(394g) Direct Design of Batch Recipes and Concentration Control in Antisolvent and Polymorphic Crystallizations | AIChE

(394g) Direct Design of Batch Recipes and Concentration Control in Antisolvent and Polymorphic Crystallizations


Wubben, T. J. - Presenter, University of Illinois at Urbana-Champaign
Woo, X. Y. - Presenter, University of illinois, National University of Singapore
Fujiwara, M. - Presenter, University of Illinois at Urbana-Champaign
Kee, N. - Presenter, National University of Singapore
Tan, R. B. H. - Presenter, The National University of Singapore

Increasing emphasis is being placed on designing and operating pharmaceutical crystallizers so as to produce a robust and consistent crystal product [1]. In batch crystallization in industry, usually the recipe is designed to follow a temperature and/or antisolvent addition profile. Rigorous determination of an optimal batch recipe requires accurate growth and nucleation kinetics, which can be determined in a series of continuous or batch experiments [2-4]. For agglomerating and other complex crystallization systems, it can be difficult to determine kinetics that are accurate enough to compute an optimal batch recipe. These complications have resulted in the common industrial practice of trial-and-error experimentation to design batch recipes for pharmaceutical crystallization. An alternative approach that does not require accurate kinetics or trial-and-error experimentation is to control the crystallizer so that it follows a supersaturation profile in the metastable zone [5-8]. The advantage of this approach is its lower sensitivities to most practical disturbances and to variations in the nucleation and growth kinetics, and that this method does not require the derivation of first-principles models and the associated determination of crystallization kinetics [9].

This paper describes applications of a concentration control system to follow a setpoint supersaturation profile in the metastable zone for batch antisolvent and polymorphic crystallizations. This is an expansion of past studies in cooling crystallization, in which an automated system [5,8,10] was implemented that determined the metastable limit and the solubility curve using the Lasentec FBRM [11-13] and ATR-FTIR spectroscopy [5-8,13] coupled with chemometrics [14-16]. In the concentration feedback control system, the supersaturation is calculated from the in-process solution concentration measurement (using ATR-FTIR spectroscopy coupled with chemometrics) and a previously measured saturation concentration, which is obtained using an automated system [5,8,10]. The crystallizer follows the setpoint supersaturation profile by adjusting the cooling or antisolvent addition rate based on the concentration measurement. The batch recipe is implemented so that the cooling or antisolvent addition rate is an algebraic function of the supersaturation defined by the setpoint profile, and so is very easy to implement and requires no control tuning [9].

Both simulations and experiments demonstrate the robust performance obtained by the proposed concentration-control method for the design and implementation of batch recipes for antisolvent and polymorphic crystallization. The implementation in Visual Basic was designed so that the metastable zone determination and batch recipe design can operate in an automated manner, while providing a graphical user interface so that experts can choose to make adjustments based on their level of expertise.


[1] X. L. Yu, R. A. Lionberger, A. S. Raw, R. D'Costa, H. Q. Wu, A. S. Hussain, Applications of process analytical technology to crystallization processes, Advanced Drug Delivery Reviews, 56, 349, 2004.

[2] T. Togkalidou, H. H. Tung, Y. Sun, A. T. Andrews, and R. D. Braatz, Parameter estimation and optimization of a loosely bound aggregating pharmaceutical crystallization using in situ infrared and laser backscattering measurements, Ind. Eng. Chem. Res., 43, 6168, 2004.

[3] J. Worlitschek and M. Mazzotti, Model-based optimization of particle size distribution in batch-cooling crystallization of paracetamol, Crystal Growth & Design, 4, 891, 2004.

[4] S. M. Miller and J. B. Rawlings, Model Identification and Control Strategies for Batch Cooling Crystallizers, AIChE J., 40, 1312, 1994.

[5] M. Fujiwara, P. S. Chow, D. L. Ma, and R. D. Braatz, Paracetamol crystallization using laser backscattering and ATR-FTIR spectroscopy: Metastability, agglomeration, and control, Crystal Growth & Design, 2, 363, 2002.

[6] H. Gron, A. Borissova, and K. J. Roberts. In-process ATR-FTIR spectroscopy for closed-loop supersaturation control of a batch crystallization producing monosodium glutamate crystals of defined size, Ind. Eng. Chem. Res., 42, 198, 2003.

[7] L. L. Feng and K. A. Berglund. ATR-FTIR for determining optimal cooling curves for batch crystallization of succinic acid. Crystal Growth & Design, 2, 449, 2002.

[8] V. Liotta and V. Sabesan, Monitoring and feedback control of supersaturation using ATR-FTIR to produce an active pharmaceutical ingredient of a desired crystal size, Org. Proc. Res. Dev., 8, 488, 2004.

[9] M. Fujiwara, Z. K. Nagy, J. W. Chew, and R. D. Braatz. First-principles and direct design approaches for the control of pharmaceutical crystallization. J. of Process Control, 15, 493, 2005.

[10] A. R. Parsons, S. N. Black, and R. Colling, Automated measurement of metastable zones for pharmaceutical compounds, Chem. Eng. Res. Des., 81, 700, 2003.

[11] L. Lafferrere, C. Hoff, and S. Veesler, In situ monitoring of the impact of liquid-liquid phase separation on drug crystallization by seeding, Crystal Growth & Design, 4, 1175, 2004.

[12] K. Pollanen, A. Hakkinen, S. P. Reinikainen, et al., ATR-FTIR in monitoring of crystallization processes: comparison of indirect and direct OSC methods, Chemom. Int. Lab. Syst., 76, 25, 2005.

[13] N. Doki, H. Seki, K. Takano, H. Asatani, M. Yokota, and N. Kubota, Process control of seeded batch cooling crystallization of the metastable alpha-form glycine using an in-situ ATR-FTIR spectrometer and an in-situ FBRM particle counter, Crystal Growth & Design, 4, 949, 2004.

[14] T. Togkalidou, H.-H. Tung, Y. Sun, A. Andrews, and R. D. Braatz. Solution concentration prediction for pharmaceutical crystallization processes using robust chemometrics and ATR FTIR spectroscopy. Org. Process Res. Dev., 6:317-322, 2002.

[15] T. Togkalidou, M. Fujiwara, S. Patel, and R. D. Braatz. Solute concentration prediction using chemometrics and ATR-FTIR spectroscopy. J. of Crystal Growth, 231, 534, 2001.

[16] D. R. Thompson, E. Kougoulos, A. G. Jones, and M. W. Wood-Kaczmar, Solute concentration measurement of an important organic compound using ATR-UV spectroscopy, J. of Crystal Growth, 276, 230, 2005.