Grant Rebecca, Coopman Karen, Silva-Gomes Sandro, Campbell Jonathan J, Kara Bo, Braybrook Julian, Petzing Jon
Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK.
Department of Aeronautical, Automotive, Chemical and Materials Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK.
Methods Protoc. 2021 Mar 30;4(2):24. doi: 10.3390/mps4020024.
Measured variability of product within Cell and Gene Therapy (CGT) manufacturing arises from numerous sources across pre-analytical to post-analytical phases of testing. Operators are a function of the manufacturing process and are an important source of variability as a result of personal differences impacted by numerous factors. This research uses measurement uncertainty in comparison to Coefficient of Variation to quantify variation of participants when they complete Flow Cytometry data analysis through a 5-step gating sequence. Two study stages captured participants applying gates using their own judgement, and then following a diagrammatical protocol, respectively. Measurement uncertainty was quantified for each participant (and analysis phase) by following Guide to the Expression of Uncertainty in Measurement protocols, combining their standard deviations in quadrature from each gating step in the respective protocols. When participants followed a diagrammatical protocol, variation between participants reduced by 57%, increasing confidence in a more uniform reported cell count percentage. Measurement uncertainty provided greater resolution to the analysis processes, identifying that most variability contributed in the Flow Cytometry gating process is from the very first gate, where isolating target cells from dead or dying cells is required. This work has demonstrated the potential for greater usage of measurement uncertainty within CGT manufacturing scenarios, due to the resolution it provides for root cause analysis and continuous improvement.
细胞与基因疗法（CGT）生产过程中所测得的产品变异性源于从分析前到分析后测试阶段的众多来源。操作人员是生产过程的一部分，由于受到众多因素影响的个人差异，他们是变异性的一个重要来源。本研究使用测量不确定度与变异系数进行比较，以量化参与者在通过五步设门序列完成流式细胞术数据分析时的变异情况。两个研究阶段分别记录了参与者凭自己的判断设门，以及按照图解方案设门的情况。通过遵循《测量不确定度表示指南》的方案，将每个参与者（以及分析阶段）在各自方案中每个设门步骤的标准偏差进行正交组合，从而对测量不确定度进行量化。当参与者遵循图解方案时，参与者之间的变异性降低了57%，从而提高了对更统一报告的细胞计数百分比的置信度。测量不确定度为分析过程提供了更高的分辨率，确定在流式细胞术设门过程中贡献最大变异性的是第一道门，即需要将目标细胞与死细胞或濒死细胞分离的步骤。这项工作证明了在CGT生产场景中更大程度使用测量不确定度的潜力，因为它为根本原因分析和持续改进提供了分辨率。
