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• Several controller strategies for a feeding-blending unit are designed and applied in a simulation and on a real plant. • Standard controller concepts are compared to a model predictive controller. • Brief feeder fluctuations are successfully attenuated by adjusting the blender speed. • Application of a model predictive controller shows advantageous behaviour compared to the other controller strategies. This paper outlines several control strategies for a feeding blending unit in a continuous pharmaceutical manufacturing setup, with the goal of damping feeder fluctuations by adjusting the blender speed. An advanced model predictive control concept and two standard concepts, PI- and model-based feed-forward control, are described and compared with respect to their performance in the simulation. The concepts which showed satisfactory behaviour in the simulation are further tested on the real system. The paper also provides a detailed explanation of each implementation step in a real system, i.e., measurement device setup, signal processing, parameter identification and controller design. The properties of control concepts are compared and analysed, particularly in view of further work on the complete direct compaction line. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop a novel closed-loop controlled continuous tablet manufacturing line, which first uses hot melt extrusion (HME) to produce pellets based on API and a polymer matrix. Such systems can be used to make complex pharmaceutical formulations, e.g., amorphous solid dispersions of poorly soluble APIs. The pellets are then fed to a direct compaction (DC) line blended with an external phase and tableted continuously. Fully-automated processing requires advanced control strategies, e.g., for reacting to raw material variations and process events. While many tools have been proposed for in-line process monitoring and real-time data acquisition, establishing real-time automated feedback control based on in-process control strategies remains a challenge. Control loops were implemented to assess the quality attributes of intermediates and product and to coordinate the mass flow rate between the unit operations. Feedback control for the blend concentration, strand temperature and pellet thickness was accomplished via proportional integral derivative (PID) controllers. The tablet press hopper level was controlled using a model predictive controller. To control the mass flow rates in all unit operations, several concepts were developed, with the tablet press, the extruder or none assigned to be the master unit of the line, and compared via the simulation. Image, graphical abstract [ABSTRACT FROM AUTHOR]

[Display omitted] • Synthesis of mesalazine in continuous flow. • Implementation of a concept for real-time data acquisition. • Development of a model-based control concept for the complete synthesis line. • Implementation of PAT and control strategy in an automation platform. A continuous synthesis line was developed integrating different common reaction steps namely nitration, substitution and hydrogenation. Mesalazine as model drug substance was produced from 2-chlorobenzoic acid in continuous flow mode. A multi-instrument PAT strategy was implemented to equip the full line with in-line monitoring capability for critical quality attributes (CQAs) at several points. While most applications of PAT in research and manufacturing of the drug substance are limited to in-process control of quality, in this study real-time process information was generated to support automated process control actions. Process models were developed for all steps of the synthesis route either mechanistic based on reaction kinetics, data driven based on process data or depicting the residence time distribution (RTD). These models facilitated the development and implementation of an automation concept. Feedback loops were established using model predictive controllers for each unit operation, with the objective to maximize yield and minimize side products. The results indicate the high potential of an advanced control concept based on process models and real-time process data. [ABSTRACT FROM AUTHOR]