7. Project Summary/Abstract Recent decades have been marked by a revolution in single-cell analytical techniques, instruments and software tools that have markedly improved our understanding of biology. A high-profile example has been the emergence of single-cell sequencing to move from bulk genomic and transcriptomic analysis to single-cell resolution that reveals the heterogeneity of individual cells. Similar trends have been observed in protein analysis, spatial transcriptomics, and other disciplines. However, there remains a critical unmet need in understanding individual cellular function, movement, interactions, and other measures of performance. The genesis of cells as living drugs requires the development of technologies that can characterize the function and performance of massive numbers of cells at single-cell resolution to support development of new therapies and clinical biomarkers. Unfortunately, existing technologies are either not scalable, are cell-destructive and so cannot evaluate cells and their interactions over time, or do not provide single-cell resolution. CellChorus® evaluates the performance and interactions of thousands of individual cells by applying Time- lapse Imaging Microscopy in Nanowell Grids (TIMING™) with neural network-based artificial intelligence (AI) to identify, track, and characterize behaviors and interactions of disease cells together with T-cells and other effector cells. The platform has been validated technically and commercially in an academic setting and an early access laboratory, but this model does not scale. We will develop and rigorously validate a Chronos™ instrument that delivers dynamic single-cell analysis based on the TIMING platform and applying our existing AI software and algorithms. The Chronos instrument will allow scientists, researchers, and manufacturing experts to apply dynamic single-cell analysis to catalyze development and manufacture of novel therapies in infectious diseases, oncology, and other medical sciences.