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

Abstract

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.

SEDEX—Self-Emulsifying Delivery Via Hot Melt Extrusion: A Continuous Pilot-Scale Feasibility Study

“…The HME process is flexible and allows for the screw configuration to be tailored to the specific requirements of the processed formulation [15,16]. In addition, HME offers the possibility of implementing PAT, real-time quality monitoring [15,17,18], and other tools for advanced process control [18][19][20][21]. Recently, in silico process development and scale-up has shown successful cases of reducing the overall process development time and material waste [21][22][23][24].…”