Challenges in the modeling and prediction of coating of pharmaceutical dosage forms

A review of different approaches to modeling the coating mass uniformity in fluidized bed and rotating drum (pans) equipment is presented. In order to predict the coefficient of variation (CV) of the coating mass distribution, the models must include the physics of non-uniform particle movement and/or non-uniform spray flux. Descriptive models for the coating process include those based on renewal theory, compartment models with appropriate population balances, and Monte Carlo simulation. These three approaches give reasonable fits to experimental data. However, they require certain model parameters to be adjusted to obtain a good fit with experimental results or, alternatively, parameters must be evaluated using an extensive experimental program. While such models can describe observed results, they generally lack the rigor to make reliable quantitative predictions outside the range for which the parameters were determined or adjusted. Nevertheless, these models are useful for making qualitative predictions about the effects of changing operating parameters. In addition, regardless of the model, they show that the CV changes with the inverse square root of coating time.More rigorous DEM and CFD models are also considered. Most work to date has not focused explicitly on evaluating the coating mass uniformity. However, recent studies show that CV can be evaluated for laboratory scale equipment and that the effects of non-spherical particles, vessel internals, and the formation of liquid bridges due to the application of coating spray can all be modeled.

Graphical abstractA review of modeling techniques that predict the uniformity of the mass coating distribution on tablets and pellets is given. Complexity of models caries from phenomenological to rigorous CFD and DEM approaches. The former are generally easier to use: however, the rigorous models allow a more complete description of the many processes taking place.Figure optionsDownload full-size imageDownload as PowerPoint slide