Download Modelling pharmaceutical crystallisation processes

British Association For Crystal Growth Annual Conference 2017
Modelling pharmaceutical crystallisation processes using a coupled
CFD-Population balance approach
D. M. Camacho, C. Y. Ma, T. Mahmud, and K. J. Roberts
School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
Corresponding. [email protected]
Crystallisation is an essential process for the isolation and purification of APIs, thus the design of a crystalliser
and selection of operating conditions are vital for obtaining crystals with the desired physical properties, such
as crystal size distribution (CSD), morphology and purity. Currently extensive laboratory and pilot-scale testing
are used for the development of crystallisation processes in order to enhance particle attributes, whereas
quality by design (QbD) now provides a methodology which has the potential to significantly reduce the product
development cost and time-to-market through the use of first principles based modelling tools.
Traditionally, lumped-parameter mechanistic modelling approaches are used for predicting CSD in batch
agitated crystallisers which assume perfectly mixed conditions in the reactor. However, it is well known that
relevant hydrodynamic quantities and temperature can vary significantly throughout the vessel, which can lead
to the incorrect estimation of nucleation and crystal growth rates and in turn CSD. In addition to this, the
crystallisation kinetics is also dependent on hydrodynamic parameters such as turbulent kinetic energy, shear
and energy dissipation rates, therefore a precision design tool for process development and scale up requires
a detailed knowledge of the distribution of these parameters. Accordingly, it is necessary to use a high-level
distributed-parameter model based on computational fluid dynamics (CFD) to capture non-uniform flow and
temperature distributions in the crystalliser.
This study is concerned with the development of a fully coupled CFD and population balance modelling (PBM)
tool for batch cooling crystallization processes. This modelling approach is applied to the crystallisation of Lglutamic acid (LGA) in a 20 L crytalliser equiped with a retreat curve impeller (RCI) and a single cylindrical
baffle [1,2], which is a typical reactor configuration used in the pharmaceutical industry. The first stage of the
work focuses on the development of an accurate CFD methodology based on our previous studies [e.g., 3]
that can be coupled with the PBM in oder to assess the inter-relationship between the distribution of
hydrodynamic parameters within the reactor and the evolution of CSD. Through this assesment relevant
hydrodynamic parameters can be incorporated into first principles models describing nucleation and crystal
growth processes within the PBM.
Extensive CFD simulations were carried out using the Shear Stress Transport (SST) and Reynold-stress
Transport (RST) models of turbulence without and with the volume-of-fluid (VOF) method for capturing the
shape of the liquid free surface. These predictions were validated against detailed velocity measurements
carried out using laser doppler anemometry (LDA) [1]. The simulation results reveal that improved predictions
are generated using the RST model coupled with the VOF approach compared to those using the SST model
with a flat liquid surface as used in the previous study [1]. As illustrated in Fig. 1, a single baffle is unable to
supress vortex formation completely, particularly at a higher impeller speed while the vortex depth increases
as a function of the impeller speed. Comparisons between the predicted mean axial, radial and tangential
velocities obtained using the RST model with and without VOF and the experimental data confirm that an
accurate representation of the liquid free surface is essential for improved predictions of the flow field as
depicted in Fig. 2.
British Association For Crystal Growth Annual Conference 2017
Fig. 1: Predicted vortex profiles at 100,150 and 250 rpm
Fig. 2: Predicted and measured mean velocity components at 100 rpm at selected heights (●) LDA data, CFD
with VOF (▬) and with flat surface (▬)
The developed CFD methodology is coupled with a 1-dimensional PBM and applied to simulate spontaneous
batch cooling crystallisation of LGA from aqueous solutions carried out at a cooling rate of 0.6°C/min. The
nucleation and crystal growth kinetic parameters were obtained from literature [4] and also determined from
experiments in a 2 L crystallizer [2]. The estimated final product CSDs are validated against experimental data
collected via ultrasonic spectroscopy at different impeller speeds (100, 150, 200 and 250 rpm) [2]. The
predicted distributions of solution temperature, solute concentartion and supersturation provide an improved
insight into the effect of hydrodynamics on the crystallisation process.
References:
[1] M.Z. Li, G. White, D. Wilkinson, K.J. Roberts, LDA Measurements and CFD Modeling of a Stirred Vessel with a Retreat
Curve Impeller, Ind Eng Chem Res, 43 (2004) 6534-6547.
[2] K. Liang, Process Scale Dependence of L-glutamic Acid Batch Crystallised from Aqueous Solution in relation to Reactor
Internals, Reactant Mixing and Process Conditions, Department of Chemical Engineering, Heriot-Watt University,
Edinburgh, 2002.
[3] J.N. Haque, T. Mahmud, K.J. Roberts, J.K. Liang, G. White, D. Wilkinson, D. Rhodes, Free-Surface Turbulent Flow
Induced by a Rushton Turbine in an Unbaffled Dish-Bottom Stirred Tank Reactor: LDV Measurements and CFD
Simulations, Can J Chem Eng, 89 (2011) 745-753.
[4] L. J Shaikh, A. H. Bari, V.V. Ranade, A.B. Pandit, Generic Framework for Crystallization Processes Using the Population
Balance Model and its Application, Ind. Eng. Chem. Res., 54 (2015) 10539-10548.