SEOUL, South Korea–(BUSINESS WIRE)–lt;a href=”https://twitter.com/hashtag/AI?src=hash” target=”_blank”gt;#AIlt;/agt;–Lunit
today announced an abstract presentation of its AI precision medicine
research portfolio at the American Society of Clinical Oncology (ASCO)
Annual Meeting 2019, 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, June
2. Lunit will also be hosting a booth exhibition during ASCO, at booth
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, 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.
After reclassifying 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.
“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
Full ASCO abstract: http://abstracts.asco.org/239/AbstView_239_266969.html
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)
Sunday, June 2,
2019, 8:00am to 11:00am, Hall A
Jussarang Lee, Communications