Supervisory control system for monitoring a pharmaceutical hot melt extrusion process

Daniel Markl, Patrick R. Wahl, José C. Menezes, Daniel M. Koller, Barbara Kavsek, Kjell Francois, Eva Roblegg, Johannes G. Khinast

Research output: Contribution to journalArticlepeer-review

57 Citations (Scopus)


Continuous pharmaceutical manufacturing processes are of increased industrial interest and require uni- and multivariate Process Analytical Technology (PAT) data from different unit operations to be aligned and explored within the Quality by Design (QbD) context. Real-time pharmaceutical process verification is accomplished by monitoring univariate (temperature, pressure, etc.) and multivariate (spectra, images, etc.) process parameters and quality attributes, to provide an accurate state estimation of the process, required for advanced control strategies. This paper describes the development and use of such tools for a continuous hot melt extrusion (HME) process, monitored with generic sensors and a near-infrared (NIR) spectrometer in real-time, using SIPAT (Siemens platform to collect, display, and extract process information) and additional components developed as needed. The IT architecture of such a monitoring procedure based on uni- and multivariate sensor systems and their integration in SIPAT is shown. SIPAT aligned spectra from the extrudate (in the die section) with univariate measurements (screw speed, barrel temperatures, material pressure, etc.). A multivariate supervisory quality control strategy was developed for the process to monitor the hot melt extrusion process on the basis of principal component analysis (PCA) of the NIR spectra. Monitoring the first principal component and the time-aligned reference feed rate enables the determination of the residence time in real-time.

Original languageEnglish
Pages (from-to)1034-1044
Number of pages11
JournalAAPS PharmSciTech
Issue number3
Early online date26 Jun 2013
Publication statusPublished - 30 Sept 2013


  • continuous monitoring
  • near-infrared spectroscopy
  • principal component analysis
  • process analytical technology


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