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Published on: February 8, 2016
A Modular High-Parameter Flow Cytometry Framework: Pre-Analytical Optimization and Validation for Clinical Research
Jennifer Scott1, Iva Lelios2, Tobias Rutishauser2
1Translational Science Department, IQVIA Laboratories, Livingstone, UK.
Summary
A modular high-parameter flow cytometry (hpFCM) approach enhances immune profiling in drug development. This adaptable assay ensures data reproducibility and supports biomarker discovery throughout clinical trials.
Area of Science:
- Immunology
- Biotechnology
- Clinical Trials
Background:
- High-parameter flow cytometry (hpFCM) is crucial for immune profiling and biomarker discovery in clinical trials.
- Clinical adoption is limited by assay variability, logistical issues, and complexity, necessitating robust quality controls and validation.
Purpose of the Study:
- To introduce and validate a modular hpFCM approach for flexible and reproducible immune cell analysis in drug development.
- To enable dynamic customization of assays throughout clinical studies for evolving immunophenotyping needs.
Main Methods:
- Developed a modular hpFCM assay with a core panel and interchangeable marker modules.
- Validated assay reliability, accuracy, selectivity, repeatability, and reproducibility according to CLSI H62 guidelines.
- Assessed specimen stability for both whole blood and frozen peripheral blood mononuclear cells (PBMCs).
Main Results:
- The modular hpFCM assay demonstrated high accuracy, selectivity, repeatability, and reproducibility across configurations.
- Key secondary endpoints (e.g., CD8+ T cells) showed precision (<20% CV), with specimen stability up to 4 days.
- Exploratory endpoints showed 90% repeatability and 55% stability over 4 days.
Conclusions:
- The modular hpFCM approach offers a scalable, agile, and cost-effective framework for biomarker strategies in drug development.
- This adaptable design addresses limitations in current hpFCM workflows, enhancing operational efficiency and enabling reverse translational research.
- The framework facilitates dynamic immunophenotyping and biomarker discovery, streamlining clinical implementation, though further validation in real-world trials is ongoing.
