DEM analysis of residence time distribution during twin screw granulation

Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map

Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism.

Experimental Study on the Agglomeration Behavior of Elongated Biomass Particles in a Lifting Tube

Pneumatic conveying devices are commonly used in the fields of chemical industry, raw material transportation, and material processing. Elongated biomass particles are not evenly distributed in the lifting tube because biomass clumps during conveying. Pneumatic conveying test setup and measurement system were built in this paper in order to study the agglomeration behavior of elongated biomass particles in the lifting tube experimentally. Particle tracking velocimetry (PTV) was used to determine the area distribution and velocity distribution of particles at different apparent air velocities and mass flow rates. The results show that while keeping the mass flow rate constant at 46.50 g/s, the apparent gas velocity increased from 5.91 to 7.91 m/s and the maximum size of agglomerates decreased from 0.689 to 0.235. The apparent gas velocity was kept at 6.40 m/s, and the particle mass flow rate was adjusted from 56.50 to 16.20 g/s. The maximum size of the agglomerates was reduced to 0.115. Therefore, appropriately increasing the apparent gas velocity or decreasing the particle mass flow rate can improve the uniformity of the particle distribution in the lifting tube. The results would provide a reference for parameter adjustment of pneumatic conveying devices in industrial production.

Pharmaceutical Application of Process Understanding and Optimization Techniques: A Review on the Continuous Twin-Screw Wet Granulation

Twin-screw wet granulation (TSWG) is a method of continuous pharmaceutical manufacturing and a potential alternative method to batch granulation processes. It has attracted more and more interest nowadays due to its high efficiency, robustness, and applications. To improve both the product quality and process efficiency, the process understanding is critical. This article reviews the recent work in process understanding and optimization for TSWG. Various aspects of the progress in TSWG like process model construction, process monitoring method development, and the strategy of process control for TSWG have been thoroughly analyzed and discussed. The process modeling technique including the empirical model, the mechanistic model, and the hybrid model in the TSWG process are presented to increase the knowledge of the granulation process, and the influence of process parameters involved in granulation process on granule properties by experimental study are highlighted. The study analyzed several process monitoring tools and the associated technologies used to monitor granule attributes. In addition, control strategies based on process analytical technology (PAT) are presented as a reference to enhance product quality and ensure the applicability and capability of continuous manufacturing (CM) processes. Furthermore, this article aims to review the current research progress in an effort to make recommendations for further research in process understanding and development of TSWG.

Optimal quantification of residence time distribution profiles from a quality assurance perspective

Residence time distribution (RTD) has been widely applied across various fields of chemical engineering, including pharmaceutical manufacturing, for applications such as material traceability, quality assurance, system health monitoring, and fault detection. Determination of a representative RTD, in principle, requires an accurate process analytical technology (PAT) procedure capturing the entire range of tracer concentrations from zero to maximum. Such a wide concentration range creates at least two problems: i) decreased accuracy of the model across the entire range of concentrations, relating to limit of quantification, and ii) ambiguity associated with the detection of the tracer for low concentration levels, relating to limit of detection (LOD). These problems affect not only the RTD profile itself, but also RTD-based applications, which can potentially lead to erroneous conclusions. This article seeks to minimize the impact of these problems by understanding the relative importance of different features of RTD on the detection of out-of-specification (OOS) products. In this work, the RTD obtained experimentally was truncated at different levels, to investigate the impact of the truncation of RTD on funnel plots for OOS detection. The main finding is that the tail of the RTD can be truncated with no loss of accuracy in the determination of exclusion intervals. This enables the manufacturing scientist to focus entirely on the peak region, maximizing the accuracy of chemometric models.

Risk Assessment for a Twin-Screw Granulation Process Using a Supervised Physics-Constrained Auto-encoder and Support Vector Machine Framework

Quality risk management is an important task when it pertains to the pharmaceutical industry, as this is directly related to product performance. With the ICH Q9 guidelines, several regulatory bodies have encouraged the pharmaceutical industry to implement risk management plans using scientific and systemic approaches such as quality-by-design to asses product quality. However, the implementation of such methods has been challenging as assessment of risks requires accurate quantitative models to predict changes in quality when variations occur. This study describes a framework that quantitatively assesses risk for a twin screw wet granulation process. This framework consists of a physics-constrained autoencoder system, whose outputs are constrained using physics-based boundary conditions. The latent variables obtained from the auto-encoder are used in a support vector machine-based classifier to understand the granule growth behavior occurring within the system. This framework is able to predict the process outcomes with 86% accuracy and classify the granule growth regimes with a true positive rate of 0.73. Based on the classification the risk associated with the process can be estimated.

Numerical analysis of die filling with a forced feeder using GPU-enhanced discrete element methods

Understanding die filling behaviour of powders is critical in developing optimal formulation and processes in various industries, such as pharmaceuticals and fine chemicals. In this paper, forced die filling is analysed using a graphics processing unit (GPU) based discrete element method (DEM), for which a powder feeder equipped with a wired stirrer is considered. The influences of operating parameters, such as the initial powder bed height, the filling speed, and the stirrer speed, on the die filling performance are systematically explored. It is shown that a larger initial powder bed height leads to a higher filling ratio, which can be attributed to a higher filling intensity; while the deposited particle mass in the die is almost independent of the powder bed height, when the initial fill level is larger than a critical bed height. Additionally, the filling ratio slightly increases with the increase of stirrer speed for cases with a stirrer, while the filling ratios are lower than that without a stirrer, which is attributed to the stirrer occupying some space above the die and reducing the effective discharge area. The obtained results can provide useful information for optimising the feeder system design and the operating condition.

A scaled down method for identifying the optimum range of L/S ratio in twin screw wet granulation using a regime map approach

Twin screw wet granulation (TSWG) has gained momentum in the pharmaceutical industry for effective continuous granulation of solid dosage products. Liquid-to-solid (L/S) ratio is a key process parameter affecting granule properties. Identifying an optimum range of L/S ratio while reducing the number of full scale experiments can minimize material requirements and streamline formulation and process development. In this work, microcrystalline cellulose-based (MCC) formulations of varying drug loads were granulated using a kneading element screw configuration at a wide range of L/S ratios until pasting was visually determined. Quantitative criteria based on process relevant granule size and mass % of fines were established to identify undesirable granulation conditions. Key mechanical properties of wet compacts measured using a small scale approach are discussed. The stress-strain behavior is used to predict pasting, and natural strain at peak yield stress and total work of deformation are used to identify undergranulation and overgranulation respectively. The small scale method is used to establish viable ranges of L/S ratios in advance of at-scale experiments. A quantitative predictive growth regime map is proposed based fully on small scale experiments and input process parameters. Strategies for establishing a generalized growth regime map for various systems of interest are discussed.

A Population Balance Methodology Incorporating Semi-Mechanistic Residence Time Metrics for Twin Screw Granulation

This work is concerned with the incorporation of semi-mechanistic residence time metrics into population balance equations for twin screw granulation processes to predict key properties. From the historical residence time and particle size data sourced, process parameters and equipment configuration information were fed into the system of equations where the input flow rates and model compartmentalization varied upon the parameters. Semi-mechanistic relations for the residence time metrics were employed to predict the particle velocities and dispersion coefficients in the axial flow direction of the twin screw granulation. The developed model was then calibrated for several experimental run points in each data-set. The predictions were evaluated quantitatively through the parity plots. The root mean square error (RMSE) was used as a metric to compare the degree of goodness of fit for different data-sets using the developed semi-mechanistic relations. In summary, this paper presents a more mechanistic but simplified approach of feeding residence time metrics into the population balance equations for twin screw granulation processes.

Conceptualisation of an Efficient Particle-Based Simulation of a Twin-Screw Granulator

Discrete Element Method (DEM) simulations have the potential to provide particle-scale understanding of twin-screw granulators. This is difficult to obtain experimentally because of the closed, tightly confined geometry. An essential prerequisite for successful DEM modelling of a twin-screw granulator is making the simulations tractable, i.e., reducing the significant computational cost while retaining the key physics. Four methods are evaluated in this paper to achieve this goal: (i) develop reduced-scale periodic simulations to reduce the number of particles; (ii) further reduce this number by scaling particle sizes appropriately; (iii) adopt an adhesive, elasto-plastic contact model to capture the effect of the liquid binder rather than fluid coupling; (iv) identify the subset of model parameters that are influential for calibration. All DEM simulations considered a GEA ConsiGma™ 1 twin-screw granulator with a 60° rearward configuration for kneading elements. Periodic simulations yielded similar results to a full-scale simulation at significantly reduced computational cost. If the level of cohesion in the contact model is calibrated using laboratory testing, valid results can be obtained without fluid coupling. Friction between granules and the internal surfaces of the granulator is a very influential parameter because the response of this system is dominated by interactions with the geometry.

Particle-Scale Modeling to Understand Liquid Distribution in Twin-Screw Wet Granulation

Experimental characterization of solid-liquid mixing for a high shear wet granulation process in a twin-screw granulator (TSG) is very challenging. This is due to the opacity of the multiphase system and high-speed processing. In this study, discrete element method (DEM) based simulations are performed for a short quasi-two-dimensional simulation domain, incorporating models for liquid bridge formation, rupture, and the effect of the bridges on inter-particular forces. Based on the knowledge gained from these simulations, the kneading section of a twin-screw wet granulation process was simulated. The time evolution of particle flow and liquid distribution between particles, leading to the formation of agglomerates, was analyzed. The study showed that agglomeration is a rather delayed process that takes place once the free liquid on the particle surface is well distributed.

Parametric Study of Residence Time Distributions and Granulation Kinetics as a Basis for Process Modeling of Twin-Screw Wet Granulation

Twin-screw wet granulation is a crucial unit operation in shifting from pharmaceutical batch to continuous processes, but granulation kinetics as well as residence times are yet poorly understood. Experimental findings are highly dependent on screw configuration as well as formulation, and thus have limited universal validity. In this study, an experimental design with a repetitive screw setup was conducted to measure the effect of specific feed load (SFL), liquid-to-solid ratio (L/S), and inclusion of a distributive feed screw on particle size distribution (PSD) and shape as well as residence time distribution of a hydrophilic lactose/microcrystalline cellulose based formulation. An intermediate sampling point was obtained by changing inlet ports along the screw axis. Camera-based particle size analysis (QICPIC) indicated no significant change of PSD between the first and second kneading section, except for low L/S and low SFL where fines increase. Mean residence time was approximated as a bilinear fit of L/S and SFL. Moreover, large mass flow pulsations were observed by continuous camera measurements of residence time distribution and correlated to hold-up of the twin-screw granulator. These findings indicate fast granulation kinetics and process instabilities for high mean residence times, questioning current standards of two kneading compartments for wet granulation. The present study further underlines the necessity of developing a multiscale simulation approach including particle dynamics in the future.

A Semi-Mechanistic Prediction of Residence Time Metrics in Twin Screw Granulation

This work is concerned with the semi-mechanistic prediction of residence time metrics using historical data from mono-component twin screw wet granulation processes. From the data, several key parameters such as powder throughput rate, shafts rotation speed, liquid binder feed ratio, number of kneading elements in the shafts and the stagger angle between the kneading elements were identified and physical factors were developed to translate those varying parameters into expressions affecting the key intermediate phenomena in the equipment, holdup, flow and mixing. The developed relations were then tested across datasets to evaluate the performance of the model, applying a k-fold optimization technique. The semi-mechanistic predictions were evaluated both qualitatively through the main effects plots and quantitatively through the parity plots and correlations between the tuning constants across datasets. The root mean square error (RMSE) was used as a metric to compare the degree of goodness of fit for different datasets using the developed semi-mechanistic relations. In summary this paper presents a new approach at estimating both the residence time metrics in twin screw wet granulation, mean residence time (MRT) and variance through semi-mechanistic relations, the validity of which have been tested for different datasets.