Chitosan/glycyrrhizic acid hydrogel: Preparation, characterization, and its potential for controlled release of gallic acid.

In the present work, chitosan (CHT) as a biodegradable polymer was crosslinked using various amounts of glycyrrhizic acid (GLA) as a novel crosslinking agent to prepare biocompatible hydrogels. The prepared hydrogels were used for the controlled release of gallic acid (GA) in transdermal therapy application. FTIR, XRD, and SEM were used to characterize the prepared gels. The results indicated that the carboxylic acid groups of GLA react with the amine groups of the CHT in the presence of activating coupling reagents to form covalent amide linkage between the polymer chains of CHT and construct CHT cross-linked hydrogel (CCH) network structure. The prepared CCH samples were characterized and used for the controlled release of a drug, i.e. (GA). For this purpose, the swelling kinetic, loading and encapsulation efficiency, in vitro drug release, drug release kinetics, cell viability assay, and anti-bacterial activity of the samples were evaluated. The swelling ratio of CCH samples were in the range of 455-37 % depending on the pH of environment. Swelling kinetic results showed an aggregate to the non-linear second-order kinetic model. Drug release results were fitted by kinetic models while the Korsmeyer-Peppas model was fitted better. The CCH samples exhibited high biocompatibility for 5 mg/ml hydrogel concentration. In addition, the CHT and CCH sample without the GA did not show anti-bacterial properties for 1200 and 150 µg/ml concentrations, respectively. The CCH sample containing the GA exhibited enough anti-bacterial activity on the S. aureus bacteria strain at 150 µg/ml concentration. In contrast, the CCH sample containing the GA has a light anti-bacterial effect on the E. coli bacteria strain. The calculated mesh size of hydrogel networks, drug size, and kinetics models revealed that the CCH samples could release GA based on a diffusion mechanism. In conclusion, the designed CCH samples have enough ability for controlled drug release in transdermal applications.

Customizing nano-chitosan for sustainable drug delivery.

Chitosan is a natural polymer with acceptable biocompatibility, biodegradability, and mechanical stability; hence, it has been widely appraised for drug and gene delivery applications. However, there has been no comprehensive assessment to tailor-make chitosan cross-linkers of various types and functionalities as well as complex chitosan-based semi- and full-interpenetrating networks for drug delivery systems (DDSs). Herein, various fabrication methods developed for chitosan hydrogels are deliberated, including chitosan crosslinking with and without diverse cross-linkers. Tripolyphosphate, genipin and multi-functional aldehydes, carboxylic acids, and epoxides are common cross-linkers used in developing biomedical chitosan for DDSs. Methods deployed for modifying the properties and performance of chitosan hydrogels, via their composite production (semi- and full-interpenetrating networks), are also cogitated here. In addition, recent advances in the fabrication of advanced chitosan hydrogels for drug delivery applications such as oral drug delivery, transdermal drug delivery, and cancer therapy are discussed. Lastly, thoughts on what is needed for the chitosan field to continue to grow is also debated in this comprehensive review article.

A new mathematical approach to predict the actual drug release from hydrogels.

In the present study, we have developed a mathematical model of drug release from a film of highly swellable gelatin based hydrogel mixed with graphene. The model considers the hydrogel volume expansion because of the swelling as well as the non-linear concentration dependence of the diffusion coefficients for the solvent and the drug. An additionl term is considered for the drug diffusion coefficient enabling the model to predict the drug maximum release from the hydrogel. The model parameters are estimated by genetic algorithem and the model resutls are validated using data sets obtained from experiments on Zoledronic acid, the model drug, loaded hydrogel samples made from several weigth ratios of gelatin to graphene crosslinked with different amounts of glutaraldehyde. The model is further developed to mathematically predict the drug conrolled release into in vivo environment and the impact of several factors influencing the release rate into the surrounding environment is investigated.

A new prospect in magnetic nanoparticle-based cancer therapy: Taking credit from mathematical tissue-mimicking phantom brain models.

Distribution patterns/performance of magnetic nanoparticles (MNPs) was visualized by computer simulation and experimental validation on agarose gel tissue-mimicking phantom (AGTMP) models. The geometry of a complex three-dimensional mathematical phantom model of a cancer tumor was examined by tomography imaging. The capability of mathematical model to predict distribution patterns/performance in AGTMP model was captured. The temperature profile vs. hyperthermia duration was obtained by solving bio-heat equations for four different MNPs distribution patterns and correlated with cell death rate. The outcomes indicated that bio-heat model was able to predict temperature profile throughout the tissue model with a reasonable precision, to be applied for complex tissue geometries. The simulation results on the cancer tumor model shed light on the effectiveness of the studied parameters.

Synthesis and characterization of glycyrrhizic acid coated iron oxide nanoparticles for hyperthermia applications.

In the present study, iron oxide magnetic nanoparticles (IONPs) were synthesized using the oxidative precipitation method for biomedical applications. Glycyrrhizic acid (GA) extracted from the roots of licorice plant was used as the coating agent for the synthesized nanoparticles (GAIONPs). The crystal phase, morphology and size were investigated by XRD, FE-SEM and TEM. The saturation magnetization (ms) value of the nanoparticles was measured by VSM indicating lowered ms of the GAIONPs with respect to that of the IONPs due to the presence of GA. In addition, the specific loss power of nanoparticles in a solution and in a tissue mimicking phantom was measured using an alternating magnetic field generator. The presence of the GA on the crystal surface was further confirmed using FT-IR and TG/DTA measurements. The specific surface area of the nanoparticles was measured by BET indicating that GA coating agent increases the available active surface area of the nanoparticles for about 25% making it more appropriate for drug loading purposes. The cytotoxicity of the nanoparticles was investigated using MTT assay on L929 fibroblast cell line and the results demonstrated that the coating agent enhances the biocompatibility of the IONPs. The effectiveness of the nanoparticles in inducing cell death was also assessed in an in vitro hyperthermia process and the results showed that the nanoparticles are appropriate to be used for cancer treatment based on hyperthermia.

Pharmacokinetic-Pharmacodynamic Modeling of Metformin for the Treatment of Type II Diabetes Mellitus.

Metformin is an antihyperglycemic agent commonly used for the treatment of Type II diabetes mellitus. However, its effects on patients are derived usually from clinical experiments. In this study, a dynamic model of Type II diabetes mellitus with the treatment of metformin is proposed. The Type II diabetic model is a modification of an existing compartmental diabetic model. The dynamic simulation of the metformin effect for a Type II diabetic patient is based on the pharmacokinetic and pharmacodynamic relationship with a human body. The corresponding model parameters are estimated by optimization using clinical data from published reports. Then, the effect of metformin in both intravenous and oral administration on a Type II diabetes mellitus model are compared. The combination treatment of insulin infusion plus oral metformin is shown to be superior than the monotherapy with oral metformin only. These results are consistent with the clinical understanding of the use of metformin. For further work, the model can be analyzed for evaluating the treatment of diabetes mellitus with different pharmacological agents.