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Pegylation, generally described as the molecular attachment of polyethylene glycols (PEGs) with different molecular weights to active drug molecules or surface treatment of drug-bearing particles with PEGs, is one of the most promising and extensively studied strategies with the goal of improving the pharmacokinetic behavior of the therapeutic drugs. A variety of PEGs, both linear and branched, with different molecular weights have been exploited successfully for use in this procedure in the form of reactive PEG species. Both reversible and irreversible PEG-drug conjugates have been prepared with relative advantages/disadvantages. The main pharmacokinetic outcomes of pegylation are summarized as changes occurring in overall circulation life-span, tissue distribution pattern, and elimination pathway of the parent drug/particle. Based on these favorable pharmacokinetic consequences leading to desired pharmacodynamic outcomes, a variety of proteins/peptides as well as small molecule drugs have been pegylated and evaluated successfully. Also a number of corresponding products have been approved by the U.S. FDA for specific clinical indications and some others are underway. In this article, the chemistry, rationale, strategies, pharmacokinetic outcomes, and therapeutic possibilities of pegylated drugs are reviewed with pharmacokinetic aspects presented with more details.

Curcumin is a multitherapeutic agent with great therapeutic potential in central nervous system (CNS) diseases. In the current study, curcumin was encapsulated in solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) for the purpose of increasing brain accumulation. The preparation processes have been optimized using experimental design and multiobjective optimization methods. Entrapment efficiency of curcumin in SLNs and NLCs was found to be 82% ± 0.49 and 94% ± 0.74, respectively. The pharmacokinetic studies showed that the amount of curcumin available in the brain was significantly higher in curcumin-loaded NLCs (AUC0‑t = 505.76 ng/g h) compared to free curcumin (AUC0‑t = 0.00 ng/g h) and curcumin-loaded SLNs (AUC0‑t = 116.31 ng/g h) (P < 0.005), after intravenous (IV) administration of 4 mg/kg dose of curcumin in rat. The results of differential scanning calorimetry and X-ray diffraction showed that curcumin has been dispersed as amorphous in the nanocarriers. Scanning electron microscopy images confirmed the nanoscale size and spherical shape of the nanoparticles. The DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging study indicated that preparation processes do not have any significant effect on the antioxidant activity of curcumin. The results of this study are promising for the use of curcumin-loaded NLCs in more studies and using curcumin in the treatment of CNS diseases.

Poly (lactic-co-glycolic acid) has received much academic attention for developing nanotherapeutics and FDA has approved it for several applications. An important parameter that dictates the bioavailability and hence the biological effect of the drug is drug release from its delivering system. This study offers a comparative mathematical analysis of drug release from Poly (lactic-co-glycolic acid)-based nanoparticles to suggest a general model explaining multi-mechanistic release they provide. Methods: Eight release models, zero order, first order, Higuchi, Hixson-Crowell, the square root of mass, the threesecond root of mass, Weibull and Korsmeyer-Peppas, as well as the second degree polynomial equation were applied to 60 data sets. The models analysed regarding several types of errors, regression parameters and average Akaike information criterion. Results and discussion: Most of the data sets present the highest R 2 , the lowest overall error and AIC for the Weibull model. Weibull model with the mean AIC ¼-36.37 and mean OE ¼ 7.24 and the highest NE less than 5, 10, 15 and 20 % in most of the cases best fits the release data from various PLGA-based drug delivery systems that are studied. Weibull model seems to show enough flexibility to describe various release patterns PLGA provides.

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