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Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Approaching stability challenges for flow cytometry in a regulated bioanalytical environment.

Anamica Muruganandham¹, Carolyne Dumont², Kuiyi Xing¹

¹Celerion, Inc., 621 Rose Street, Lincoln, NE 68502, USA.

|October 23, 2019

Summary

Sample stability is crucial for reliable flow cytometry data, especially for clinical samples requiring shipment. This study offers guidance on experimental parameters to ensure accurate results during sample transport and analysis.

Keywords:

bioanalytical challenge clinical samples flow cytometry preclinical samples regulatory environment stability

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Flow Cytometric Characterization of Murine B Cell Development

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Area of Science:

Biomedical Sciences
Analytical Chemistry
Immunology

Background:

Flow cytometry is a vital technique for cellular analysis.
Sample stability is a critical factor influencing assay reliability and data accuracy.
Clinical samples often require transportation, posing challenges for maintaining sample integrity.

Purpose of the Study:

To evaluate and define critical parameters for ensuring sample stability in flow cytometry.
To provide recommendations for experimental design to optimize sample storage and handling.
To address challenges in flow cytometry assay development for regulated bioanalytical environments.

Main Methods:

Investigated various factors affecting sample stability from collection to acquisition.
Developed and applied stability-indicating methods for flow cytometry assays.
Utilized case studies to demonstrate solutions for common stability issues.

Main Results:

Identified key experimental and stability parameters crucial for flow cytometry.
Demonstrated successful strategies for overcoming sample stability challenges.
Established protocols for reliable flow cytometry analysis of transported samples.

Conclusions:

Optimizing sample stability is essential for obtaining accurate and reproducible flow cytometry data.
The study provides practical guidance for designing robust flow cytometry methods.
Recommendations support flexible and reliable bioanalytical testing of clinical samples.