Modeling of inter- and intra-particle coating uniformity in a Wurster fluidized bed by a coupled CFD-DEM-Monte Carlo approach

JMJD2A participates in cytoskeletal remodeling to regulate castration-resistant prostate cancer docetaxel resistance

BACKGROUND

To investigate underlying mechanism of JMJD2A in regulating cytoskeleton remodeling in castration-resistant prostate cancer (CRPC) resistant to docetaxel.

METHODS

Tissue samples from CRPC patients were collected, and the expression of JMJD2A, miR-34a and cytoskeleton remodeling-related proteins were evaluated by qPCR, western blot and immunohistochemistry, and pathological changes were observed by H&E staining. Further, JMJD2A, STMN1 and TUBB3 were knocked down using shRNA in CRPC cell lines, and cell viability, apoptosis and western blot assays were performed. The interaction between miR-34a/STMN1/β3-Tubulin was analyzed with dual-luciferase reporter and co-immunoprecipitation assays.

RESULTS

In clinical experiment, the CRPC-resistant group showed higher expression of JMJD2A, STMN1, α-Tubulin, β-Tubulin and F-actin, and lower expression of miR-34a and β3-Tubulin compared to the sensitive group. In vitro experiments showed that JMJD2A could regulate cytoskeletal remodeling through the miR-34a/STMN1/β3-Tubulin axis. The expression of miR-34a was elevated after knocking down JMJD2A, and miR-34a targeted STMN1. The overexpression of miR-34a was associated with a decreased expression of STMN1 and elevated expression of β3-Tubulin, which led to the disruption of the microtubule network, decreased cancer cell proliferation, cell cycle arrest in the G0/G1 phase, and increased apoptosis.

CONCLUSION

JMJD2A promoted docetaxel resistance in prostate cancer cells by regulating cytoskeleton remodeling through the miR-34a/STMN1/β3-Tubulin axis.

Experimental and Numerical Studies of Fine Quartz Single-Particle Sedimentation Based on Particle Morphology

The sedimentation characteristics of quartz particles affect their separation and settling dehydration processes. Particle morphology determines the sedimentation equilibrium velocity. In this paper, the sedimentation of a single quartz particle is characterized by employing experimental and CFD-DEM approaches. SEM served to examine quartz particles measuring 30–500 μm, and they exhibited flaky–blocky morphologies with an average long–middle axis ratio of 1.6. Consistent with the SEM-detected morphological features of the quartz particles, suggested here is a simpler drag coefficient model, followed by verification of the model with experimental data. The results show that the velocity of a quartz particle in the non-settling direction had a fluctuation of ±0.2 mm/s. The fluctuation reached 0.4 mm/s at varying settlement release angles. The order in which the particles reached sedimentation equilibrium velocity during the settlement process was double-cone, single-cone, and square when the initial velocity was greater than sedimentation equilibrium velocity. Furthermore, the long–middle axis ratio of quartz particles diminished as their equilibrium sedimentation velocities rose. Given that the quartz particles ranged from 30 to 50 μm in size, the long–middle axis ratio wielded no discernible effect on the sedimentation equilibrium velocity.

Model-Based Evaluation of Drying Kinetics and Solvent Diffusion in Pharmaceutical Thin Film Coatings

PURPOSE

Fluid-bed coating processes make it possible to manufacture pharmaceutical products with tuneable properties. The choice of polymer type and coating thickness provides control over the drug release characteristics, and multi-layer pellet coatings can combine several active ingredients or achieve tailored drug release profiles. However, the fluid-bed coating is a parametrically sensitive process due to the simultaneous occurrence of polymer solution spraying and solvent evaporation. Designing a robust fluid-bed coating process requires the knowledge of thin film drying kinetics, which in turn critically depends on an accurate description of concentration-dependent solvent diffusion in the polymer.

METHODS

This work presents a mathematical model of thin film drying as an enabling tool for fluid-bed process design. A custom-built benchtop drying cell able to record and evaluate the drying kinetics of a chosen polymeric excipient has been constructed, validated, and used for data collection.

RESULTS

A semi-empirical mathematical model combining heat transfer, mass transfer, and film thickness evolution was formulated and used for estimating the solvent diffusion coefficient and solvent distribution in the polymer layer. The combined experimental and computational methodology was then used for analysing the drying kinetics of common polymeric excipients: poly(vinylpyrrolidone) and two grades of hydroxypropyl methylcellulose.

CONCLUSIONS

The experimental setup together with the mathematical model represents a valuable tool for predictive modeling of pharmaceutical coating processes.

An efficient multiscale bi-directional PBM-DEM coupling framework to simulate one-dimensional aggregation mechanisms

The mesoscale population balance modelling (PBM) technique is widely used in predicting aggregation processes. The accuracy and efficiency of PBM depend on the formulation of its kernels. A model of the volume- and time-dependent one-dimensional aggregation kernel is developed for predicting the temporal evolution of the considered particulate system. To make the developed model physically relevant, the PBM model needs three unknown parameters as input: volume-dependency in collisions, collision frequency per particle and aggregation probability. For this, the microscale discrete element model (DEM) is used. The system’s collision frequency is extracted periodically using a novel collision detection algorithm that detects and ignores duplicate collisions.

Finally, a multiscale bi-directional PBM–DEM coupling framework is presented to simulate the aggregation mechanism. PBM and DEM simulations take place periodically to update the particle size distribution (PSD) and extract the collision-frequency, respectively. The coupling framework successfully explains the dependence between the PSD and the collision frequency. Additionally, computational cost of the algorithm is optimized while maintaining the accuracy of the results. Lastly, the accuracy and efficiency of the developed framework are verified using two different test cases. In one of the examples, a simple aggregation is simulated directly inside the DEM for the first time.

Direct Compaction Drug Product Process Modeling

Most challenges during the development of solid dosage forms are related to the impact of any variations in raw material properties, batch size, or equipment scales on the product quality and the control of the manufacturing process. With the ever pertinent restrictions on time and resource availability versus heightened expectations to develop, optimize, and troubleshoot manufacturing processes, targeted and robust science-based process modeling platforms are essential. This review focuses on the modeling of unit operations and practices involved in batch manufacturing of solid dosage forms by direct compaction. An effort is made to highlight the key advances in the past five years, and to propose potentially beneficial future study directions.

An Efficient Scheme for Coupling OpenMC and FLUENT with Adaptive Load Balancing

This paper develops a multi-physics interface code MC-FLUENT to couple the Monte Carlo code OpenMC with the commercial computational fluid dynamics code ANSYS FLUENT. The implementations and parallel performances of block Gauss–Seidel-type and block Jacobi-type Picard iterative algorithms have been investigated. In addition, this paper introduces two adaptive load-balancing algorithms into the neutronics and thermal-hydraulics coupled simulation to reduce the time cost of computation. Considering that the different scalability of OpenMC and FLUENT limits the performance of block Gauss–Seidel algorithm, an adaptive load-balancing algorithm that can increase the number of nodes dynamically is proposed to improve its efficiency. Moreover, with the natural parallelism of block Jacobi algorithm, another adaptive load-balancing algorithm is proposed to improve its performance. A 3 x 3 PWR fuel pin model and a 1000 MWt ABR metallic benchmark core were used to compare the performances of the two algorithms and verify the effectiveness of the two adaptive load-balancing algorithms. The results show that the adaptive load-balancing algorithms proposed in this paper can greatly improve the computing efficiency of block Jacobi algorithm and improve the performance of block Gauss–Seidel algorithm when the number of nodes is large. In addition, the adaptive load-balancing algorithms are especially effective when a case demands different computational power of OpenMC and FLUENT.

Modeling the coating layer thickness in a pharmaceutical coating process

Although mechanistic numerical simulations can offer great insights into a process, they are limited with respect to resolved process time. While statistical models provide long-term predictability, determining the underlying probability distributions is often challenging. In this work, detailed CFD-DEM simulations of a pharmaceutical Wurster coating process for microspheres are used to evaluate the input parameters for a novel Monte-Carlo simulation approach. The combined strengths of both modeling approaches make it possible to predict the coating mass and thickness distributions over the entire process time. It was observed that smaller beads receive a thicker coating layer since they pass the spray zone closer to the nozzle. Moreover, it was established that, in contrast to the airflow rate, the spray rate has a great impact on the inter-particle coating variability. A stochastic model was developed to investigate the relative contribution of coating layer variability and fill weight variability to the product non-uniformity in a capsule filling process of Multiple Unit Pellet Systems (MUPS).

Pharmaceutical Application of Tablet Film Coating

Tablet film coating is a common but critical process providing various functionalities to tablets, thereby meeting diverse clinical needs and increasing the value of oral solid dosage forms. Tablet film coating is a technology-driven process and the evolution of coated dosage forms relies on advancements in coating technology, equipment, analytical techniques, and coating materials. Although multiple coating techniques are developed for solvent-based or solvent-free coating processes, each method has advantages and disadvantages that may require continuous technical refinement. In the film coating process, intra- and inter-batch coating uniformity of tablets is critical to ensure the quality of the final product, especially for active film coating containing active pharmaceutical ingredients in the coating layer. In addition to experimental evaluation, computational modeling is also actively pursued to predict the influence of operation parameters on the quality of the final product and optimize process variables of tablet film coating. The concerted efforts of experiments and computational modeling can save time and cost in optimizing the tablet coating process. This review provides a brief overview of tablet film coating technology and modeling approaches with a focus on recent advancements in pharmaceutical applications.