Characterization of Simultaneous Evolution of Size and Composition Distributions Using Generalized Aggregation Population Balance Equation

Modeling and Optimization of the Para-Xylene Continuous Suspension Crystallization Separation Process via a Morphology Technique and a Multi-Dimensional Population Balance Equation

In this study, we carried out a para-xylene crystallization experiment at constant temperature and concentration levels. Throughout the process, the kinetics of nucleation, growth, breakage, and aggregation of para-xylene particles were measured and built using a morphological approach. An additional a three-stage continuous suspension crystallization separation experiment was carried out, the process for which was simulated using the population balance model based on correlated kinetic equations. The population balance equation was solved using an extended moment of classes algorithm, and the solving process was implemented in MATLAB. In this case, the predicted particle size distribution of the products matched well with the experiment. In order to provide references for the optimization of the industrial para-xylene crystallization process, a three-stage suspension crystallization separation experiment was designed and conducted, in which each crystallizer had a distinct operating temperature and mean residence time. The effects of operating parameters on the final product were investigated further. The proposed models and algorithms can also be applied in other cases and provide an alternative approach for optimizing continuous crystallization processes.

Advances in numerical simulation of unit operations for tablet preparation

Recently, there has been an increase in the use of numerical simulation technology in pharmaceutical preparation processes. Numerical simulation can contribute to a better understanding of processes, reduce experimental costs, optimize preparation processes, and improve product quality. The intermediate material of most dosage forms is powder or granules, especially in the case of solid preparations. The macroscopic behavior of particle materials is controlled by the interactions of individual particles with each other and surrounding fluids. Therefore, it is very important to analyze and control the microscopic details of the preparation process for solid preparations. Since tablets are one of the most widely used oral solid preparations, and the preparation process is relatively complex and involves numerous units of operation, it is especially important to analyze and control the tablet production process. The present paper discusses recent advances in numerical simulation technology for the preparation of tablets, including drying, mixing, granulation, tableting, and coating. It covers computational fluid dynamics (CFD), discrete element method (DEM), population balance model (PBM), finite element method (FEM), Lattice-Boltzmann model (LBM), and Monte Carlo model (MC). The application and deficiencies of these models in tablet preparation unit operations are discussed. Furthermore, the paper provides a systematic reference for the control and analysis of the tablet preparation process and provides insight into the future direction of numerical simulation technology in the pharmaceutical industry.

New Discrete Formulation for Reduced Population Balance Equation: An Illustration to Crystallization

In this paper, we focus on providing a discrete formulation for a reduced aggregation population balance equation. The new formulation is simpler, easier to code, and adaptable to any type of grid. The presented method is extended to address a mixed-suspension mixed-product removal (MSMPR) system where aggregation and nucleation are the primary mechanisms that affect particle characteristics (or distributions). The performance of the proposed formulation is checked and verified against the cell average technique using both gelling and non gelling kernels. The testing is carried out on two benchmarking applications, namely batch and MSMPR systems. The new technique is shown to be computationally less expensive (approximately 40%) and predict numerical results with higher precision even on a coarser grid. Even with a revised grid, the new approach tends to outperform the cell average technique while requiring less computational effort. Thus the new approach can be easily adapted to model the crystallization process arising in pharmaceutical sciences and chemical engineering.

Improvement of a 1D Population Balance Model for Twin-Screw Wet Granulation by Using Identifiability Analysis

Recently, the pharmaceutical industry has undergone changes in the production of solid oral dosages from traditional inefficient and expensive batch production to continuous manufacturing. The latest advancements include increased use of continuous twin-screw wet granulation and application of advanced modeling tools such as Population Balance Models (PBMs). However, improved understanding of the physical process within the granulator and improvement of current population balance models are necessary for the continuous production process to be successful in practice. In this study, an existing compartmental one-dimensional PBM of a twin-screw granulation process was improved by altering the original aggregation kernel in the wetting zone as a result of an identifiability analysis. In addition, a strategy was successfully applied to reduce the number of model parameters to be calibrated in both the wetting zone and kneading zones. It was found that the new aggregation kernel in the wetting zone is capable of reproducing the particle size distribution that is experimentally observed at different process conditions as well as different types of formulations, varying in hydrophilicity and API concentration. Finally, it was observed that model parameters could be linked not only to the material properties but also to the liquid to solid ratio, paving the way to create a generic PBM to predict the particle size distribution of a new formulation.