DEM-CFD investigation of particle residence time distribution in top-spray fluidised bed granulation

CFD-DEM simulation of particle coating process coupled with chemical reaction flow model

Particle coating process, one of the main methods to improve the particle properties, is widely used in industrial production and pharmaceutical industry. For the scale up and optimization of this process, a mechanistic and detailed study is needed or numerical simulation as an alternative way. Decomposition of substances usually involves multiple chemical reactions and produces multiple substances in the actual chemical reaction. In the study, a chemical reaction flow (CRF) model has been established based on kinetic mechanism of elementary reaction, the theory of molecular thermodynamics and the sweep theory. It was established with the comprehensive consideration of the decomposition of substances, deposition process, adhesion process, desorption process, hydrogen inhibition, and clearance effect. Then the CFD-DEM model was coupled with CRF model to simulate particle coating process by FB-CVD method, and the CFD-DEM-CRF coupling model was implemented in the software Fluent-EDEM with their user definition function (UDF) and application programming interface (API). The coating process in the spouted bed was analyzed in detail and the coating behavior under different conditions were compared at the aspects of CVD rate, coating efficiency, particle concentration distribution, particle mixing index and gas concentration distribution. It is found that the average CVD rate is 6.06 × 10−4 mg/s when the inlet gas velocity is 11 m/s and bed temperature is 1273 K, and simulation result agrees with the experimental result well. Average CVD rate and coating efficiency increase with temperature increasing, but decrease acutely with mass fraction of injected hydrogen increasing. The CFD-DEM-CRF coupling model can be developed as a basic model for investigating particle coating process in detail and depth and can provide some guidance for the operating conditions and parameters design of the spouted bed in the real coating process.

CFD-DEM -DDM Model for Spray Coating Process in a Wurster Coater

A multiscale model by coupling computational fluid dynamics (CFD) with a discrete element model (DEM) and discrete droplet model (DDM) is developed to simulate a lab-scale Wurster coater. Two case studies are conducted to study the effect of particle shape in the system. In the first case study, 45,000 spherical particles are coated for 5 s while for the second case study, a mixture of 22,500 spherical particles and 22,500 cylindrical particles is simulated. The residence time distributions (RTD) of particles in different spray zones are compared, and the best spray zone is derived by analysing the positions of spray droplet-particle contacts. The simulation results show that the RTD of the particles within an accurate spray zone can provide valuable information on the final product's particles size distribution. Furthermore, the coefficient of variation (COV) for the coating mass received by the particles is studied for both case studies.

CFD-DEM Simulation of a Coating Process in a Fluidized Bed Rotor Granulator

Coating of particles is a widely used technique in order to obtain the desired surface modification of the final product, e.g., specific color or taste. Especially in the pharmaceutical industry, rotor granulators are used to produce round, coated pellets. In this work, the coating process in a rotor granulator is investigated numerically using computational fluid dynamics (CFD) coupled with the discrete element method (DEM). The droplets are generated as a second particulate phase in DEM. A liquid bridge model is implemented in the DEM model to take the capillary and viscous forces during the wet contact of the particles into account. A coating model is developed, where the drying of the liquid layer on the particles, as well as the particle growth, is considered. The simulation results of the dry process compared to the simulations with liquid injection show an important influence of the liquid on the particle dynamics. The formation of liquid bridges and the viscous forces in the liquid layer lead to an increase of the average particle velocity and contact time. Changing the injection rate of water has an influence on the contact duration but no significant effect on the particle dynamics. In contrast, the aqueous binder solution has an important influence on the particle movement.

Model-Based Scale-Up Methodologies for Pharmaceutical Granulation

In the pharmaceutical industry, it is a major challenge to maintain consistent quality of drug products when the batch scale of a process is changed from a laboratory scale to a pilot or commercial scale. Generally, a pharmaceutical manufacturing process involves various unit operations, such as blending, granulation, milling, tableting and coating and the process parameters of a unit operation have significant effects on the quality of the drug product. Depending on the change in batch scale, various process parameters should be strategically controlled to ensure consistent quality attributes of a drug product. In particular, the granulation may be significantly influenced by scale variation as a result of changes in various process parameters and equipment geometry. In this study, model-based scale-up methodologies for pharmaceutical granulation are presented, along with data from various related reports. The first is an engineering-based modeling method that uses dimensionless numbers based on process similarity. The second is a process analytical technology-based modeling method that maintains the desired quality attributes through flexible adjustment of process parameters by monitoring the quality attributes of process products in real time. The third is a physics-based modeling method that involves a process simulation that understands and predicts drug quality through calculation of the behavior of the process using physics related to the process. The applications of these three scale-up methods are summarized according to granulation mechanisms, such as wet granulation and dry granulation. This review shows that these model-based scale-up methodologies provide a systematic process strategy that can ensure the quality of drug products in the pharmaceutical industry.

Empirical prediction model based process optimization for droplet size and spraying angle during pharmaceutical fluidized bed granulation

The objective of this study was to predict the droplet size and the spraying angle during the process of binder atomization in pharmaceutical fluidized bed granulation using an empirical model. The effects of the binder viscosity, the atomization pressure, and the spray rate on the droplet size and the spraying angle were investigated using a response surface central composite design and analysis of variance. Prediction models for droplet size and spraying angle were then established using stepwise regression analysis and were validated by comparing the measured and predicted values. The results showed that the droplet size model and the spraying angle model were well established, with an R² of 0.93 (p < 0.0001) and a root mean square error (RMSE) of 10.10, and an R² of 0.82 (p < 0.0001) and an RMSE of 3.69, respectively. The error between the measured and predicted values of the droplet size and the spraying angle were less than 10%, indicating that the established models were accurate. The results of the present study were significant in predicting the droplet size and spraying angle in the process of pharmaceutical fluidized bed granulation.

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product quality. A commonly used mechanistic modeling approach for powder is the discrete element method (DEM). Most pharmaceutical materials have powder or granular material. Therefore, DEM might be widely applied in the pharmaceutical industry. This review focused on the basic elements of DEM and its implementations in pharmaceutical manufacturing simulation. Contact models and input parameters are essential elements in DEM simulation. Contact models computed contact forces acting on the particle-particle and particle-geometry interactions. Input parameters were divided into two types-material properties and interaction parameters. Various calibration methods were presented to define the interaction parameters of pharmaceutical materials. Several applications of DEM simulation in pharmaceutical manufacturing processes, such as milling, blending, granulation and coating, were categorized and summarized. Based on this review, DEM simulation might provide a systematic process understanding and process control to ensure the quality of a drug product.