CRITICAL ANALYSIS OF POWDER FLOW BEHAVIOUR OF DIRECTLY COMPRESSIBLE COPROCESSED EXCIPIENTS

Abstract

The aim of this pre-formulation study was to adopt simple linear regression modelling and correlation statistics to understand the associations between pharmacopoeial powder test methods using datasets generated from five commercial brands of directly compressible excipients with a specific focus to inferential implications in formulation design. Powder characterization was conducted using protocols defined in Chapter <1174> and <616> of the United States Pharmacopoeia (USP41-NF36). The study adopted a linear regression modelling analytics and correlation statistics using the fitting algorithm of OriginPro® (OriginPro, Version 2021b, OriginLab Corporation, Northampton, MA, USA). In the results, the modulus of Pearson’s product moment correlation coefficient was used to measure the strength of the linear association between test variables and a correlation matrix generated. Strong positive correlation modulus of Hausner’s Ratio (HR) with Carr’s index (r=+0.999) and static angle of repose (r=+0.932) were evident. Bulk density strongly correlates with tap density in the positive direction (r=+0.911). Tap density also shows a slight negative correlation with HR (r=-0.230), Carr’s index (r=-0.228), and static angle of repose (r==-0.421), while Carr’s index strongly correlated with static angle of repose (r=+0.933). In conclusion, modelling bivariate powder flow datasets has provided a powerful but simplistic statistical relationship for characterizing the modulus of association between HR, Carr’s index, and static angle of repose of the model excipients useful in preformulation design of pharmaceutical formulations.