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Dynamic flowsheet model development and sensitivity analysis of a continuous pharmaceutical tablet manufacturing process using the wet granulation route

By Metta, Nirupaplava; Ghijs, Michael Schäfer, Elisabeth Kumar, Ashish Cappuyns, Philippe Van Assche, Ivo Singh, Ravendra Ramachandran, Rohit De Beer, Thomas; Ierapetritou, Marianthi

Published on

Abstract

In view of growing interest and investment in continuous manufacturing, the development and utilization of mathematical model(s) of the manufacturing line is of prime importance. These models are essential for understanding the complex interplay between process-wide critical process parameters (CPPs) and critical quality attributes (CQAs) beyond the individual process operations. In this work, a flowsheet model that is an approximate representation of the ConsiGma TM -25 line for continuous tablet manufacturing, including wet granulation, is developed. The manufacturing line involves various unit operations, i.e., feeders, blenders, a twin-screw wet granulator, a fluidized bed dryer, a mill, and a tablet press. The unit operations are simulated using various modeling approaches such as data-driven models, semi-empirical models, population balance models, and mechanistic models. Intermediate feeders, blenders, and transfer lines between the units are also simulated. The continuous process is simulated using the flowsheet model thus developed and case studies are provided to demonstrate its application for dynamic simulation. Finally, the flowsheet model is used to systematically identify critical process parameters (CPPs) that affect process responses of interest using global sensitivity analysis methods. Liquid feed rate to the granulator, and air temperature and drying time in the dryer are identified as CPPs affecting the tablet properties.

Journal

Processes. Volume 7, 2019, 234

DOI

10.3390/pr7040234

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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