{"id":849,"date":"2021-06-03T00:00:00","date_gmt":"2021-06-03T00:00:00","guid":{"rendered":"https:\/\/www.lunit.io\/media-hub\/ai-based-analysis-of-cancer-tissue-predicts-response-to-immunotherapy-findings-to-be-presented-at-asco-2021\/"},"modified":"2021-06-03T00:00:00","modified_gmt":"2021-06-03T00:00:00","slug":"ai-based-analysis-of-cancer-tissue-predicts-response-to-immunotherapy-findings-to-be-presented-at-asco-2021","status":"publish","type":"media-hub","link":"https:\/\/www.lunit.io\/en\/media-hub\/ai-based-analysis-of-cancer-tissue-predicts-response-to-immunotherapy-findings-to-be-presented-at-asco-2021\/","title":{"rendered":"AI-based Analysis of Cancer Tissue Predicts Response to Immunotherapy--Findings to Be Presented at ASCO 2021"},"content":{"rendered":"<ul>\n<li>\n<p>Lunit to present four abstracts including one in a \u2018Poster Discussion Session\u2019<\/p>\n<\/li>\n<li>\n<p>AI-based tissue analysis platform \u2018Lunit SCOPE\u2019 to be launched within the second half of 2021: \u201cWe aim to make our AI the new standard for cancer treatment\u201d<\/p>\n<\/li>\n<\/ul>\n<p><\/p>\n<p><\/p>\n<p><\/p>\n<p>A new finding reveals that AI-based tissue analysis can show better prognosis for immunotherapy as well as find more patients eligible for the treatment, according to a medical AI startup, Lunit. The findings will be presented during the upcoming American Society of Clinical Oncology(ASCO) Annual meeting 2021. The company is to present four poster presentations, including one in a \u201cPoster Discussion Session\u201d.<\/p>\n<p><\/p>\n<p><\/p>\n<p>The presentations feature Lunit SCOPE, an AI software that analyzes tissue slide images, developed by Lunit. One finding states that Lunit SCOPE IO\u2014one of Lunit SCOPE product lines\u2014can be used as a new biomarker for the treatment of multiple cancer types. The software analyzes tumor-infiltrating lymphocytes(TIL) in cancer patients\u2019 tissue slides, assigning a score to each criterion. Upon validation with real-world data, the results showed that the higher the score, the better the response to immune checkpoint inhibitor (ICI) treatment, a subtype of immunotherapy.<\/p>\n<p><\/p>\n<p><\/p>\n<p>TIL is known as a potential tumor agnostic biomarker for ICI therapy. Lunit has been validating the clinical application of Lunit SCOPE IO for predicting ICI treatment outcomes in advanced lung cancer. This study expanded the clinical application of Lunit SCOPE IO across multiple cancer types. The study was verified by more than 1,000 real-world patient data of 9 cancer types, which were collected from major institutions including Stanford University Medical Center.<\/p>\n<p><\/p>\n<p><\/p>\n<p>\u201cWith multiple researches and long-term studies, we have been validating the effectiveness of an AI-based tissue analysis platform called \u2018Lunit SCOPE\u2019 that can help predict a cancer patient\u2019s response to immunotherapy,\u201d said Chan-young Ock, Chief Medical Officer of Lunit.<\/p>\n<p><\/p>\n<p><\/p>\n<p><\/p><figcaption>\n<p><img decoding=\"async\" src=\"\/en\/wp-content\/uploads\/EDITOR\/ce303dd6-8280-4af8-92bb-bf5084505ada.jpg#1088\">\u25b2 Online demo of Lunit SCOPE IO, analyzing the tissue slide image<\/p>\n<p><\/p>\n<\/figcaption><p><\/p>\n<p><\/p>\n<p><\/p>\n<p>Lunit will also present a study on Lunit SCOPE PD-L1. AI analysis of PD-L1 expression can generate objective quantification, which can lead to accurately finding subjects for ICI therapy among non-small cell lung cancer (NSCLC) patients.<\/p>\n<p><\/p>\n<p><\/p>\n<p>\u201cCurrently, pathologists interpret tissue slides through the naked eye. They assess PD-L1 expression level, which is the current standard for clinical application, but there are limitations. With the help of Lunit SCOPE PD-L1, which was trained with data including PD-L1 expression results of 380,000 cancer cells, we are able to find more patients who would respond to ICI therapy, 50% more, according to our study,\u201d said Ock.<\/p><figcaption>\n<p><\/p>\n<p><\/p>\n<p><img decoding=\"async\" src=\"\/en\/wp-content\/uploads\/EDITOR\/bdf76551-fc4f-42ac-8271-3f440ba060d3.jpg#1087\">\u25b2 Online demo of Lunit SCOPE PD-L1, analyzing the tissue slide image<\/p>\n<p><\/p>\n<\/figcaption><p>Lunit also announced that one of its abstracts about assessment of breast cancer risk has been selected for the ASCO 2021 \u2018Poster Discussion Session\u2019. Around 20% among all poster presentations are selected for this session, through strict review by the ASCO committee.<\/p>\n<p><\/p>\n<p><\/p>\n<p>According to this study, unique parenchymal pattern with future breast cancer risk among breast cancer patients was identified by AI. Among breast cancer patients who developed cancer on one of the breasts, images from the other \u2018normal\u2019 side were collected and labeled as \u2018high risk\u2019. After training the AI with this dataset, the algorithm was validated on more than 4,000 external cases. The results showed that Lunit\u2019s AI distinguished between high-risk and normal tissue with high accuracy, showing potential to be used as an independent biomarker to select high-risk populations based on mammography alone.<\/p>\n<p><\/p>\n<p><\/p><figcaption>\n<p><img decoding=\"async\" src=\"\/en\/wp-content\/uploads\/EDITOR\/7c9c5174-1cfa-4f85-87d6-14b4b3e3c779.jpg#1063\">\u25b2 Lunit is making a poster presentation at ASCO 2019<\/p>\n<\/figcaption><p><\/p>\n<p><\/p>\n<p><\/p>\n<p>\u201cThrough continuous research, Lunit has been presenting groundbreaking findings at ASCO since 2019,\u201d said Brandon Suh, CEO of Lunit. \u201cIt is considered a remarkable achievement for a medical AI startup to present four abstracts at such a renowned global medical conference. We are now focusing on the next stage, going beyond academic research to productization of our AI softwares to be used in actual cancer research, and eventually, clinical practice. We are planning to formally launch Lunit SCOPE products this year, taking steps on setting our AI as the new standard of cancer treatment.\u201d<\/p>\n<p><\/p>\n<p><\/p>\n<p>Marking its 57th anniversary, ASCO 2021 will be held online from June 4 to 8 due to COVID-19. More than 45,000 medical professionals from over 150 countries worldwide take part in the meeting to share the latest R&amp;D achievements and insights related to cancer treatment.<\/p>\n<p><\/p>\n<p><\/p>\n<p><strong>Lunit Abstract Information at ASCO 2021<\/strong><\/p>\n<\/p>\n<p><a href=\"https:\/\/meetinglibrary.asco.org\/record\/196064\/abstract\" target=\"_blank\"><u>Abstract #2607<\/u><\/a><\/p>\n<p><\/p>\n<p>Title: Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.<\/p>\n<p><\/p>\n<p>Session Title: Developmental Therapeutics\u2014Immunotherapy<\/p>\n<p><\/p>\n<p>Session Type: Poster Session<\/p>\n<p><\/p>\n<p>Online Demo: <a href=\"http:\/\/demo.scope.lunit.io\/io\" target=\"_blank\"><u>demo.scope.lunit.io\/io<\/u><\/a><\/p>\n<p><\/p>\n<p><\/p>\n<p><\/p>\n<p><\/p>\n<p><a href=\"https:\/\/meetinglibrary.asco.org\/record\/200590\/abstract\" target=\"_blank\"><u>Abstract #9026<\/u><\/a><\/p>\n<p><\/p>\n<p>Title: Clinical performance of artificial intelligence-powered annotation of tumor cell PD-L1 expression for treatment of immune-checkpoint inhibitor (ICI) in advanced non-small cell lung cancer (NSCLC).<\/p>\n<p><\/p>\n<p>Session Title: Lung Cancer\u2014Non-Small Cell Metastatic<\/p>\n<p><\/p>\n<p>Session Type: Poster Session<\/p>\n<p><\/p>\n<p>Online Demo: <a href=\"https:\/\/demo.scope.lunit.io\/pdl1\" target=\"_blank\"><u>demo.scope.lunit.io\/pdl1<\/u><\/a><\/p>\n<p><\/p>\n<p><\/p>\n<p><\/p>\n<p><a href=\"https:\/\/meetinglibrary.asco.org\/record\/200167\/abstract\" target=\"_blank\"><u>Abstract #1568<\/u><\/a><\/p>\n<p><\/p>\n<p>Title: AI-based imaging biomarker in mammography for prediction of tumor invasiveness.<\/p>\n<p><\/p>\n<p>Session Title: Care Delivery and Regulatory Policy<\/p>\n<p><\/p>\n<p>Session Type: Poster Session<\/p>\n<p><\/p>\n<p><\/p>\n<p><\/p>\n<p><a href=\"https:\/\/meetinglibrary.asco.org\/record\/196534\/abstract\" target=\"_blank\"><u>Abstract #10519<\/u><\/a><\/p>\n<p><\/p>\n<p>Title: Development of AI-powered imaging biomarker for breast cancer risk assessment on the basis of mammography alone.<\/p>\n<p><\/p>\n<p>Session Title: Prevention, Risk Reduction, and Hereditary Cancer<\/p>\n<p><\/p>\n<p>Session Type: Poster Discussion Session<\/p>\n<p><\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"template":"","media-hub-type":[35],"class_list":["post-849","media-hub","type-media-hub","status-publish","hentry","media-hub-type-precision-oncology"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - 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