Prediction of drug-polymer interactions in binary mixtures using energy balance supported by inverse gas chromatography

Abstract

Surface energy is extensively adopted to predict the surface properties of materials nowadays. Our study was aimed at utilizing the surface free energy measured by inverse gas chromatography to determine inter-particle interactions and to describe the overall behaviour of mixtures. The model drugs of different solubility (tadalafil, levocetirizine dihydrochloride, vardenafil hydrochloride, and amlodipine besylate) and two grades of polyvinylpyrrolidone (Kollidon® 12 PF, Kollidon® VA 64) were mixed in various ratios. Investigated components were characterized using inverse gas chromatography, particle size distribution and specific surface area. We also determined the work of adhesion and cohesion between the components in the binary mixtures. Due to the formation of levocetirizine agglomerates, the effect of mixing time on both components of the surface free energy was also studied for the binary mixture with Kollidon® VA 64. The results based on the energy analysis, especially positive or negative excess surface energies in theoretical and real binary mixtures, indicate that we can predict whether the components can form the desired ordered (interactive) mixture. For this reason, we have proposed, to the best of our knowledge, different approach to predict the interactions between components and their behaviour in the binary mixtures using inverse gas chromatography in terms of the energy balance based only on the surface parameters (surface free energy, dispersive and specific surface energy). Therefore, the approach of energy balance is an innovative and comparatively simple tool for analysis and identification of interactions between components in particulate systems, which can also predict the quality of the mixing.

Keywords: Binary mixtures; Drug-polymer interactions; Energy analysis; Energy balance; Inverse gas chromatography; Prediction.