FORMULATION AND EVALUATION OF GLIPIZIDE MICROEMULSION

Objective: The aim of the present study was to formulate a microemulsion for the oral delivery of Glipizide.Methods: Microemulsion systems composed of oleic acid, isopropyl myristate as oils; tween 80, span 20 and cremophor EL as surfactants; propylene glycol, isopropyl alcohol as cosurfactants were investigated as potential drug delivery vehicle for delivery for glipizide. Pseudo-ternary phase diagram of the investigated system at constant surfactant concentration and varying oil/water or oil/cosurfactant ratios was constructed at room temperature by titration method. This allowed studying structural inversion from oil-in-water to water-in–oil microemulsion. Furthermore, electrical conductivity, in vitro dissolution studies, pH, centrifugation, % transmittance, viscosity, particle size, polydispersity index, zeta potential, DSC and accelerated stability studies were conducted.Results: The results of electrical conductivity clearly indicated the structural inversion. Based on these values oil/water microemulsions were selected. The plain drug has shown only 40% of dissolution, while the drug from all the o/w microemulsions has shown>90% dissolution. Based on in vitro release studies f3, f12, f22 formulations were chosen. Particle size values of f3, f12, f22 formulations are 202.4 nm, 83.3 nm, 315.3 nm respectively. Viscosity results showed that the formulations follow the Newtonian flow.Conclusion: The 3 formulations f3, f12 and f22 were successful in increasing the dissolution of glipizide in GIT and capable of sustaining the release of the drug for 8 h. From the viscosity, particle size, polydispersity index values, f12 was considered as the optimized formulation. Further, centrifugation, zeta potential and accelerated stability studies also indicated that the formulations were stable. DSC studies revealed no drug-excipient interaction in the optimized formulation. Owing to the above results microemulsion can be thus considered as a suitable oral delivery system for glipizide.Â

SAR Automatic Target Recognition via Non-negative Matrix Approximations

The set of orthogonal eigen-vectors built via principal component analysis (PCA), while very effective for compression, can often lead to loss of crucial discriminative information in signals. In this work, we build a new basis set using synthetic aperture radar (SAR) target images via non-negative matrix approximations (NNMAs). Owing to the underlying physics, we expect a non-negative basis and an accompanying non-negative coefficient set to be a more accurate generative model for SAR profiles than the PCA basis which lacks direct physical interpretation. The NNMA basis vectors while not orthogonal capture discriminative local components of SAR target images. We test the merits of the NNMA basis representation for the problem of automatic target recognition using SAR images with a support vector machine (SVM) classifier. Experiments on the benchmark MSTAR database reveal the merits of basis selection techniques that can model imaging physics more closely and can capture inter-class variability, in addition to identifying a trade-off between classification performance and availability of training