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Research ArticleTechnology/Application

A Risk Index and Data Display for Process Performance in the Pharmaceutical Industry

Bert Gunter, Daniel Coleman, Aaron Goerke, Theo Koulis, Jens Lamerz and Yiming Peng
PDA Journal of Pharmaceutical Science and Technology March 2018, 72 (2) 188-198; DOI: https://doi.org/10.5731/pdajpst.2017.008177
Bert Gunter
1Retired, formerly Nonclinical Biostatistics, Genentech, Inc., South San Francisco, CA;
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Daniel Coleman
2Nonclinical Biostatistics, Genentech, Inc., South San Francisco, CA;
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  • For correspondence: coleman.daniel@gene.com
Aaron Goerke
3Global Manufacturing Science and Technology, F. Hoffmann-La Roche AG, Basel, Switzerland; and
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Theo Koulis
2Nonclinical Biostatistics, Genentech, Inc., South San Francisco, CA;
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Jens Lamerz
4Nonclinical Biostatistics, F. Hoffmann-La Roche AG, Basel, Switzerland
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Yiming Peng
2Nonclinical Biostatistics, Genentech, Inc., South San Francisco, CA;
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Abstract

We propose a new index and graphical display for quantifying and visualizing process performance in the pharmaceutical industry. These tools can provide management a comprehensive, high level overview of the process performance of a global manufacturing network suitable for risk ranking, by which is meant: identifying those processes at greatest risk of failing to meet specifications, and prioritizing resources to drive continuous process improvement. Our index, like others currently in use, compares the observed variation of CQAs—critical quality attributes—to their specifications. However, instead of relying on traditional data summaries such as means and standard deviations to characterize process results, the proposed index uses sample quantiles. Quantiles are more accurate and reliable when data are skewed or short-tailed as is often observed for pharmaceutical processes. Perhaps just as important, we communicate the results with a new visual display that accurately compares processes and sites. The display identifies instances when the summaries may mislead and the subject matter expert needs to “drill down” into manufacturing data to assure correct understanding.

LAY ABSTRACT: The proposed risk index and graphical display enables high-risk processes to be identified, process improvements to be prioritized, resources to be efficiently allocated, and strategic planning for continuous process improvement to be evidence-based.

  • Risk ranking
  • process performance
  • process capability
  • critical quality attribute
  • specifications
  • continuous process improvement
  • © PDA, Inc. 2018
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PDA Journal of Pharmaceutical Science and Technology: 72 (2)
PDA Journal of Pharmaceutical Science and Technology
Vol. 72, Issue 2
March/April 2018
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A Risk Index and Data Display for Process Performance in the Pharmaceutical Industry
Bert Gunter, Daniel Coleman, Aaron Goerke, Theo Koulis, Jens Lamerz, Yiming Peng
PDA Journal of Pharmaceutical Science and Technology Mar 2018, 72 (2) 188-198; DOI: 10.5731/pdajpst.2017.008177

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A Risk Index and Data Display for Process Performance in the Pharmaceutical Industry
Bert Gunter, Daniel Coleman, Aaron Goerke, Theo Koulis, Jens Lamerz, Yiming Peng
PDA Journal of Pharmaceutical Science and Technology Mar 2018, 72 (2) 188-198; DOI: 10.5731/pdajpst.2017.008177
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  • Article
    • Abstract
    • 1. Introduction and Context
    • 2. Rpk Objectives
    • 3. Some Basics On Statistical Quantiles
    • 4. Rpk Definition and Interpretation
    • 5. Product A—How To “Read” the Data Display (Figure 2)
    • 6. Product B—Drilling Down (Figures 3 and 4)
    • 7. Product C—Drilling Down (Figures 5 and 6)
    • 8. FAQS
    • 9. Summary
    • Conflict of Interest Declaration
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    • References
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Keywords

  • risk ranking
  • process performance
  • Process capability
  • Critical quality attribute
  • Specifications
  • continuous process improvement

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