Predictive Evaluation of Heat Treatment Effect on Theophylline Release of Spray-Dried Pre-Gelatinised Glutinous Rice Starch Particles by near Infrared Spectroscopy

Abstract

Starch is a natural polymeric with high chemical stability and no toxicity, so it is used widely as an additive in pharmaceutical manufacturing and the food industry. In this study, the effect of heat treatment on the controlled theophylline (TH) release rate of spray-dried pre-gelatinised glutinous rice starch (pGRS) was evaluated predictively by near infrared (NIR) spectroscopy. Spray-dried particles (SGRS) were obtained by spray-drying of TH ethanolic aqueous solution (TH: pGRS = 1: 1). The obtained SGRS was heat-treated to control drug release by chemical modification at 40–100°C. TH release test of the SGRS was performed to evaluate the drug release rate constant (K_H) in water at 37°C – body temperature. NIR spectra of heat-treated SGRS were recorded by diffuse reflectance NIR spectroscopy. The best calibration model consisted of five latent variables to predict K_H and was determined by partial least squares (PLS) regression. Since the drug release profiles of TH from SGRS followed a Higuchi-type plot (diffusion-controlled sustained drug release), it was indicated that the rate-determining step of TH release is diffusion in polymeric matrices of SGRS. The K_H of SGRS was evaluated based on Higuchi plots. It decreased with increasing temperature. X-ray diffraction and NIR results of SGRS suggested that TH recrystallised in SGRS after heat treatment. The relationship between actual and predicted K_H values by our best PLS model based on NIR spectra gave a straight line with r² = 0.990, with the slopes being close to 1. The K_H of SGRS could be controlled by heat treatment. The K_H could be predicted from NIR spectra and a chemometric method.

Keywords

controlled drug release pre-gelatinised glutinous rice starch near infrared spectroscopy spray-drying partial least squares regression heat treatment

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