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In-Depth Evaluation of Data Collected During a Continuous Pharmaceutical Manufacturing Process: A Multivariate Statistical Process Monitoring Approach

By Silva, Ana F.; Vercruysse, Jurgen; Vervaet, Chris; Remon, Jean P.; Lopes, João A.; De Beer, Thomas; Sarraguça, Mafalda C.

Published on

Abstract

The present work presents an in-depth evaluation of continuously collected data during a twin-screw granulation and drying process performed on a continuous manufacturing line. During operation, the continuous line logs 49 univariate process variables, hence generating a large amount of data. Three identical 5-h continuous manufacturing runs were performed. Multivariate data analysis tools, more specifically latent variable modeling tools such as principal component analysis, were used to extract information from the generated data sets unveiling process trends and drifts. Furthermore, a statistical process monitoring strategy is presented. The approach is based on the application of multivariate statistical process monitoring to model the variables that remain around a steady state.

Journal

Journal of Pharmaceutical Sciences. Volume 108, 2019, 439-450

DOI

10.1016/j.xphs.2018.07.033

Type of publication

Peer-reviewed journal

Affiliations

  • Ghent University
  • Universidade do Porto
  • University of Lisbon

Article Classification

Research article

Classification Areas

  • PAT
  • Control

Tags