TPLS as predictive platform for twin-screw wet granulation process and formulation development

Abstract

In recent years, the interest in continuous manufacturing techniques, such as twin-screw wet granulation, has increased. However, the understanding of the influence of the combination of raw material properties and process settings upon the granule quality attributes is still limited. In this study, a T-shaped partial least squares (TPLS) model was developed to link raw material properties, the ratios in which these raw materials were combined and the applied process parameters for the twin-screw wet granulation process with the granule quality attributes. In addition, the predictive ability of the TPLS model was used to find a suitable combination of formulation composition and twin-screw granulation process settings for a new API leading to desired granule quality attributes. Overall, this study helped to better understand the link between raw material properties, formulation composition and process settings on granule quality attributes. Moreover, as TPLS can provide a reasonable starting point for formulation and process development for new APIs, it can reduce the experimental development efforts and consequently the consumption of expensive (and often limited available) new API.