Determination of Residence Time Distribution in a Continuous Powder Mixing Process With Supervised and Unsupervised Modeling of In-line Near Infrared (NIR) Spectroscopic Data

Research output: Contribution to journalJournal articleResearchpeer-review

  • Troels Pedersen
  • Anssi Pekka Karttunen
  • Ossi Korhonen
  • Jian Xiong Wu
  • Kaisa Naelapää
  • Erik Skibsted
  • Rantanen, Jukka

Successful implementation of continuous manufacturing processes requires robust methods to assess and control product quality in a real-time mode. In this study, the residence time distribution of a continuous powder mixing process was investigated via pulse tracer experiments using near infrared spectroscopy for tracer detection in an in-line mode. The residence time distribution was modeled by applying the continuous stirred tank reactor in series model for achieving the tracer (paracetamol) concentration profiles. Partial least squares discriminant analysis and principal component analysis of the near infrared spectroscopy data were applied to investigate both supervised and unsupervised chemometric modeling approaches. Additionally, the mean residence time for three powder systems was measured with different process settings. It was found that a significant change in the mean residence time occurred when comparing powder systems with different flowability and mixing process settings. This study also confirmed that the partial least squares discriminant analysis applied as a supervised chemometric model enabled an efficient and fast estimate of the mean residence time based on pulse tracer experiments.

Original languageEnglish
JournalJournal of Pharmaceutical Sciences
Issue number3
Pages (from-to)1259-1269
Number of pages11
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© 2020 American Pharmacists Association®

    Research areas

  • Continuous powder blending, Continuously stirred tank reactor (CSTR) in series, Mean residence time, Near infrared (NIR) spectroscopy, Partial least squares discriminant analysis (PLS-DA), Principal component analysis (PCA), Process analytical technologies (PAT), Residence time distribution (RTD)

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