Jun 3, 2021 — 4 min read
Lunit to present four abstracts including one in a ‘Poster Discussion Session’
AI-based tissue analysis platform ‘Lunit SCOPE’ to be launched within the second half of 2021: “We aim to make our AI the new standard for cancer treatment”
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 “Poster Discussion Session”.
The presentations feature Lunit SCOPE, an AI software that analyzes tissue slide images, developed by Lunit. One finding states that Lunit SCOPE IO—one of Lunit SCOPE product lines—can be used as a new biomarker for the treatment of multiple cancer types. The software analyzes tumor-infiltrating lymphocytes(TIL) in cancer patients’ 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.
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.
“With multiple researches and long-term studies, we have been validating the effectiveness of an AI-based tissue analysis platform called ‘Lunit SCOPE’ that can help predict a cancer patient’s response to immunotherapy,” said Chan-young Ock, Chief Medical Officer of Lunit.
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.
“Currently, 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,” said Ock.
Lunit also announced that one of its abstracts about assessment of breast cancer risk has been selected for the ASCO 2021 ‘Poster Discussion Session’. Around 20% among all poster presentations are selected for this session, through strict review by the ASCO committee.
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 ‘normal’ side were collected and labeled as ‘high risk’. After training the AI with this dataset, the algorithm was validated on more than 4,000 external cases. The results showed that Lunit’s 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.
“Through continuous research, Lunit has been presenting groundbreaking findings at ASCO since 2019,” said Brandon Suh, CEO of Lunit. “It 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.”
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&D achievements and insights related to cancer treatment.
Lunit Abstract Information at ASCO 2021
Title: Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.
Session Title: Developmental Therapeutics—Immunotherapy
Session Type: Poster Session
Online Demo: demo.scope.lunit.io/io
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).
Session Title: Lung Cancer—Non-Small Cell Metastatic
Session Type: Poster Session
Online Demo: demo.scope.lunit.io/pdl1
Title: AI-based imaging biomarker in mammography for prediction of tumor invasiveness.
Session Title: Care Delivery and Regulatory Policy
Session Type: Poster Session
Title: Development of AI-powered imaging biomarker for breast cancer risk assessment on the basis of mammography alone.
Session Title: Prevention, Risk Reduction, and Hereditary Cancer
Session Type: Poster Discussion Session
Lunit wins Tumor Proliferation Assessment Challenge (TUPAC) 2016
Lunit to unveil data-driven imaging biomarker at RSNA 2016
Lunit to showcase AI-powered products at USCAP 2017
Lunit INSIGHT: The First-ever, Real-time Imaging AI Analytics on the Web
Uncertainty and Deep Learning
Lunit Returns to RSNA with Real-time Imaging Platform, Featuring Cloud-based A
Lunit Unveils “Lunit INSIGHT,” A New Real-time Imaging AI Platform on the Web at RSNA 2017
Lunit INSIGHT: Q&A with Brandon B. Suh, Chief Medical Officer at Lunit
Media Advisory: Lunit at RSNA 2018
Lunit Opens “Lunit INSIGHT for Mammography” for Public Access
Lunit Brings its Newest AI Solution for Mammography to RSNA 2018
Lunit to Introduce Medical AI Solutions at GTC 2019
Lunit to Present Abstracts on AI-powered Precision Pathology at 2019 AACR Annual Meeting
Lunit to Showcase AI Solution for Breast Cancer at SBI 2019
Lunit to Present Findings on the Predictive Power of AI Biomarker for Lung Cancer Immunotherapy at ASCO 2019
Lunit Named to the 2019 CB Insights Digital Health 150 -- List of Most Innovative Digital Health Startups
Lunit at RSNA 2019
Lunit Announces its First CE Mark for AI-Powered Chest X-ray Analysis Software, Lunit INSIGHT CXR
Lunit AI software clinically installed in global sites—to be presented at RSNA 2019
Renowned Oncologist Dr. Tony Mok Joins Lunit Advisory Board
Lunit to Present Findings on the Predictive Power of AI-based Analysis of Immune Phenotype at ASCO 2020
Lunit Awarded as Technology Pioneer by World Economic Forum
Lunit at ECR 2020: Providing Virtual Exhibition and Online Presentations
Lunit Named to the 2020 CB Insights Digital Health 150 -- List of Most Innovative Digital Health Startups
RSNA 2020--Lunit Collaborates with Global Giants in Presenting its AI Solution at Virtual Booths of GE Healthcare, FujiFilm, and Sectra
What do medical studies say about AI for COVID-19 management?
What do the medical journals say about AI-powered mammography?
Research Using Lunit Demo Website
Lunit Presents AI-powered Pathologic Classification of Immune Phenotype that Predicts Response to Immunotherapy at USCAP 2021
What do the medical journals say about AI-powered chest x-ray interpretation?
Join our webinar with Dr. Fredrik Strand
From retrospective to prospective trials of AI in breast cancer screening
AACR 2021 - Lunit Presents Abstracts Demonstrating the Potential of its AI Biomarker in Cancer Treatment
Will AI Identify Breast Cancer Better Than Radiologists in Actual Clinical Screening?
Case of the Month | Where Is Breast Cancer?
Clinical Application of Lunit AI For Chest Radiography and Mammography to Be Presented at AOCR 2021
Lunit Secures $26M Investment from Guardant Health in a Strategic Funding Round
A Multi-reader Study Finds Unnecessary CT Exams Can Be Reduced by 30% When Analyzing Chest Radiographs with AI
Fujifilm Introduces its AI-powered Product for Chest X-ray in Japan, in Collaboration with Lunit
Lunit Collaborates with Intel to Provide AI Solutions to CPU-Based Customers in Need of Effective X-ray Diagnosis
Lunit AI Applied to Clinical Trial for Drug Development for the First Time--Findings Presented at ESMO 2021
Case of the Month (Chest x-ray)
COVID Global User Testimonials
Where is Cancer?
Breast Cancer Awareness Month — Ambassador Messages
TimeSformer: Is Space-Time Attention All You Need for Video Understanding?
Evaluation curves for object detection algorithms in medical images
Lunit to Participate in RSNA 2021, Presenting its New AI Solutions for Digital Breast Tomosynthesis and Chest CT
Lunit Expands Team with Multiple Industry Leaders to Accelerate its Business Growth
Lunit Presents Studies at SITC 2021, Highlighting the Effectiveness of AI in Predicting Response to Immunotherapy in a Clinical Trial Setting
Lunit Gets FDA Nod for AI-based Chest X-ray Triage Solution, Developed for Sorting of Emergency Cases
Lunit's AI Software for Breast Cancer Detection, Lunit INSIGHT MMG, Wins FDA Clearance
Research Backs Clinical Efficacy of Lunit's Radiology AI Products; Abstracts to be Presented at RSNA 2021
Medical AI Provider Lunit Raises $61M in Funding Round Led By Major Global Healthcare Investors
Lunit Named to the 2021 CB Insights Digital Health 150 -- List of Most Innovative Digital Health Startups
Lunit Obtains MDSAP Certificate, Granted Fast-Track Regulatory Process in Major Countries
Lunit to Showcase Chest and Breast Radiology AI in Arab Health 2022
Baheya Foundation, Egypt’s Premier Destination for Breast Cancer, Adopts Lunit AI to Enhance Early Screening