Modelling and understanding powder flow properties and compactability of selected active pharmaceutical ingredients, excipients and physical mixtures from critical material properties

In this study, predictive multilinear regression models were effectively developed from critical material properties to estimate static powder flow parameters from particle size distribution data for a single component and for binary systems. A multilinear regression model, which was successfully developed for ibuprofen, also efficiently predicted the powder flow properties for a range of batches of two other active pharmaceutical ingredients processed by the same manufacturing route. The particle size distribution also affected the compactability of ibuprofen, and the scope of this work will be extended to the development of predictive multivariate models for compactability, in a similar manner to the approach successfully applied to flow properties. Graphical abstract
Source: International Journal of Pharmaceutics - Category: Drugs & Pharmacology Source Type: research