No More Than Three: Technoeconomic Mixed Integer Nonlinear Programming Optimization of Mixed Suspension, Mixed Product Removal Crystallizer Cascades for Melitracen, an Antidepressant API

Abstract

Mixed Suspension, Mixed Product Removal (MSMPR) crystallizers have been considered in numerous cases as a continuous mode of operation in the production of Active Pharmaceutical Ingredients (APIs). The steady-state continuous MSMPR crystallization of melitracen via cooling has been recently demonstrated in the literature, with crystallization kinetic parameters regressed from experimental data. Mixed Integer Nonlinear Programming (MINLP) has been implemented extensively for the optimization of separation process designs in various manufacturing sectors, but not for systematic design and screening of MSMPR cascade flowsheet configurations. This study performs MINLP optimization to maximize the Net Present Value (NPV) of a MSMPR cascade for continuous melitracen crystallization with solids recycle. Process flowsheets consider varying numbers of crystallizers and recycle stream feed point location. First, the MSMPR model describing API solubility, crystallization kinetics, population balance equations and process mass balances are described. The MINLP problem and constraints are then described with detailed costing equations. The optimal flowsheet configuration for both considered plant capacities (10 3 and 10 4 kg API yr -1 ) is three crystallizers with recycle fed to the first and last vessels. This study illustrates the utility of rapid screening of continuous crystallization cascades via MINLP optimization to facilitate process development towards fully Continuous Pharmaceutical Manufacturing (CPM) plant designs.

Techno‐economic analysis of dynamic, end‐to‐end optimal pharmaceutical campaign manufacturing using PharmaPy

“…Just like labor costs are difficult to quantify in OPEX as operating modes and capacity are changed. Furthermore, capital expenditures are presented here to allow comparing different process alternatives, and might result in underestimation of equipment costs, for which vendor‐specific data and different costing account methods are available in the literature for processes similar to the one studied in this work 32,33 …”

Mathematical Modeling and Optimization to Inform Impurity Control in an Industrial Active Pharmaceutical Ingredient Manufacturing Process

“…This can also be used for in silico sensitivity analysis and optimization. In an industrial context, this can mean enhanced process understanding, reduced material consumption, and potential cost savings …”

“…In an industrial context, this can mean enhanced process understanding, reduced material consumption, and potential cost savings. 16 Various demonstrations of modeling for impurity control exist in the literature. Reaction kinetics models are frequently used for modeling scenarios of impurity and degradant formation.…”

Theoretical Feedback Control Scheme for the Ultrasound-Assisted Continuous Antisolvent Crystallization of Aspirin in a Tubular Crystallizer

“…Last but not least, Diab and Gerogiorgis optimized the operating conditions for Melitracen production with the use of a techno-economic mixed integer nonlinear programming optimization of mixed-suspension and mixedproduct removal crystallizer cascades. 16 Following the above progress on modeling and control of crystallization systems for aspirin-based applications, two main issues need to be tackled. The first is the proper and accurate dynamic modeling of the ultrasound-assisted continuous antisolvent crystallization.…”

“…A rather interesting approach was also presented by Kwon et al There, a feedforward controller was applied toward crystal shape and size with an aim to alleviate emerged disturbances. Last but not least, Diab and Gerogiorgis optimized the operating conditions for Melitracen production with the use of a techno-economic mixed integer nonlinear programming optimization of mixed-suspension and mixed-product removal crystallizer cascades …”