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Explore a groundbreaking webinar that introduces Deep Visual Proteomics (DVP) combined with AI-powered pathology foundation models for high-resolution characterization of disease mechanisms in clinical tissue samples. Learn how AI trained on extensive histopathological datasets identifies and segments cellular regions within complex tissues, enabling spatially-resolved mass spectrometry-based proteomics analysis. Discover how this innovative platform allows direct comparison of molecular signatures across diverse tissue states by identifying thousands of proteins from minimal, phenotype-matched cell populations to create detailed, spatially-resolved proteomic maps of disease progression. Understand how DVP reveals complex signaling pathways and molecular signatures that drive the transition from health to disease, offering insights into disease dynamics at the proteomic level. Examine the identification of potential biomarkers and therapeutic targets that could facilitate early detection and intervention across various diseases. Gain knowledge about how merging AI-driven pathology with the depth of DVP establishes a new paradigm for spatial medicine, enhancing understanding and clinical tools for studying disease initiation and progression. The presentation is delivered by Dr. Andreas Mund, Associate Professor at the University of Copenhagen and Chief Scientific Officer at OmicVision Biosciences, who specializes in proteomics science and spatial protein expression analysis.
