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Effect of multivariate process instability on principal component analysis: A case study

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Abstract

With the rising use of principal component analysis/partial least squares (PCA/PLS) in the process analytical technology (PAT) initiative of the pharmaceutical industry, it seems appropriate to view that approach from a statistical process control (SPC) perspective. The purpose of this study was to demonstrate the effect of process instability (ie, state of statistical out-of-control) on use of PCA/PLS. The demonstrated differences in results should encourage PCA/PLS users to incorporate SPC as an active part of their process analytical control (PAC) toolkit to check for stability prior to drawing conclusions based on PCA/PLS analysis.

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Authors and Affiliations

  1. Stochos Inc, 14 North College Street, 12305, Schenectady, NY

    Donald S. Holmes

  2. Rochester Institute of Technology, 14623, Rochester, NY

    A. Erhan Mergen

Authors
  1. Donald S. Holmes
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  2. A. Erhan Mergen
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Correspondence to Donald S. Holmes.

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Published: April 29, 2005.

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Holmes, D.S., Mergen, A.E. Effect of multivariate process instability on principal component analysis: A case study. AAPS J 7, 11 (2005). https://doi.org/10.1208/aapsj070111

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  • DOI: https://doi.org/10.1208/aapsj070111

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