Development and application of a process window for achieving high-quality coating in a fluidized bed coating process.

Next to the coating formulation, process conditions play important roles in determining coating quality. This study aims to develop an operational window that separates layering from agglomeration regimes and, furthermore, the one that leads to the best coating quality in a fluidized bed coater. The bed relative humidity and the droplet size of the coating aerosol were predicted using a set of engineering models. The coating quality was characterized using a quantitative image analysis method, which measures the coating thickness distribution, the total porosity, and the pore size in the coating. The layering regime can be achieved by performing the coating process at a certain excess of the viscous Stokes number (DeltaSt(v)). This excess is dependent on the given bed relative humidity and droplet size. The higher the bed relative humidity, the higher is the DeltaSt(v) required to keep the process in the layering regime. Further, it is shown that using bed relative humidity and droplet size alone is not enough to obtain constant coating quality. The changes in bed relative humidity and droplet size have been identified to correlate to the fractional area of particles sprayed per unit of time. This parameter can effectively serve as an additional parameter to be considered for a better control on the coating quality. High coating quality is shown to be achieved by performing the process close to saturation and spraying droplets small enough to obtain high spraying rate, but not too small to cause incomplete coverage of the core particles.

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PURPOSE: This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. METHODS: The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. RESULTS: The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. CONCLUSIONS: Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.