Empirical prediction model based process optimization for droplet size and spraying angle during pharmaceutical fluidized bed granulation

Abstract

The objective of this study was to predict the droplet size and the spraying angle during the process of binder atomization in pharmaceutical fluidized bed granulation using an empirical model. The effects of the binder viscosity, the atomization pressure, and the spray rate on the droplet size and the spraying angle were investigated using a response surface central composite design and analysis of variance. Prediction models for droplet size and spraying angle were then established using stepwise regression analysis and were validated by comparing the measured and predicted values. The results showed that the droplet size model and the spraying angle model were well established, with an R² of 0.93 (p < 0.0001) and a root mean square error (RMSE) of 10.10, and an R² of 0.82 (p < 0.0001) and an RMSE of 3.69, respectively. The error between the measured and predicted values of the droplet size and the spraying angle were less than 10%, indicating that the established models were accurate. The results of the present study were significant in predicting the droplet size and spraying angle in the process of pharmaceutical fluidized bed granulation.

Keywords:

• Fluidized bed granulation
• empirical prediction model
• process parameters
• droplet size
• spraying angle

Disclosure statement

The authors declare that they have no conflict of interest.