Comparison of video analysis and simulations of a drum coating process.

Tablet coating is a common unit operation in the pharmaceutical industry. To improve currently established processes, it is important to understand the influence of the process parameters on the coating quality. One of the critical parameters is the tablet velocity. In this work, numerical results are compared to results obtained experimentally. Tablet movement in the drums was simulated using the Discrete Element Method (DEM). The simulation parameters were adapted to fit the simulation to the experimental data. A comparison of the experimental and simulation results showed that the simulation correctly represents the real tablet velocity. A change in the velocity over time and its dependence on the rotation rates and the baffle position in the simulation were similar to the experimental results. In summary, simulations can improve the understanding of tablet coating processes and will thus provide insights into the underlying process mechanics, which cannot be obtained via ordinary experiments.

Simulation of a tablet coating process at different scales using DEM.

Spray coating of tablets is an important unit operation in the pharmaceutical industry and is mainly used for modified release, enteric protection, better appearance and brand recognition. It can also be used to apply an additional active pharmaceutical ingredient to the tablet core. Scale-up of such a process is an important step in commercialization. However, scale-up is not trivial and frequently, at manufacturing scales the required coating quality cannot be reached. Thus, we propose a method where laboratory experiments are carried out, yet scale-up is done via computational methods, i.e., by extrapolating results to larger scales. In the recent years, the Discrete Element Method (DEM) has widely been used to simulate tablet behavior in a laboratory scale drum coater. Due the increasing computational power and more sophisticated DEM algorithms, it has become possible to simulate millions of particles on regular PCs and model industrial scale tablet coating devices. In this work, simulations were performed on the laboratory, pilot and industrial scales and DEM was used to study how different scale-up rules influence the bed behavior on larger scales. The material parameters of the tablets were measured in the laboratory and a glued sphere approach was applied to model the tablet shape. The results include a vast amount of qualitative and quantitative data at the different scales. In conclusion, the evolution of the inter-tablet coating variation for the different scales and process parameters is presented. The results suggest that keeping the Froude number constant during the scale up process leads to faster processes as the cycle time is shorter and the spray residence time is more uniform when compared to keeping the circumferential velocity constant.

Analysis of large-scale tablet coating: Modeling, simulation and experiments.

This work concerns a tablet coating process in an industrial-scale drum coater. We set up a full-scale Design of Simulation Experiment (DoSE) using the Discrete Element Method (DEM) to investigate the influence of various process parameters (the spray rate, the number of nozzles, the rotation rate and the drum load) on the coefficient of inter-tablet coating variation (cv,inter). The coater was filled with up to 290kg of material, which is equivalent to 1,028,369 tablets. To mimic the tablet shape, the glued sphere approach was followed, and each modeled tablet consisted of eight spheres. We simulated the process via the eXtended Particle System (XPS), proving that it is possible to accurately simulate the tablet coating process on the industrial scale. The process time required to reach a uniform tablet coating was extrapolated based on the simulated data and was in good agreement with experimental results. The results are provided at various levels of details, from thorough investigation of the influence that the process parameters have on the cv,inter and the amount of tablets that visit the spray zone during the simulated 90s to the velocity in the spray zone and the spray and bed cycle time. It was found that increasing the number of nozzles and decreasing the spray rate had the highest influence on the cv,inter. Although increasing the drum load and the rotation rate increased the tablet velocity, it did not have a relevant influence on the cv,inter and the process time.

Linear and nonlinear regression techniques for simultaneous and proportional myoelectric control.

In recent years the number of active controllable joints in electrically powered hand-prostheses has increased significantly. However, the control strategies for these devices in current clinical use are inadequate as they require separate and sequential control of each degree-of-freedom (DoF). In this study we systematically compare linear and nonlinear regression techniques for an independent, simultaneous and proportional myoelectric control of wrist movements with two DoF. These techniques include linear regression, mixture of linear experts (ME), multilayer-perceptron, and kernel ridge regression (KRR). They are investigated offline with electro-myographic signals acquired from ten able-bodied subjects and one person with congenital upper limb deficiency. The control accuracy is reported as a function of the number of electrodes and the amount and diversity of training data providing guidance for the requirements in clinical practice. The results showed that KRR, a nonparametric statistical learning method, outperformed the other methods. However, simple transformations in the feature space could linearize the problem, so that linear models could achieve similar performance as KRR at much lower computational costs. Especially ME, a physiologically inspired extension of linear regression represents a promising candidate for the next generation of prosthetic devices.