Skip to main content
Join CMKC members for a complimentary virtual event on December 10, 11am ET: CM MythBusters: https://bit.ly/3YXJynA. This is a fantastic opportunity to connect, collaborate, and debunk common myths about continuous manufacturing!
18.119.106.66

Improving Pellet Quality in a Pharmaceutical Hot Melt Extrusion Process via PID Control and LOLIMOT-Based MPC

By Rehrl, J; Kirchengast, MCelikovic, S; Sacher, S; Kruisz, J; Khinast, J; Horn, M

Published on

Abstract

Purpose The aim of this paper is the development of a process control concept for a hot melt extrusion (HME) and pelletization process. The new concept should improve the particle size distribution of the pellets produced. Methods Production of pellets containing an active pharmaceutical ingredient (API) can be achieved by means of HME, followed by a pelletization process step. The quality of pellets produced depends on the strand temperature at the pelletizer's inlet and the pelletizer's intake speed. This paper presents a strategy for the strand diameter and temperature control based on adjusting the cooling intensity on the cooling track between the HME and the pelletization step and altering the pelletizer's intake speed. Two concepts are presented and compared to the open-loop operation of the system: the first one is model predictive control (MPC) in combination with a model based on the local linear model tree (LOLIMOT) algorithm, and the second one is PID control. The quality of the pellets produced was analyzed in terms of particle size distribution (PSD). Results By implementation of the two control concepts, strand temperature and diameter could be kept close to the desired set points. Consequently, the presented concepts yielded pellets with a narrower particle size distribution than the open-loop operation of the plant. Conclusions The application of the presented control strategies can improve the quality of the pellets produced by an HME and pelletization system in terms of their particle size distribution.

Journal

Journal of Pharmaceutical Innovation. Volume 15, 2020, 678-689

DOI

10.1007/s12247-019-09417-0

Type of publication

Peer-reviewed journal

Affiliations

  • Research Center Pharmaceutical Engineering
  • Graz University of Technology

Article Classification

Research Article

Classification Areas

  • API
  • Modeling

Tags