Jon Petzing
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Jon Petzing has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Bo Kara
GlaxoSmithKline
1 shared publication - Jonathan J. Campbell
National Measurement Laboratory, LGC, Queens Road, Teddington TW11 0LY, Middlesex, UK
1 shared publication - Julian Braybrook
National Measurement Laboratory, LGC
1 shared publication - Karen Coopman
Loughborough University
1 shared publication - Nicholas Medcalf
Centre for Biological Engineering, Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough, UK
1 shared publication - Rebecca Grant
Loughborough University
1 shared publication
Latest Publications
- 16 October 2020
- Published by Parenteral Drug Association, Inc. in PDA Journal of Pharmaceutical Science and Technology
- Vol. 75 (1) , 33-47
Quantifying Operator Subjectivity within Flow Cytometry Data Analysis as a Source of Measurement Uncertainty and the Impact of Experience on Results
Background: Flow Cytometry is a complex measurement characterisation technique, utilised 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 focuses on understanding the contribution of manual operator variability within the data analysis phase. Methods: 38 participants completed a questionnaire providing information about experience and motivational factors, before completing a simple gating study. Results were analysed using Gauge Repeatability & 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. Results: 85 % of participants surveyed preferred manual gating to automated data analysis, with primary reasons being legacy (″it′s always been done that way″) and accuracy, not in the metrological sense, but in clear definition of the correct target population. The median expanded uncertainty was calculated as 3.6 % for the population studied, with no significant difference between more or less experienced users. Discussion: 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.
- 16 October 2020
- Published by Parenteral Drug Association, Inc. in PDA Journal of Pharmaceutical Science and Technology
- Vol. 75 (1) , 33-47
Quantifying Operator Subjectivity within Flow Cytometry Data Analysis as a Source of Measurement Uncertainty and the Impact of Experience on Results
Background: Flow Cytometry is a complex measurement characterisation technique, utilised 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 focuses on understanding the contribution of manual operator variability within the data analysis phase. Methods: 38 participants completed a questionnaire providing information about experience and motivational factors, before completing a simple gating study. Results were analysed using Gauge Repeatability & 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. Results: 85 % of participants surveyed preferred manual gating to automated data analysis, with primary reasons being legacy (″it′s always been done that way″) and accuracy, not in the metrological sense, but in clear definition of the correct target population. The median expanded uncertainty was calculated as 3.6 % for the population studied, with no significant difference between more or less experienced users. Discussion: 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.