Your browser doesn't support javascript.
loading
Assessment of Protocol Impact on Subjectivity Uncertainty When Analyzing Peripheral Blood Mononuclear Cell Flow Cytometry Data Files.
Grant, Rebecca; Coopman, Karen; Silva-Gomes, Sandro; Campbell, Jonathan J; Kara, Bo; Braybrook, Julian; Petzing, Jon.
Afiliação
  • Grant R; Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK.
  • Coopman K; Department of Aeronautical, Automotive, Chemical and Materials Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK.
  • Silva-Gomes S; GlaxoSmithKline, Gunnels Wood Road, Stevenage SG1 2NY, UK.
  • Campbell JJ; LGC Group, Queen's Road, Teddington, Middlesex TW11 0LY, UK.
  • Kara B; GlaxoSmithKline, Gunnels Wood Road, Stevenage SG1 2NY, UK.
  • Braybrook J; LGC Group, Queen's Road, Teddington, Middlesex TW11 0LY, UK.
  • Petzing J; Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK.
Methods Protoc ; 4(2)2021 Mar 30.
Article em En | MEDLINE | ID: mdl-33808088
ABSTRACT
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.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article