Plant-wide model predictive control for a continuous pharmaceutical process

Abstract

Integrated continuous manufacturing offers ample opportunities for efficient and cost-effective pharmaceutical processes. Plant-wide control is required for meeting the stringent regulatory requirements on quality attributes of products in continuous pharmaceutical manufacturing processes. This paper investigates plant-wide model predictive control (MPC) of an end-to-end continuous pharmaceutical manufacturing process with nearly 8000 state variables. The process includes two series of chemical synthesis and crystallization steps, followed by tablet formation steps. A subspace identification approach is adopted to obtain a linear low-dimensional description of the complex plant-wide dynamics. Quadratic dynamic matrix control algorithm is used to enable input-output formulation of the control problem, whose online computational cost is independent of the state dimension. The performance of the plant-wide MPC system is evaluated in a closed-loop setting with an existing nonlinear plant simulator equipped with a stabilizing control layer. The closed-loop simulation results demonstrate the ability of plant-wide MPC to facilitate flexible process operation and effective regulation of quality attributes of tablets.