Aniruddha Majumder

Model Development and Experimental Validation for Crystal Shape Control by Using Tailored Mixtures of Crystal Growth Modifiers

Abstract The quality of crystalline products is often determined by the shape distribution, because its significant effect on downstream processes as well as on biological activity. Thus, controlling the crystal shape is important, especially in the pharmaceutical industry. In this work, we describe a new methodology of investigation, simulation and control of the crystal shape by using tailored mixtures of crystal growth modifiers (CGM). Particle Vision Measurement (PVM) and image analysis were applied to track the shape in real time. The effect of CGMs on the morphology is investigated by combining the growth kinetic model with competitive adsorption mechanism of the CGMs on the crystal face and their incorporation in the population balance model (PBM). The model parameters are identified using experimental data. The process simulator is proven to be an effective tool for investigating the process and calculation of the required CGM concentrations to achieve desired crystal shape.

Population balance model based multi-objective optimization and robustness analysis of a continuous plug flow antisolvent crystallizer

Crystallization is a major separation process in the pharmaceutical industry. Most crystallizations are performed batchwise, but there is great incentive for switching to continuous operation. We have investigated the modeling, simulation, optimization, and robustness of a multi-segmented, multi-addition plug-flow crystallizer (MSMA-PFC). The design accepts multiple antisolvent flows along its length, permitting localized control of supersaturation. A mass balance equation was used to track the depletion of dissolved solute (flufenamic acid), and a population balance equation for tracking the crystal size distribution. Multiobjective optimization was done using the antisolvent flowrates into each segment as decision variables. The genetic algorithm was used to calculate the Pareto frontiers for the two competing objectives of maximizing average crystal size (L43), and minimizing coefficient of variation (CV). The sensitivity of the Pareto frontier to variation in the growth and nucleation kinetic parameters was investigated. The robustness of a single solution was examined as well with respect to error in the kinetic parameters, as well as to errors in antisolvent flowrate.

A Comparative Study of Coupled Preferential Crystallizers for the Efficient Resolution of Conglomerate-Forming Enantiomers

The separation of enantiomers is of great importance due to their possible differences in therapeutic properties. Preferential crystallization in various configurations of coupled batch crystallizers is used as an attractive means to separate the conglomerate-forming enantiomers from racemic mixtures. However, the productivity of such batch processes can be limited by the nucleation of the counter enantiomer and consumption of the supersaturation. In this work, a recently proposed process configuration, which uses coupled mixed suspension mixed product removal (MSMPR) with liquid phase exchange, is investigated by simulation studies. A detailed study on the effect of process parameters (e.g., feed flow rate, seed mass, and liquid phase exchange) on the productivity and yield of the coupled MSMPR has been presented. Moreover, a comparison of various coupled crystallizer configurations is carried out. It is shown through simulation studies that the productivity of the enantiomeric separation can be significantly improved compared to the previously proposed batch modes when the continuous configuration is used. The effect of nucleation kinetic parameters on the performances of various crystallizer configurations is studied as well. A set of coupled population balance equations (PBEs) was used to describe the evolution of the crystal phase of the both enantiomers in each vessel. These equations were solved numerically using the quadrature method of moments. The insights obtained in this study will be useful in the process design of coupled crystallizer systems.

Spatially Distributed Fines Removal in a Continuous Plug Flow Crystallizer by Optimal Temperature Profile with Controlled Dissolution

Abstract A systematic study for obtaining the optimal temperature profile in a continuous plug flow crystallizer (PFC) is presented. The PFC consists of multiple segments where the temperature of the each segment can be controlled individually. An optimization problem is formulated for a target crystal size distribution (CSD) (without fines) with the temperature of the PFC segments as decision variables. It is found that for the crystallization kinetics considered here, the optimal temperature profile also introduces dissolution steps so that the crystal fines due to secondary nucleation can be reduced significantly. A systematic study on the growth and dissolution kinetics is also performed. This study suggests that the key factor that determines whether the dissolution steps will be successful in reducing fines (without compromising the final size of the crystals from seed) is the size dependence of the growth and dissolution kinetics. If kinetics of the system is such that the larger crystals grow faster than the smaller ones and the smaller crystals dissolve faster than the larger ones, best results for fines removal is achieved. On the other hand, when both the growth and dissolution kinetics are independent of crystal size, fines removal found to be ineffective by temperature cycling. These findings will be very useful in enhancing the understanding of the continuous crystallization processes in an industrial perspective