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Development and implementation of an advanced model predictive control system into continuous pharmaceutical tablet compaction process

By Bhaskar, Aparajith; Barros, Fernando N; Singh, Ravendra

Published on

Abstract

In the context of continuous pharmaceutical oral dosage manufacturing, a control system is essential to ensure that the critical quality attributes (CQAs) are maintained within the regulatory constraints by mitigating variations generated in upstream operations. Such a system is essential to the Quality by Design (QbD) paradigm shift, which can ensure that predefined end quality attributes are achieved within an optimal economic and time bracket. In this work, an advanced model predictive control (MPC) architecture integrated with a novel real-time tablet weight measurement method has been development and implemented into a continuous direct compaction tablet manufacturing pilot-plant. The proposed control architecture has the potential to control tablet weight and tablet breaking force simultaneously by systematically decoupling and cascading the control loops. The model predictive control algorithm was experimentally found to be superior to the PID (proportional, integral and derivative) controller and thus, can be utilized for a wide range of applications to improve the quality of pharmaceutical products in continuous manufacturing. The MPC was used to control main compression force and pre compression force using main compression height and fill depth respectively as the actuators. The introduction of this methodology leads to new ways of developing MPC models, tablet weight measurement methods and control strategies that enhance the manufacturability and quality of pharmaceutical tablets.

Journal

International Journal of Pharmaceutics. Volume 534, 2017, 159-178

DOI

10.1016/j.ijpharm.2017.10.003

Type of publication

Peer-reviewed journal

Affiliations

  • Rutgers, The State University of New Jersey

Article Classification

Research Article

Classification Areas

  • Oral doses
  • Modeling

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