Nucleai, an artificial intelligence (AI)-based spatial biomarker and diagnostics company, announced in April the launch of what it said was a first-of-its-kind deep learning model designed to automate the normalization of high-plex imaging data—a foundational step within the spatial proteomics workflow that is intended to accelerate the discovery of biomarkers for antibody-drug conjugates (ADCs), bispecifics, and immunotherapies. During the recent American Society of Clinical Oncology (ASCO) Annual Meeting, Nucleai demonstrated its optical density (OD)-based quantitative biomarker scoring solution, designed to solve challenges associated with manual visual scoring of immunohistochemistry (IHC) images by pathologists.
