APR 29, 2026 3:00 PM PDT

Speed Meets Spectrum: A Practical Flow Cytometry Advantage for Translational Immunology

Sponsored by: Thermo Fisher Scientific
Speaker

Abstract

As translational immunology moves toward increasingly complex and clinically driven questions, flow cytometry must deliver both speed and analytical depth. This presentation highlights how the combination of high-speed and spectral flow cytometry meets these evolving demands and supports more efficient immune profiling in real-world research environments. High-speed acquisition allows to process large, complex sample sets within practical timeframes, while spectral flow cytometry enhances multiparametric resolution and experimental flexibility—particularly valuable when working with limited, heterogeneous clinical material.

Through two applied case studies, this talk emphasizes how these technologies impact everyday laboratory work. An example from HIV research will illustrate the importance of rapid, high-dimensional profiling for preserving sample integrity and extracting actionable insights. A second example from cancer immunology will show how this approach enables robust analysis of challenging tumor-derived samples. Together, these use cases demonstrate how combining speed and spectral capabilities not only advances translational discovery but also improves workflow efficiency and confidence in experimental outcomes.

Learning Objectives: 

1. Explain how pairing rapid acquisition with spectral detection increases analytical depth, supports multiparametric immune profiling, and addresses constraints of limited, heterogeneous clinical samples in translational studies. 

2. Describe workflow strategies that leverage high-speed spectral cytometry in HIV research to minimize processing delays, maintain data quality, and translate complex phenotyping into decision-relevant outputs. 

3. Outline panel design, compensation/unmixing, and QC approaches that enable reliable characterization of diverse cell populations in cancer immunology, improving efficiency, reproducibility, and confidence in experimental outcomes.


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