Speaker: Ettai Markovits, MD, PhD | Director of Biomedical Research, Nucleai
Resistance to immunotherapy treatments continues to be a major challenge and is an active area of investigation across academia, the clinical community, and the biopharma industry. While recent advances in single-cell and spatial omics technologies have expanded the study of immunobiology of the tumor microenvironment, the role of functional and metabolic states of tumor and immune cells in driving disease progression and therapy resistance warrant further investigation.
In this webinar, the speaker will present results from a recent collaboration with University of Queensland and Yale University, where a comprehensive multiplex immunofluorescence (mIF) panel was combined with Nucleai’s deep learning pipeline and applied to a cohort of metastatic non-small cell lung cancer (NSCLC) and metastatic head and neck squamous cell carcinoma (HNSCC) patient samples. The study uncovered a novel metabolic signature predictive of treatment resistance. The speaker will also discuss how Nucleai’s deep learning platform can help biopharma researchers rapidly extract clinically relevant biomarker signatures from complex mIF datasets, at scale.
