Onco-Innovations' Inka Health Innovative AI-Driven Oncology Study Paves the Way for New Research
Onco-Innovations (OTCQB:ONNVF) subsidiary Inka Health has published a groundbreaking study protocol in medRxiv focusing on AI-generated synthetic patient models for oncology research. The study, titled 'ECLIPSE', leverages advanced machine learning to create synthetic patient data, particularly beneficial for rare cancer research where traditional patient data is scarce.
Led by Dr. Winson Cheung, Medical Advisor at Inka Health and Professor at the University of Calgary, alongside Inka Health co-founders Dr. Paul Arora and Dr. Alind Gupta, the research aims to develop synthetic patient cohorts using AI technology. The initiative utilizes Inka's proprietary AI platform, SynoGraph, to enhance patient stratification and improve clinical trial efficiency.
The technology focuses on generating comparator arms for trials, addressing a critical challenge in rare cancer research where randomizing patients to control groups is often unfeasible. This approach aims to accelerate drug development and regulatory processes in the pharmaceutical and biotech industries.
Onco-Innovations (OTCQB:ONNVF) ha pubblicato un protocollo di studio innovativo tramite la sua sussidiaria Inka Health su medRxiv, incentrato su modelli sintetici di pazienti generati dall'IA per la ricerca oncologica. Lo studio, intitolato 'ECLIPSE', sfrutta l'apprendimento automatico avanzato per creare dati sintetici di pazienti, particolarmente utili per la ricerca su tumori rari, dove i dati tradizionali sono scarsi.
Guidato dal Dr. Winson Cheung, consulente medico di Inka Health e professore all'Università di Calgary, insieme ai cofondatori di Inka Health, il Dr. Paul Arora e il Dr. Alind Gupta, la ricerca mira a sviluppare coorti di pazienti sintetici utilizzando la tecnologia IA. L'iniziativa utilizza la piattaforma proprietaria di IA di Inka, SynoGraph, per migliorare la stratificazione dei pazienti e aumentare l'efficienza delle sperimentazioni cliniche.
La tecnologia si concentra sulla generazione di bracci comparativi per le sperimentazioni, affrontando una sfida critica nella ricerca sui tumori rari, dove randomizzare i pazienti in gruppi di controllo è spesso impraticabile. Questo approccio mira ad accelerare lo sviluppo di farmaci e i processi regolatori nelle industrie farmaceutiche e biotecnologiche.
Onco-Innovations (OTCQB:ONNVF) ha publicado un protocolo de estudio innovador a través de su subsidiaria Inka Health en medRxiv, centrándose en modelos sintéticos de pacientes generados por IA para la investigación oncológica. El estudio, titulado 'ECLIPSE', aprovecha el aprendizaje automático avanzado para crear datos sintéticos de pacientes, particularmente beneficiosos para la investigación de cánceres raros, donde los datos tradicionales son escasos.
Dirigido por el Dr. Winson Cheung, asesor médico de Inka Health y profesor en la Universidad de Calgary, junto con los cofundadores de Inka Health, el Dr. Paul Arora y el Dr. Alind Gupta, la investigación tiene como objetivo desarrollar cohortes de pacientes sintéticos utilizando tecnología de IA. La iniciativa utiliza la plataforma de IA propietaria de Inka, SynoGraph, para mejorar la estratificación de pacientes y aumentar la eficiencia de los ensayos clínicos.
La tecnología se centra en generar brazos comparativos para los ensayos, abordando un desafío crítico en la investigación de cánceres raros, donde randomizar pacientes en grupos de control a menudo no es factible. Este enfoque tiene como objetivo acelerar el desarrollo de medicamentos y los procesos regulatorios en las industrias farmacéutica y biotecnológica.
Onco-Innovations (OTCQB:ONNVF)의 자회사 Inka Health가 의학 연구 플랫폼 medRxiv에 AI 생성 합성 환자 모델에 관한 혁신적인 연구 프로토콜을 발표했습니다. 'ECLIPSE'라는 제목의 이 연구는 희귀 암 연구에서 전통적인 환자 데이터가 부족한 경우에 특히 유용한 합성 환자 데이터를 생성하기 위해 고급 기계 학습을 활용합니다.
캘거리 대학교의 교수이자 Inka Health의 의료 고문인 Dr. Winson Cheung가 이끄는 이 연구는 Inka Health의 공동 창립자인 Dr. Paul Arora와 Dr. Alind Gupta와 함께 AI 기술을 사용하여 합성 환자 집단을 개발하는 것을 목표로 하고 있습니다. 이 이니셔티브는 Inka의 독점 AI 플랫폼인 SynoGraph를 활용하여 환자 분류를 개선하고 임상 시험의 효율성을 높입니다.
이 기술은 임상 시험을 위한 비교군을 생성하는 데 중점을 두어, 희귀 암 연구에서 환자를 대조군으로 무작위 배정하는 것이 종종 불가능한 중요한 문제를 해결합니다. 이 접근 방식은 제약 및 생명공학 산업에서 약물 개발 및 규제 프로세스를 가속화하는 것을 목표로 합니다.
Onco-Innovations (OTCQB:ONNVF) a publié un protocole d'étude révolutionnaire via sa filiale Inka Health sur medRxiv, axé sur des modèles de patients synthétiques générés par IA pour la recherche en oncologie. L'étude, intitulée 'ECLIPSE', tire parti de l'apprentissage automatique avancé pour créer des données de patients synthétiques, particulièrement bénéfiques pour la recherche sur les cancers rares, où les données traditionnelles sont rares.
Dirigée par le Dr. Winson Cheung, conseiller médical d'Inka Health et professeur à l'Université de Calgary, ainsi que par les cofondateurs d'Inka Health, le Dr. Paul Arora et le Dr. Alind Gupta, la recherche vise à développer des cohortes de patients synthétiques en utilisant la technologie IA. L'initiative utilise la plateforme IA propriétaire d'Inka, SynoGraph, pour améliorer la stratification des patients et accroître l'efficacité des essais cliniques.
La technologie se concentre sur la génération de bras comparatifs pour les essais, abordant un défi critique dans la recherche sur les cancers rares, où la randomisation des patients dans des groupes de contrôle est souvent impraticable. Cette approche vise à accélérer le développement de médicaments et les processus réglementaires dans les industries pharmaceutiques et biotechnologiques.
Onco-Innovations (OTCQB:ONNVF) hat über seine Tochtergesellschaft Inka Health ein bahnbrechendes Studienprotokoll in medRxiv veröffentlicht, das sich auf KI-generierte synthetische Patientenmodelle für die Onkologie-Forschung konzentriert. Die Studie mit dem Titel 'ECLIPSE' nutzt fortschrittliches maschinelles Lernen, um synthetische Patientendaten zu erstellen, die besonders vorteilhaft für die Forschung zu seltenen Krebserkrankungen sind, bei denen traditionelle Patientendaten rar sind.
Die Forschung wird von Dr. Winson Cheung, medizinischer Berater von Inka Health und Professor an der Universität Calgary, zusammen mit den Mitbegründern von Inka Health, Dr. Paul Arora und Dr. Alind Gupta, geleitet. Ziel der Forschung ist es, synthetische Patientenkohorten mithilfe von KI-Technologie zu entwickeln. Die Initiative nutzt Inkas proprietäre KI-Plattform SynoGraph, um die Patientensortierung zu verbessern und die Effizienz klinischer Studien zu steigern.
Die Technologie konzentriert sich auf die Generierung von Vergleichsgruppen für Studien und adressiert eine kritische Herausforderung in der Forschung zu seltenen Krebserkrankungen, bei der die Randomisierung von Patienten in Kontrollgruppen oft nicht möglich ist. Dieser Ansatz zielt darauf ab, die Arzneimittelentwicklung und die Regulierungsprozesse in der Pharma- und Biotechnologiebranche zu beschleunigen.
- Development of innovative AI platform SynoGraph for clinical trial optimization
- Strategic collaboration with renowned cancer researchers and private sector partners
- Potential to accelerate drug development and regulatory processes
- No immediate revenue generation mentioned
- Technology still in development phase with unproven commercial success
VANCOUVER, BC / ACCESS Newswire / February 27, 2025 / Onco-Innovations Limited (CSE:ONCO)(OTCQB:ONNVF)(Frankfurt:W1H,WKN: A3EKSZ) ("Onco" or the "Company") is pleased to provide information regarding its wholly-owned subsidiary, Inka Health ("Inka"), which has made significant strides in advancing AI-driven oncology research by leading a transformative study protocol1 published in medRxiv in September 2024, focused on AI-generated synthetic patient models. This innovative research aims to advance the study of oncology by creating synthetic patient data, thereby leveraging advanced machine learning techniques to overcome critical challenges, particularly in the study of rare cancers where traditional patient data is often unavailable or difficult to obtain.
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
investors@oncoinnovations.com
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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
2 In clinical trials, control arms are groups that receive either a placebo or standard treatment to compare against the experimental therapy.
SOURCE: Onco-Innovations Limited
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