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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.

Over the past decades, considerable attention has been dedicated to the exploitation of diverse immune cells as therapeutic and/or diagnostic cell-based microrobots for hard-to-treat disorders. To date, a plethora of therapeutics based on alive immune cells, surface-engineered immune cells, immunocytes' cell membranes, leukocyte-derived extracellular vesicles or exosomes, and artificial immune cells have been investigated and a few have been introduced into the market. These systems take advantage of the unique characteristics and functions of immune cells, including their presence in circulating blood and various tissues, complex crosstalk properties, high affinity to different self and foreign markers, unique potential of their on-demand navigation and activity, production of a variety of chemokines/cytokines, as well as being cytotoxic in particular conditions. Here, the latest progress in the development of engineered therapeutics and diagnostics inspired by immune cells to ameliorate cancer, inflammatory conditions, autoimmune diseases, neurodegenerative disorders, cardiovascular complications, and infectious diseases is reviewed, and finally, the perspective for their clinical application is delineated.

Patients with SARS-CoV-2 infections experience lymphopenia and inflammatory cytokine storms in the severe stage of the disease, leading to multi-organ damage. The exact pattern of immune system changes and their condition during the disease process is unclear. The available knowledge has indicated that the NF-kappa-B pathway, which is induced by several mediators, has a significant role in cytokine storm through the various mechanisms. Therefore, identifying the state of the immune cells and the dominant mechanisms for the production of cytokines incorporated in the cytokine storm can be a critical step in the therapeutic approach. On the other hand, some studies identified a higher risk for diabetic patients. Diabetes mellitus exhibits a close association with inflammation and increases the chance of developing COVID-19. Patients with diabetes mellitus have shown to have more virus entry, impaired immunity response, less viral elimination, and dysregulated inflammatory cytokines. The parallel analysis of COVID-19 and diabetes mellitus pathogenesis has proposed that the control of the inflammation through the interfering with the critical points of major signaling pathways may provide the new therapeutic approaches. In recent years, the role of Dipeptidyl Peptidase 4 (DPP4) in chronic inflammation has been proved. Numerous immune cells express the DPP4 protein. DPP4 regulates antibody production, cytokine secretion, and immunoglobulin class switching. DPP4 inhibitors like sitagliptin reduce inflammation intensity in different states. Following the accumulating data, we hypothesize that sitagliptin might reduce COVID-19 severity. Sitagliptin, an available DPP4 inhibitor drug, showed multidimensional anti-inflammatory effects among diabetic patients. It reduces the inflammation mostly by affecting on NF-kappa-B signaling pathway. Under the fact that inflammatory mediators are active in individuals with COVID-19, blocking the predominant pathway could be helpful.

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