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Quantifying operator subjectivity within flow cytometry data analysis as a source of measurement uncertainty and the impact of experience on results

journal contribution
posted on 2021-03-23, 14:05 authored by Rebecca GrantRebecca Grant, Karen CoopmanKaren Coopman, Nick Medcalf, Sandro Silva-Gomes, Jonathan J Campbell, Bo Kara, Julian Braybrook, Jon PetzingJon Petzing
Flow cytometry is a complex measurement characterization technique, utilized within the manufacture, measurement, and release of cell and gene therapy products for rapid, high-content, and multiplexed discriminatory cell analysis. A number of factors influence the variability in the measurement reported including, but not limited to, biological variation, reagent variation, laser and optical configurations, and data analysis methods. This research focused on understanding the contribution of manual operator variability within the data analysis phase. Thirty-eight participants completed a questionnaire, providing information about experience and motivational factors, before completing a simple gating study. The results were analyzed using gauge repeatability and reproducibility techniques to quantify participant uncertainty. The various stages of the gating sequence were combined through summation in quadrature and expanded to give each participant a representative uncertainty value. Of the participants surveyed, 85% preferred manual gating to automated data analysis, with the primary reasons being legacy (“it’s always been done that way”) and accuracy, not in the metrological sense but in the clear definition of the correct target population. The median expanded uncertainty was calculated as 3.6% for the population studied, with no significant difference among more or less experienced users. Operator subjectivity can be quantified to include within measurement uncertainty budgets, required for various standards and qualifications. An emphasis on biomanufacturing measurement terminology is needed to help understand future and potential solutions, possibly looking at translational clinical models to engage and enhance better training and protocols within industrial and research settings.

Funding

EPSRC/MRC Doctoral Training Centre for Regenerative Medicine at Loughborough University (EP/L105072/1)

GlaxoSmithKline

LGC

History

School

  • Mechanical, Electrical and Manufacturing Engineering
  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Chemical Engineering

Published in

PDA Journal of Pharmaceutical Science and Technology

Volume

75

Issue

1

Pages

33 - 47

Publisher

Parenteral Drug Association

Version

  • AM (Accepted Manuscript)

Rights holder

© PDA, Inc.

Publisher statement

This paper was accepted for publication in the journal PDA Journal of Pharmaceutical Science and Technology and the definitive published version is available at https://doi.org/10.5731/pdajpst.2019.011213.

Acceptance date

2020-09-14

Publication date

2021-02-22

Copyright date

2021

ISSN

1079-7440

eISSN

1948-2124

Language

  • en

Depositor

Dr Jon Petzing. Deposit date: 18 March 2021

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