Lunit Enters into Research Collaboration to Explore the Use of AI to Improve the Effectiveness of Immunotherapy

–       Lunit to support MD Anderson researchers studying immune phenotype biomarkers for pembrolizumab treatment response

SEOUL, South Korea, Oct. 27, 2023 /PRNewswire/ — Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced a research collaboration with The University of Texas MD Anderson Cancer Center to analyze the use of Merck’s (known as MSD outside the US and Canada) Keytruda (pembrolizumab), a type of immunotherapy drug used in cancer treatment, in multiple cancer types. The project will use Lunit’s proprietary AI solution for tissue data analysis, Lunit SCOPE IO.


Lunit AI-powered TIL analyzer, Lunit SCOPE IO

Lunit will collaborate with Aung Naing, M.D., professor of Investigational Cancer Therapeutics at MD Anderson, as the lead Principal Investigator (PI) for this study. The goal of the study is to evaluate AI technology with the objective of improving patient data analysis and increasing the effective use of treatment for patients with different types of cancer. Lunit and Dr. Naing team plans to assess Merck’s clinical data by leveraging the capabilities of Lunit SCOPE IO, AI software that analyzes H&E-stained tissue slides to enable immune phenotyping and more.

“There is currently a lack of effective biomarkers for immunotherapy,” said Brandon Suh, CEO of Lunit. “Existing methods have limitations. The landscape is changing rapidly and state-of-art technologies such as AI are playing a significant role in enabling new biomarkers. We are particularly excited to be working with Dr. Naing to analyze biomarkers for pembrolizumab, one of the most important immunotherapy drugs.”

Lunit SCOPE IO has been trained with more than 500,000 H&E slides and more than 10 million cell annotations from over 150 pathologists. It detects cancer area, stroma, and tumor infiltrating lymphocytes (TIL), an important immune cell type that plays a key role in immunotherapy. Among other analyses, SCOPE IO generates an immune phenotype map based on TIL density within the tumor microenvironment, and supports analysis in more than 16 cancer types.

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About Lunit

Lunit is a deep learning-based medical AI company on a mission to conquer cancer. Our focus is on developing AI solutions for precision diagnostics and therapeutics, ensuring the right diagnosis, and treatment, at the right cost for each patient. Lunit is devoted to developing advanced medical image analytics and AI-based biomarkers via cutting-edge technology.

Founded in 2013, Lunit has been acknowledged around the world for its advanced, state-of-the-art technology and its application in medical images. As a medical AI company grounded on clinical evidence, the company’s findings are presented in major peer-reviewed journals, such as the Journal of Clinical Oncology and JAMA Network Open, and global conferences, including ASCO and AACR.

After receiving FDA clearance and the CE Mark, our flagship Lunit INSIGHT suite is clinically used in approximately 2,000+ hospitals and medical institutions across 40+ countries. Lunit is headquartered in Seoul, South Korea, with offices and representatives worldwide. For more information, please visit lunit.io

About Lunit SCOPE

Lunit SCOPE is a suite of AI-powered software that analyzes tissue slide images for digital pathology and AI biomarker development, aiming to optimize workflow and facilitate more accurate and predictive clinical data for clinicians and researchers.

Lunit SCOPE platform offers multiple AI-powered tissue analysis products and assays that can streamline digital pathology workflow and diagnostics and enhance the drug development process.

Lunit SCOPE IO analyzes the tumor microenvironment (TME) based on H&E analysis and provides AI-based predictive clinical outcome information. In addition, AI-driven Immunohistochemistry (IHC) slide analysis services are offered, through products such as Lunit SCOPE PD-L1, Lunit SCOPE HER2, Lunit SCOPE ER/PR, and others.