Lunit Partnering with Daiichi Sankyo to Bring AI-Powered Pathology Analysis into Two of Daiichi Sankyo’s Oncology Research and Development Programs to Facilitate Faster Biomarker Discovery and Better Translational Research in Oncology Lunit is collaborating with Daiichi Sankyo to integrate its best-in-class AI-powered digital pathology solutions – Lunit SCOPE IO and SCOPE universal IHC (uIHC) – into two of Daiichi Sankyo’s oncology research and development programs to facilitate rapid exploration and discovery of novel biomarkers and improve translational research in oncology by utilizing AI to quantitate IHC staining, analyze immune phenotyping to identify novel markers, and analyze spatial features to discover novel biomarkers and better enable precise patient stratification to enrich clinical trials and ultimately optimize future clinical trial design and development plans
Also Read: L&T Technology Services Unveils AI-Powered “Digital Twin” to Revolutionize Respiratory Diagnostics with NVIDIA
“Lunit SCOPE was designed to illuminate unseen insights from pathology slide images – quantifying the tumor microenvironment, predicting molecular characteristics, and producing analytic features to inform clinical trial design,” said Brandon Suh, Lunit’s CEO; “SCOPE uIHC is now enabling the discovery of a whole new generation of IHC-based biomarkers. In collaboration with Daiichi Sankyo, we are now incorporating these tools and technologies into translational and clinical research to enable rapid discovery and precise patient stratification. This will lead to more efficient clinical trials and better outcomes – where every single patient will have a much better chance of receiving the right therapy for their individual needs and characteristics.” The two companies will conduct exploratory research and analyses to identify and discover potential opportunities to shape their approach to biomarker discovery and inform their clinical development strategies and research into more precise and effective cancer therapies and treatments to better collaborate and lead the utilization of AI technology to improve cancer research and treatment.


