Modeling weight variability in a pan coating process using Monte Carlo simulations.

Abstract

The primary objective of the current study was to investigate process variables affecting weight gain mass coating variability (CV(m) ) in pan coating devices using novel video-imaging techniques and Monte Carlo simulations. Experimental information such as the tablet location, circulation time distribution, velocity distribution, projected surface area, and spray dynamics was the main input to the simulations. The data on the dynamics of tablet movement were obtained using novel video-imaging methods. The effects of pan speed, pan loading, tablet size, coating time, spray flux distribution, and spray area and shape were investigated. CV(m) was found to be inversely proportional to the square root of coating time. The spray shape was not found to affect the CV(m) of the process significantly, but an increase in the spray area led to lower CV(m) s. Coating experiments were conducted to verify the predictions from the Monte Carlo simulations, and the trends predicted from the model were in good agreement. It was observed that the Monte Carlo simulations underpredicted CV(m) s in comparison to the experiments. The model developed can provide a basis for adjustments in process parameters required during scale-up operations and can be useful in predicting the process changes that are needed to achieve the same CV(m) when a variable is altered.