An investigation of the mechanism of release of the amphoteric drug amoxycillin from poly(D,L-lactide-co-glycolide) matrices

Topically Applied Biopolymer-Based Tri-Layered Hierarchically Structured Nanofibrous Scaffold with a Self-Pumping Effect for Accelerated Full-Thickness Wound Healing in a Rat Model

Wound healing has grown to be a significant problem at a global scale. The lack of multifunctionality in most wound dressing-based biopolymers prevents them from meeting all clinical requirements. Therefore, a multifunctional biopolymer-based tri-layered hierarchically nanofibrous scaffold in wound dressing can contribute to skin regeneration. In this study, a multifunctional antibacterial biopolymer-based tri-layered hierarchically nanofibrous scaffold comprising three layers was constructed. The bottom and the top layers contain hydrophilic silk fibroin (SF) and fish skin collagen (COL), respectively, for accelerated healing, interspersed with a middle layer of hydrophobic poly-3-hydroxybutyrate (PHB) containing amoxicillin (AMX) as an antibacterial drug. The advantageous physicochemical properties of the nanofibrous scaffold were estimated by SEM, FTIR, fluid uptake, contact angle, porosity, and mechanical properties. Moreover, the in vitro cytotoxicity and cell healing were assessed by MTT assay and the cell scratching method, respectively, and revealed excellent biocompatibility. The nanofibrous scaffold exhibited significant antimicrobial activity against multiple pathogenic bacteria. Furthermore, the in vivo wound healing and histological studies demonstrated complete wound healing in wounded rats on day 14, along with an increase in the expression level of the transforming growth factor-β1 (TGF-β1) and a decrease in the expression level of interleukin-6 (IL-6). The results revealed that the fabricated nanofibrous scaffold is a potent wound dressing scaffold, and significantly accelerates full-thickness wound healing in a rat model.

Heuristic modeling of macromolecule release from PLGA microspheres

Dissolution of protein macromolecules from poly(lactic-co-glycolic acid) (PLGA) particles is a complex process and still not fully understood. As such, there are difficulties in obtaining a predictive model that could be of fundamental significance in design, development, and optimization for medical applications and toxicity evaluation of PLGA-based multiparticulate dosage form. In the present study, two models with comparable goodness of fit were proposed for the prediction of the macromolecule dissolution profile from PLGA micro- and nanoparticles. In both cases, heuristic techniques, such as artificial neural networks (ANNs), feature selection, and genetic programming were employed. Feature selection provided by fscaret package and sensitivity analysis performed by ANNs reduced the original input vector from a total of 300 input variables to 21, 17, 16, and eleven; to achieve a better insight into generalization error, two cut-off points for every method was proposed. The best ANNs model results were obtained by monotone multi-layer perceptron neural network (MON-MLP) networks with a root-mean-square error (RMSE) of 15.4, and the input vector consisted of eleven inputs. The complicated classical equation derived from a database consisting of 17 inputs was able to yield a better generalization error (RMSE) of 14.3. The equation was characterized by four parameters, thus feasible (applicable) to standard nonlinear regression techniques. Heuristic modeling led to the ANN model describing macromolecules release profiles from PLGA microspheres with good predictive efficiency. Moreover genetic programming technique resulted in classical equation with comparable predictability to the ANN model.

DDSolver: an add-in program for modeling and comparison of drug dissolution profiles

In recent years, several mathematical models have been developed for analysis of drug dissolution data, and many different mathematical approaches have been proposed to assess the similarity between two drug dissolution profiles. However, until now, no computer program has been reported for simplifying the calculations involved in the modeling and comparison of dissolution profiles. The purposes of this article are: (1) to describe the development of a software program, called DDSolver, for facilitating the assessment of similarity between drug dissolution data; (2) to establish a model library for fitting dissolution data using a nonlinear optimization method; and (3) to provide a brief review of available approaches for comparing drug dissolution profiles. DDSolver is a freely available program which is capable of performing most existing techniques for comparing drug release data, including exploratory data analysis, univariate ANOVA, ratio test procedures, the difference factor f (1), the similarity factor f (2), the Rescigno indices, the 90% confidence interval (CI) of difference method, the multivariate statistical distance method, the model-dependent method, the bootstrap f (2) method, and Chow and Ki's time series method. Sample runs of the program demonstrated that the results were satisfactory, and DDSolver could be served as a useful tool for dissolution data analysis.

Quantifying drug release from PLGA nanoparticulates

The objective of this work was to investigate the mechanism of release of active pharmaceutical ingredients (APIs) both small molecules (ketoprofen, indomethacin, coumarin-6) and macromolecules (human serum albumin, ovalbumin), from PLGA (50:50) nanoparticulates (400-700nm), having drug loadings less than 10%. The nanoparticulates were prepared by emulsification/solvent evaporation methods and release determined in phosphate buffer pH 7.4 at 37 degrees C. The release profiles exhibited an initial burst release phase, a slower lag phase and a second increased release rate phase. The profiles were consistent with a model in which the first phase of the release reflects diffusion controlled dissolution of drug accessible to the solid/dissolution medium interface and the second phase reflects release of drug entrapped in the polymer, the release of which was dependent on the bulk degradation of the polymer. The burst phase tended to increase with increase in API loading and solubility. The polymer erosion related parameters also indicated that increased drug loading accelerated this phase of API release. Small acidic hydrophobic actives such as ketoprofen and indomethacin had a much greater effect on these parameters than the larger hydrophilic more neutral proteins, HSA and ovalbumin.

Effect of poly-hydroxy aliphatic ester polymer type on amoxycillin release from cylindrical compacts

The objective of the work was to investigate the effects of a range of poly-hydroxy aliphatic esters (poly-lactide (PLA) and poly-lactide-co-glycolide (PLGA)) of different molecular weight and composition on the release and stability of the amphoteric drug amoxycillin. The effect of this amphoteric drug on the extent and kinetics of polymer degradation was also investigated. The polymers were used to prepare drug-free and drug-loaded cylindrical discs. Drug release profiles were determined while changes in polymer composition were monitored by weight loss and molecular weight change. The extent of drug release was highly dependent on polymer molecular weight and composition, with earlier complete release occurring with the lower molecular weight and lower lactide containing polymers. A larger proportion of drug was released by polymer degradation control with the higher lactide containing polymer. The proportion of drug released intact was influenced by the polymer molecular weight, with a greater proportion of intact drug being released from the higher molecular weight systems. The inclusion of amoxycillin influenced polymer degradation and resulted in slower polymer hydrolysis. Model parameters obtained for polymer degradation indicated that this retardation effect increased with increasing lactide content of the polymer. The results suggest that small amounts of amoxycillin or its degradation products may bind or cross link with the polymers, thus retarding their degradation.