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Evaluating the quality of a cell counting measurement process via a dilution series experimental design

细胞计数 重复性 计算机科学 质量保证 复制 过程(计算) 计数过程 准确度和精密度 实验设计 工艺验证 测量不确定度 数据挖掘 统计 数学 工程类 化学 验证和确认 外部质量评估 操作系统 细胞 生物化学 细胞周期 运营管理
作者
Sumona Sarkar,Steven P. Lund,Ravi Vyzasatya,Padmavathy Vanguri,John T. Elliott,Anne L. Plant,Sheng Lin‐Gibson
出处
期刊:Cytotherapy [Elsevier]
卷期号:19 (12): 1509-1521 被引量:21
标识
DOI:10.1016/j.jcyt.2017.08.014
摘要

Background aims Cell counting measurements are critical in the research, development and manufacturing of cell-based products, yet determining cell quantity with accuracy and precision remains a challenge. Validating and evaluating a cell counting measurement process can be difficult because of the lack of appropriate reference material. Here we describe an experimental design and statistical analysis approach to evaluate the quality of a cell counting measurement process in the absence of appropriate reference materials or reference methods. Methods The experimental design is based on a dilution series study with replicate samples and observations as well as measurement process controls. The statistical analysis evaluates the precision and proportionality of the cell counting measurement process and can be used to compare the quality of two or more counting methods. As an illustration of this approach, cell counting measurement processes (automated and manual methods) were compared for a human mesenchymal stromal cell (hMSC) preparation. Results For the hMSC preparation investigated, results indicated that the automated method performed better than the manual counting methods in terms of precision and proportionality. Discussion By conducting well controlled dilution series experimental designs coupled with appropriate statistical analysis, quantitative indicators of repeatability and proportionality can be calculated to provide an assessment of cell counting measurement quality. This approach does not rely on the use of a reference material or comparison to "gold standard" methods known to have limited assurance of accuracy and precision. The approach presented here may help the selection, optimization, and/or validation of a cell counting measurement process.
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