SEOUL, South Korea--(BUSINESS WIRE)--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 #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, 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 partnerships.”
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