Biodegradable polymers have played an important role in the delivery of drugs in a controlled and targeted manner. Polylactic-co-glycolic acid (PLGA) is one of the extensively researched synthetic biodegradable polymers due to its favorable properties. It is also known as a 'Smart Polymer' due to its stimuli sensitive behavior. A wide range of PLGA-based drug delivery systems have been reported for the treatment or diagnosis of various diseases and disorders. The present review provides an overview of the chemistry, physicochemical properties, biodegradation behavior, evaluation parameters and applications of PLGA in drug delivery. Different drug-polymer combinations developed into drug delivery or carrier systems are enumerated and discussed.

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Autonomic fault aware scheduling is a feature quite important for cloud computing and it is related to adoption of workload variation. In this context, this paper proposes an fault aware pattern matching autonomic scheduling for cloud computing based on autonomic computing concepts.  In order to validate  the proposed solution, we performed two experiments one with traditional approach and other other with pattern recognition fault aware approach. The results show the effectiveness of the scheme.

The current studies entail systematic development of self-nanoemulsifying drug delivery systems (SNEDDS) containing medium-chain triglycerides (MCTs) and long-chain triglycerides (LCTs) for augmenting the biopharmaceutical performance of artemether. Equilibrium solubility and pseudoternary phase diagram studies facilitated selection of Captex 355 and Ethyl oleate as MCTs and LCTs, and Cremophor RH 40 and Tween 80 as surfactants, while Transcutol HP as cosolvent for formulating the SNEDDS. Systematic optimization was performed employing the Box-Behnken design taking concentrations of lipid, surfactant and cosolvent as the critical material attributes (CMAs), while evaluating for globule size, emulsification time, dissolution efficiency and permeation as the critical quality attributes (CQAs). In situ single pass intestinal perfusion (SPIP) studies in Wistar rats substantiated significant augmentation in the absorption (5-to 6-fold) and permeation (4-to 5-fold) parameters from the optimized MCT and LCT-SNEDDS vis-à-vis the pure drug. In vivo pharmacodynamic studies in Plasmodium berghi infected laca mice exhibited superior reduction in the levels of percent parasitemia, SGOT, SGPT and bilirubin, followed by higher survival rate of the animals by optimized MCT-SNEDDS followed by LCT-SNEDDS vis-à-vis the pure drug, which was subsequently ratified through histopathological examination of liver tissues. Overall, the studies construed successful development of the optimized SNEDDS of artemether with distinctly improved biopharmaceutical and antimalarial potential.

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Background Ceftazidime, a third-generation cephalosporin, is widely used in the treatment of lung infections, often given as “off-label” nebulization. There is need for developing a sensitive and robust analytical method to compute aerodynamic properties of ceftazidime following nebulization. Objective The current study entails development of a simple, accurate and sensitive high-performance liquid chromatography method (HPLC) for ceftazidime estimation, employing the principles of analytical quality-by-design (AQbD) and Monte Carlo simulations. Methods Selection of critical material attributes (CMAs) affecting method performance was accomplished by factor screening exercise. Subsequently, the influential CMAs, i.e., mobile phase ratio and flow rate, were systemically optimized using a face-centred cubic design for the chosen critical analytical attributes (CAAs). The factor relationship(s) between CMAs and CAAs was explored employing 3 D-response surface and 2 D-contour plots, followed by numerical as well as graphical optimization, for establishing the optimal chromatographic conditions. The obtained method operable design region was validated by Monte Carlo simulations for defect rate analysis. Results The optimized HPLC conditions for estimating ceftazidime were acetonitrile to acetic acid solution (75:25) as mobile phase at a flow rate of 0.7 mL/min, leading to Rt of 4.5 min and peak tailing ≤ 2. Validation studies, as per ICH Q2(R1) guidance’s, demonstrated high sensitivity, accuracy and efficiency of the developed analytical method with LOD of 0.075 and LOQ of 0.227 µg/mL. Application of this chromatographic method was extrapolated for determining aerodynamic performance by nebulizing ceftazidime at flow rate of 15 L/min using next-generation impactor. The study indicated superior performance, sensitivity and specificity of the developed analytical system for quantifying ceftazidime. Conclusions Application of AQbD approach, coupled with Monte Carlo simulations, aided in developing a robust HPLC method for estimation of ceftazidime per se and on various stages of impactor.

The present work involved development of phospholipid-based permeation enhancing nanovesicles (PENVs) for topical delivery of ketoprofen. Screening of phospholipids and process parameters was performed. Central composite design was used for optimization of factors, that is, amount (%, w/w) of phospholipid and ethanol at three levels. The optimized nanovesicles (NVs) were loaded with different terpenes and then incorporated into a gel base. Optimized NVs exhibited 69% entrapment efficiency, 51% transmittance, 328 nm mean vesicle size, and polydispersity index of 0.25. In vitro release kinetics evaluation indicated best fitting as per Korsemeyer-Peppa's model and drug release via Fickian-diffusion mechanism. The optimized NVs loaded with mint terpene showed minimal degree of deformability and maximal elasticity as compared with the conventional NVs and liposomes. Rheology and texture analysis indicated pseudoplastic flow and smooth texture of the vesicle gel formulation. Ex vivo permeation studies across Wistar rat skin indicated low penetration (0.43-fold decrease) and