Lunit to Present Findings on the Predictive Power of AI Biomarker for Lung Cancer Immunotherapy at ASCO 2019

Poster Presentation on Sunday, 2 June; Exhibition at Booth #19129

Lunit today announced abstract presentation of its AI precision medicine research portfolio at the American Society of Clinical Oncology (ASCO) Annual Meeting 2019. The meeting will be held May 31 – June 4 in Chicago.

The accepted abstract highlights the feasibility of AI-based biomarker in metastatic non-small cell lung cancer, based on the H&E analysis that predicts response to immune checkpoint inhibitors (ICI).

The abstract will be presented at ASCO poster sessions on Sunday, 2 June. Lunit will also be hosting a booth exhibition during ASCO, at booth #19129.

The study evaluated the predictive value of AI versus PD-L1, the main biomarker for ICI, in terms of both its comparative predictive value as well as additive predictive value.

According to the research conducted by Lunit, within PD-L1(+) patient group, the treatment response and progression-free survival (PFS) significantly differed depending on the AI score. The same results were obtained within the PD-L1(-) group.

According to the results, after the reclassification of PD-L1(-) patient group based on the AI score, 52% of patients with high AI score had, in fact, shown response to ICI. These patients had three times longer PFS compared to the patients who had a low AI score.

Similar outcomes were found among the PD-L1(+) patient group. Classified with AI profiling, 63% of low AI score patients were non-responsive to ICI. These patients had six times shorter PFS compared to high AI score patients.

Additionally, in an AI analysis independent of PD-L1, the team was able to identify more patients that showed response to ICI. Among PD-L1(+) patient group, 49% of the patients were responsive to ICI, whereas 65% of patients within high AI score patient group showed response.

Lunit SCOPE, an AI-powered H&E image analyzing tool, developed by Lunit.
Lunit SCOPE, an AI-powered H&E image analyzing tool, developed by Lunit.


“Our study reveals promising results that show an added value of AI analysis in cancer therapy, especially for the patient group with PD-L1(-), commonly known to be non-responsive to immune checkpoint inhibitors,” said Kyunghyun Paeng, Head of Precision Pathology at Lunit. “An enhanced treatment response is expected for those patients with high AI score within PD-L1(-) group. This signals a more precise identification of patients who are classified to be non-responsive according to the current standard of care.”

Lunit’s AI research in the field of pathology has been recognized to be world-leading in various occasions. The company had ranked world #1 in both MICCAI TUPAC Challenge 2016 and CAMELYON 2017, ahead of competitors like Microsoft and IBM.

“With our advanced deep-learning technology, we seek to push the boundary of precision medicine and navigate for opportunities that transcend current practices,” said Brandon Suh, CEO of Lunit. “We look forward to accelerating our research and development in AI biomarkers for cancer treatment and outcome prediction through various research partnerships.”

Lunit had recently presented abstracts during AACR 2019, showing the power of AI-based identification and quantification of cancer tissues as a potential prognostic & predictive biomarker for breast cancer.

The full ASCO abstract presented by Lunit can be found at:


ASCO Poster Session Abstract by Lunit:

#9094 Deep learning-based predictive biomarker for immune checkpoint inhibitor response in metastatic non-small cell lung cancer

Poster Session: Lung Cancer - Non-Small Cell Metastatic (Board #417)

Date: Sunday, June 2, 2019

Time: 8:00am to 11:00am

Location: Hall A


Jussarang Lee Communications Manager


About Lunit

Perfecting Intelligence, Transforming Medicine.

With AI, we aim to make data-driven medicine the new standard of care. We are especially focused on conquering cancer, one of the leading causes of death worldwide.

We develop AI solutions for precision diagnostics and therapeutics, to find the right diagnosis at the right cost, and the right treatment for the right patients.

Lunit, abbreviated from “learning unit,” is an AI software company devoted to developing advanced medical image analytics and data-driven imaging biomarkers via cutting-edge deep learning technology.

Founded in 2013, Lunit has been internationally acknowledged for its advanced, state-of-the-art technology and its application in medical images. Lunit has been named by CB Insights as one of “AI 100” startups transforming healthcare industry.

Lunit's technology has been recognized at international competitions such as ImageNet (5th place, 2015), TUPAC 2016 (1st place), and Camelyon 2017 (1st place), surpassing top companies like Google, IBM, and Microsoft. Lunit is based in Seoul, South Korea.

15th floor, 27 Teheran-ro 2-gil, Gangnam-gu,
Seoul, South Korea