon non à petites cellules avancé (aNSCLC) en utilisant des données de patients du monde réel. L'étude a montré que l'application de l'Analyse de Biais Quantitatif (QBA) a considérablement amélioré l'alignement entre les émulations du monde réel et les résultats des essais randomisés d'origine.
Cette méthodologie sera intégrée dans la plateforme SynoGraph d'Inka, améliorant le soutien aux partenaires pharmaceutiques dans l'optimisation des stratégies de preuves du monde réel, en particulier dans les scénarios où les essais randomisés traditionnels ne sont pas réalisables.
Die Tochtergesellschaft von Onco-Innovations (ONNVF), Inka Health, hat eine bahnbrechende Studie in JAMA Network Open veröffentlicht, die von Roche gesponsert wurde und sich mit methodischen Lücken in der Onkologie-Forschung der realen Welt beschäftigt. Die Studie mit dem Titel 'Quantitative Bias Analysis for the Assessment of Bias in Comparisons between Synthetic Control Arms' führt Q-BASEL ein, einen neuartigen Ansatz zur Verbesserung der Validität klinischer Vergleiche aus realen Daten.
Die Forschung, geleitet von Alind Gupta, einem Mitbegründer von Inka Health, führte 15 Behandlungsvergleiche bei fortgeschrittenem nicht-kleinzelligem Lungenkrebs (aNSCLC) unter Verwendung von Daten realer Patienten durch. Die Studie zeigte, dass die Anwendung der Quantitativen Bias-Analyse (QBA) die Übereinstimmung zwischen realen Emulationen und den Ergebnissen ursprünglicher randomisierter Studien erheblich verbesserte.
Diese Methodologie wird in die SynoGraph-Plattform von Inka integriert, um die Unterstützung für pharmazeutische Partner bei der Optimierung von Strategien für reale Evidenz zu verbessern, insbesondere in Szenarien, in denen traditionelle randomisierte Studien nicht durchführbar sind.
- Publication in prestigious JAMA Network Open demonstrates scientific credibility
- Strategic partnership with Roche, the fifth-largest pharmaceutical company globally
- Integration of Q-BASEL methodology into SynoGraph platform enhances commercial potential
- Addresses regulatory agencies' increasing acceptance of real-world evidence
- None.
VANCOUVER, BC / ACCESS Newswire / April 10, 2025 / Onco-Innovations Limited (CSE:ONCO)(OTCQB:ONNVF)(Frankfurt:W1H, WKN: A3EKSZ) ("Onco" or the "Company") is pleased to announce that its subsidiary, Inka Health Corp. ("Inka Health"), has published a significant and novel study titled Quantitative Bias Analysis for the Assessment of Bias in Comparisons between Synthetic Control Arms (the "Study") published in JAMA Network Open[1] in March 2025, addressing a critical methodological gap in real-world oncology research. The Study[2], sponsored by F. Hoffmann-La Roche (Roche), the fifth-largest pharmaceutical company in the world by revenue[3], presents a novel approach to improving the validity of clinical comparisons drawn from real-world data. Specifically, it provides a method to adjust for unseen differences between patient groups that can lead to misleading results when randomized trials[4] are not possible.
As regulatory bodies increasingly turn to real-world evidence in evaluating new treatments[5], the Study contributes a significant tool for addressing underlying bias in real-world data sources, helping ensure that treatment effects observed outside of traditional trials can be interpreted with greater scientific rigor and confidence.
The Study was led by Alind Gupta, co-founder of Inka Health, in collaboration with Roche and internationally recognized experts in medical research, including Harvard Professor Miguel Hernán[6]. This research builds on Inka Health's efforts to address real-world challenges in oncology trial design, particularly in settings where traditional randomized trials are not feasible. Q-BASEL applies Quantitative Bias Analysis (QBA) to external control arm[7] (ECA) studies, which compare single-arm trial results to outcomes derived from historical or real-world data. These types of studies are increasingly used when randomized controlled trials are not feasible, such as in advanced non-small cell lung cancer (aNSCLC).
The Q-BASEL study emulated 15 treatment comparisons in advanced non-small cell lung cancer (aNSCLC) by using real-world patient data to recreate experimental arms from previously conducted randomized trials. The research team applied Quantitative Bias Analysis (QBA) after adjusting for known baseline differences, using evidence from medical literature, clinical trial data, and expert input to account for unmeasured or mismeasured factors. The Study then compared the results from these real-world emulations to the original randomized trial outcomes. The findings showed that applying QBA meaningfully improved the alignment between the two, demonstrating its ability to reduce bias and enhance the reliability of external control arm analyses.
By incorporating external evidence from clinical trials, expert opinion, and published literature, the QBA approach adjusts for potential bias introduced by unmeasured or mismeasured variables. In simpler terms, it helps account for hidden differences between patient groups that could otherwise lead to misleading comparisons. The Study showed that this method substantially improves the alignment of real-world data with randomized trial outcomes, offering a more reliable foundation for clinical decision-making and regulatory assessment.
The application of QBA in this context is particularly relevant as regulatory agencies such as the U.S. Food and Drug Administration[8] (FDA), European Medicines Agency[9] (EMA), National Institute for Health and Care Excellence[10] (NICE), and Canada's Drug Agency [11] (CDA-AMC) continue to support the use of ECAs in evidence submissions. The methodology demonstrated in Q-BASEL offers a scalable solution with potential application across a broad range of therapeutic areas. Onco-Innovations and Inka Health intend to integrate this capability into Inka's SynoGraph platform, enhancing its ability to support pharmaceutical partners in optimizing real-world evidence strategies and advancing access to innovative treatments in settings where traditional trials remain challenging.
"By addressing a longstanding gap in the way we evaluate treatments using real-world data, this work brings us closer to making faster, evidence-based decisions in areas where patients often cannot wait for traditional trials. It also lays the foundation for how SynoGraph can support the next generation of real-world studies with greater methodological integrity. Integrating these tools into our platform enables us to help biopharma partners generate more credible evidence, streamline regulatory submissions, and expand access to innovative therapies in difficult-to-study cancer populations," said Alind Gupta, Co-founder of Inka Health.
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 helps 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 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
investors@oncoinnovations.com
The CSE and Information Service Provider have not reviewed and do not accept responsibility for the accuracy or adequacy of this release.
Forward-Looking Statements Caution. This news release contains forward-looking statements relating to the further development, potential commercialization and benefits of the Company's technologies, including 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 the Company's 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] JAMA Network Open is an international, peer-reviewed, open access, general medical journal that publishes research on clinical care, innovation in health care, health policy, and global health across all health disciplines and countries for clinicians, investigators, and policy makers. (see https://jamanetwork.com/journals/jamanetworkopen/pages/for-authors#fa-about for more information)
[2] Gupta A, Hsu G, Kent S, et al. Quantitative Bias Analysis for Single-Arm Trials With External Control Arms. JAMA Netw Open. 2025;8(3):e252152. doi:10.1001/jamanetworkopen.2025.2152
[3] https://www.proclinical.com/blogs/2024-7/who-are-the-top-10-pharma-companies-in-the-world-2024
[4] Randomized trials, also known as randomized controlled trials (RCTs), are a type of study where participants are randomly assigned to different groups to compare the effects of different treatments or interventions. This random assignment helps ensure that groups are similar, allowing for a more fair comparison of treatment effects (see https://pmc.ncbi.nlm.nih.gov/articles/PMC6235704/).
[5] The U.S. Food and Drug Administration's 2018 Real-World Evidence Framework explicitly outlines how RWE can be used to support regulatory decisions. The 21st Century Cures Act encourages the FDA to expand the use of RWE.(see https://www.fda.gov/media/120060/download for more information)
[6] Gupta A, Hsu G, Kent S, et al. Quantitative Bias Analysis for Single-Arm Trials With External Control Arms. JAMA Netw Open. 2025;8(3):e252152. doi:10.1001/jamanetworkopen.2025.2152
[7] In clinical trials, control arms are groups that receive either a placebo or standard treatment to compare against the experimental therapy.
[8] https://www.fda.gov/media/120060/download
[10] https://www.nice.org.uk/corporate/ecd9/resources/nice-realworld-evidence-framework-pdf-1124020816837
[11] https://www.cda-amc.ca/real-world-evidence-and-health-technology-assessment-past-present-and-future
SOURCE: Onco-Innovations Limited
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FAQ
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