Optimization and prediction of drug release from matrix tablets using response surface methodology and near infrared chemical imaging

The purpose of this work was to understand the formulation effect on the drug release from a hydrophilic matrix tablet of niacin using a multivariate statistical technique and Near Infrared Chemical Imaging (NIR-CI). Tablets were composed of ethyl cellulose (EC) and polyethylene oxide (PEO) as release retarding polymers and lactose as the release modulator. D-optimal experimental design was composed of three formulation variables: the content of EC(X(1)), PEO (X(2)), and lactose (X(3)). Response surface methodology (RSM) and multiple response optimization utilizing the polynomial equation were used to predict the optimal formulation. Results showed that the interaction effect of lactose with the polymers PEO and EC and lactose by itself were the most influential factors on the drug release rate. While lactose enhances the drug release rate by forming pores it also promotes water penetration into the tablet core. This in turn helps the formation of the gel layer which acts as barrier to drug diffusion. NIR-CI showed that tablets with higher level of PEO swells at a faster rate and greater extent than formulations with higher level of EC. NIR-CI was thus found to be a very useful technique to predict the drug release rate from hydrophilic matrix systems.