Assessment and predictive modeling of pharmaceutical powder flow behavior in small-scale hoppers

Abstract

The propensity of powder to bridge in hoppers and bins is important for a wide variety of pharmaceutical processes, yet it remains difficult to predict large-scale performance from small-scale powder measurements. Despite the availability of various powder flow testing techniques, the prediction of powder bridging has remained elusive. To address this issue, powder flow performance was characterized for several pharmaceutical powders out of small-scale conical hoppers under various conditions. Specifically, the impacts of powder properties, hopper design, hopper fill level and vibration prior to discharge were characterized. The hopper flow regimes were categorized as mass flow, funnel flow, rat-holing or bridging. A Projection to Latent Spaces (PLS, a.k.a. partial least squares regression) model was developed to predict flow behavior from easily measured powder properties such as the Hausner ratio and measured hopper dimensions. The model correctly predicted flow initiation for new materials for ~90% of tests. The variables of Hausner ratio, vibration prior to discharge, and hopper orifice diameter were seen to be most predictive of flow. Surprisingly, powder shear test data such as flow function and unconfined yield strength along with other flow properties were not predictive of hopper performance for the conditions studied. A useful metric, tan(ϕ)/D, was developed utilizing the hopper semi-apex angle (ϕ) and orifice diameter (D), and was considered as a first-pass scale-up model.