Abstract How immune cells respond to stimuli is fundamental in developing adoptive cell therapies, vaccines, and other immunotherapies. T cells dynamically undergo activation, exhaustion, expansion, phenotype switching, and cell killing. Flow cytometry is the gold standard method for characterizing these at high throughput, typically by comparing T cell populations before and at different timepoints after treatment. This approach is limited to population-level analyses and overlooks any heterogeneity of individual T cell responses over time, which may contribute to variability in response. Here, we describe the development of a novel flow cytometry-based method (Time-lapse flowTM) to characterize immune cell responses over time at the single cell level. To measure the same cells repeatedly on a flow cytometer, we employed a new optical barcoding technology called laser particles (LPs) that provide individual cells with a unique spectral signature that can be tracked over the course of multiple measurements. Using a custom flow cytometer with fluorescence and LP detection, we performed a multi-day assay to capture how T cell marker expression changes over time after CD3/CD28 activation. Specifically, we used releasable antibodies to quantify PD1, CD69 and CD25 at each time-point and correlated these expression kinetics with cell function at the end of the assay by measuring cytokine secretion (IFNg, IL2, TNFa) after PMA/ionomycin stimulation. We found significant cellular heterogeneity in kinetic profiles of PD1, CD69 and CD25 expression, with different dominant ‘kinetic modes’ present for each marker. For example, while a large proportion of PD1 expression was transient (positive on day 1, but not on days 2 and 3), nearly all cells that express CD69 on day 1 retained their expression on day 2. We also found that T cells with late expression of PD1 had significantly more cytokine secretion compared to cells that were initially positive for PD1. These results were replicated with at least 3 replicate samples for multiple donors. Differences in kinetic phenotypes were not explained by conventional phenotyping with CD4, CD8, CD45RA and CCR7. To date, immune cell phenotyping with flow cytometry involves classifying cell types through their marker expression profiles at a single time-point. Here, we introduce a novel approach for acquiring time-resolved single-cell data with a flow cytometer and applied it to study T cell activation. We found novel kinetic phenotypes of T cells defined by their marker expression over time, which also correlated to their functional potential (cytokine secretion). These kinetic phenotypes could not be identified with conventional flow cytometry. Our approach could have significant implications for immunotherapy development, particularly in identifying the most suitable cell populations to use, understanding mechanisms of exhaustion and persistence, and elucidating the basis of donor variability. Citation Format: Sheldon J. Kwok, Sarah Forward, Emane Rose Assita, Trevor Brown, Marissa Fahlberg, Pratip Chattopadhyay. High-throughput time-resolved single-cell analysis of T-cell activation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1210.