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Technoeconomic Optimization of Continuous Crystallization for Three Active Pharmaceutical Ingredients: Cyclosporine, Paracetamol, and Aliskiren

By Diab, S; Gerogiorgis, DI

Published on

Abstract

Mixed suspension, mixed product removal (MSMPR) crystallizers are widely implemented for the continuous crystallization of active pharmaceutical ingredients (APIs), allowing enhanced efficiency, flexibility, and product quality compared to currently dominant batch crystallizer designs. Establishing cost-effective continuous crystallization process configurations for societally and economically important APIs is essential to ensure the successful implementation of end-to-end continuous pharmaceutical manufacturing (CPM) campaigns. Process modeling and optimization allow rapid, systematic comparative technoeconomic evaluations. This paper pursues total cost minimization of different crystallizer configurations of three APIs-cyclosporine, paracetamol, and aliskiren hemifumarate-whose continuous MSMPR crystallization has been experimentally demonstrated. Nonlinear optimization for total cost minimization is implemented for one to three crystallizers for different plant API capacities with crystallizer temperatures and residence times as decision variables. Optimization results show that the optimal number of crystallizers is dependent on plant capacity; implementing one crystallizer is preferred for all three APIs at 10(2) kg year(-1) while multiple crystallizer implementation is more cost-beneficial at increased capacities. These trends are observed due to the increasing dominance of operating expenditures on total costs at increased capacities, making the benefits of implementing more crystallizers (enhanced yields, reduced utility loads) worth the increased capital expenditures. Process modeling and optimization allows rapid technoeconomic evaluation of MSMPR crystallizer configurations for different APIs toward systematic selection of optimal continuous crystallizer designs for continuous manufacturing.

Journal

Industrial & Engineering Chemistry Research. Volume 57, 2018, 9489-9499

DOI

10.1021/acs.iecr.8b00679

Type of publication

Peer-reviewed journal

Affiliations

  • University of Edinburgh

Article Classification

Research Article

Classification Areas

  • API
  • Modeling

Tags