Trained on large
Lunit SCOPE PD-L1 analyzes every PD-L1 positive tumor cell and generates analysis results close to the ground truth
How AI Improves
AS-IS (Only Human)
- Discrepancy between pathologists
TO-BE (With AI)
- Objective result
How It Works
Enabling Better Immunotherapy
based on AI-powered PD-L1 Analysis
analysis of PD-L1
* Lunit SCOPE PD-L1 is currently applicable to NSCLC (non-small cell lung cancer) only.
Lunit SCOPE PD-L1
Detects tumor cell PD-L1 +/- and inflammatory cell PD-L1 +/- from whole slide images.
Calculates PD-L1 positive score including TPS (Tumor Proportion Score) and CPS (Combined Positive Score).
AI Score and Report
Provides AI analysis results including PD-L1 TPS score and map within a report.
Improving PD-L1 test efficiency through
How Our AI Works
Tissue slide (FFPE)
slicing & IHC staining
Digitization using a scanner
Supports various scanner vendors
File upload to server
(both cloud or on-prem)
Lunit SCOPE PD-L1 analysis
Lunit SCOPE PD-L1
- Detection results for visualization
- Quantification results of key features detected
- Final score for response prediction
*Lunit SCOPE PD-L1 is currently available for
research use only
Lunit SCOPE PD-L1
Deep learning from HE slides predicts the clinical benefit from adjuvant chemotherapy in hormone receptor-positive breast cancer patients
Abstract : Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.
Abstract : Pathologic validation of artificial intelligence-powered prediction of combined positive score of PD-L1 immunohistochemistry in urothelial carcinoma.
Abstract: Artificial intelligence-powered spatial analysis of tumor infiltrating lymphocytes (TIL) to reflect target gene expressions of novel immuno-oncology agents.
Abstract : Deep learning based radiomic biomarker for predicting the presence of high-grade histologic patterns in lung adenocarcinoma
Abstract: Comprehensive deep learning analysis of H&E tissue phenomics reveals distinct immune landscape and transcriptomic enrichment profile among immune inflamed, excluded and desert subtypes...
Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses
Abstract: Deep-learning analysis of H&E images to define three immune phenotypes to reveal loss-of-target in excluded immune cells as a novel resistance mechanism of immune checkpoint inhibitor...
Abstract: Deep learning-based immune phenotype analysis reveals distinct resistance pattern of immune checkpoint inhibitor in non-small cell lung cancer
Abstract: Deep learning-based predictive biomarker for adjuvant chemotherapy in early-stage hormone receptor-positive breast cancer
Abstract: Pan-cancer analysis of tumor microenvironment using deep learning-based cancer stroma and immune profiling in H&E images
Abstract: Deep learning-based predictive biomarker for immune checkpoint inhibitor response in metastatic non-small cell lung cancer
Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge
Abstract : Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes reveals distinct genomic profile of immune excluded phenotype in pan-carcinoma
Abstract : Artificial intelligence-powered tissue analysis reveals distinct tumor-infiltrating lymphocyte profile as a potential biomarker of molecular subtypes in endometrial cancer
Abstract : Clinical performance of artificial intelligence-powered annotation of tumor cell PD-L1 expression for treatment of immune-checkpoint inhibitor (ICI) ...
Abstract: Distinct subset of immune cells assessed by multiplex immunohistochemistry correlates with immune phenotype classified by ...