Model-Based Optimal Strategies for Controlling Particle Size in Antisolvent Crystallization Operations

Abstract

In this paper, a model-based optimal strategy is presented for the control of particle size in antisolvent crystallization. Size is controlled on demand by dynamic optimization using a population balance based model. Knowledge of the ternary solute-solvent-antisolvent equilibrium and crystallization kinetics is crucial in this strategy, and these are thus incorporated in the model. The optimization is capable of determining the optimal antisolvent feed profile that achieves a desired particle size. Experimental validation of the strategy is carried out and presented herein. Such a strategy stands as a key solution to antisolvent operations ubiquitous in the pharmaceutical and fine chemicals industries.

A stochastic formulation for the description of the crystal size distribution in antisolvent crystallization processes

“…A detailed description of the experimental set-up and the experimental procedures were reported elsewhere. 5,10 Here, suffice to say that, in all experiments, purified water by a Milli-Q system was used. The purities of sodium chloride (NaCl) salt (Merck) and ethanol (Merck) used in the experiments were 99.5% and 99.9%, respectively.…”

Design and optimization of a multistage continuous cooling mixed suspension, mixed product removal crystallizer

“…Currently batch crystallization is the preferred mode of operation in the pharmaceutical industry and the design of such crystallizers is well understood for cooling (Worlitschek and Mazzotti, 2004;Choong and Smith, 2004a), antisolvent (Ó'Ciardhá et al, 2012;Nowee et al, 2008) and reactive precipitation (Choong and Smith, 2004b). Although the design criteria have been well established for a batch crystallizer, there still exists a problem with batch to batch variation which can lead to inconsistent product which can ultimately be out-ofspecification (Lawton et al, 2009).…”

Time evolution of the PSD in crystallization operations: An analytical solution based on Ornstein‐Uhlenbeck process

“…[1][2][3][4][5][6] The development of effective mathematical models describing the crystal growth dynamics is a crucial issue toward finding the optimal process performance and to control the crystal size and distribution. [1][2][3][4][5][6] The development of effective mathematical models describing the crystal growth dynamics is a crucial issue toward finding the optimal process performance and to control the crystal size and distribution.…”