Spectral and spatial characterization of protein loaded PLGA nanoparticles

Preparation of PLGA Nanoparticles by Milling Spongelike PLGA Microspheres

Currently, emulsification-templated nanoencapsulation techniques (e.g., nanoprecipitation) have been most frequently used to prepare poly-d,l-lactide-co-glycolide (PLGA) nanoparticles. This study aimed to explore a new top-down process to produce PLGA nanoparticles. The fundamental strategy was to prepare spongelike PLGA microspheres with a highly porous texture and then crush them into submicron-sized particles via wet milling. Therefore, an ethyl formate-based ammonolysis method was developed to encapsulate progesterone into porous PLGA microspheres. Compared to a conventional solvent evaporation process, the ammonolysis technique helped reduce the tendency of drug crystallization and improved drug encapsulation efficiency accordingly (solvent evaporation, 27.6 ± 4.6%; ammonolysis, 65.1 ± 1.7%). Wet milling was performed on the highly porous microspheres with a D₅₀ of 64.8 μm under various milling conditions. The size of the grinding medium was the most crucial factor for our wet milling. Milling using smaller zirconium oxide beads (0.3~1 mm) was simply ineffective. However, when larger beads with diameters of 3 and 5 mm were used, our porous microspheres were ground into submicron-sized particles. The quality of the resultant PLGA nanoparticles was demonstrated by size distribution measurement and field emission scanning electron microscopy. The present top-down process that contrasts with conventional bottom-up approaches might find application in manufacturing drug-loaded PLGA nanoparticles.

Redox Nano-Architectures: Perspectives and Implications in Diagnosis and Treatment of Human Diseases

SIGNIFICANCE

Efficient targeted therapy with minimal side-effects is the need of the hour. Locally altered redox state is observed in several human ailments, such as inflammation, sepsis, and cancer. This has been taken advantage of in designing redox-responsive nanodrug carriers. Redox-responsive nanosystems open a door to a multitude of possibilities for the control of diseases over other drug delivery systems. Recent Advances: The first-generation nanotherapy relies on novel properties of nanomaterials to shield the drug and deliver it to the diseased tissue or organ. The second generation is based on targeting the drug or diagnostic material to the diseased cell-specific receptors, or to a particular organ to improve the efficacy of the drug. The third and the latest generation of nanocarriers, the stimuli-responsive nanocarriers exploit the disease condition or environment to specifically deliver the drug or diagnostic probe for the best diagnosis and treatment. Several different kinds of stimuli such as temperature, magnetic field, pH, and altered redox state-responsive nanosystems have educed immense promise in the field of nanomedicine and therapy.

CRITICAL ISSUES

We describe the evolution of nanomaterial since its inception with an emphasis on stimuli-responsive nanocarriers, especially redox-sensitive nanocarriers. Importantly, we discuss the future perspectives of redox-responsive nanocarriers and their implications.

FUTURE DIRECTIONS

Redox-responsive nanocarriers achieve a near-to-zero premature release of the drug, thus avoiding off-site toxicity associated with the free drug. This bears great potential for the development of more effective drug delivery with better pharmacokinetics and pharmacodynamics.

Synthesis of hesperetin-loaded PLGA nanoparticles by two different experimental design methods and biological evaluation of optimized nanoparticles

Hesperetin was effectively encapsulated into poly (d,l-lactic-co-glycolic acid) nanoparticles by using experimental design methods. A seven-factor Plackett-Burman design was used in order to determine the major process parameters. A significant linear equation, which shows the effect of each process parameter on encapsulation efficiency was developed, and then the most effective factors were determined. Further investigation and optimization was carried out by applying the three-factor three-level Box-Behnken design. Significant second-order mathematical models were developed by regression analysis of the experimental data for both responses: encapsulation efficiency and nanoparticle size. The two step experimental design allowed the synthesis of the desired nanoparticle formulations with maximum encapsulation efficiency (80.5 ± 4.9%) and minimum particle size (260.2 ± 16.5 nm) at optimum process conditions: 0.5% polyvinyl alcohol (PVA) concentration, 5.13 water:organic phase ratio, and 3.59 ml min^-1 flow rate of the emulsified solution into 0.1% PVA. Furthermore, the biological activity of these optimized nanoparticles were determined with antimicrobial activity and cytotoxicity studies; results were then compared to the free hesperetin. The cytotoxicity result revealed that hesperetin and hesperetin-loaded nanoparticles were biocompatible with normal cell line L929 fibroblast cells up to 184.83 and 190.88 μg ml^-1 for 24 h, and up to 133.24 and 134.80 μg ml^-1 for 48 h, respectively. In the antimicrobial study, the optimized nanoparticle showed inhibition activity (minimal inhibitory concentration (MIC) values were 125 μg ml^-1 for Escherichia coli, and 200 μg ml^-1 for Staphylococcus aureus), while the free hesperetin did not demonstrate activity in both strains (MIC value >200 μg ml^-1). These in vitro results may provide useful information for the investigation of hesperetin-loaded nanoparticles in diagnostic and therapeutic applications.

Hunter screening design to understand the product variability of solid dispersion formulation of a peptide antibiotic

The focus of present research was to understand and control the variability of solid dispersion (SD) formulation of non-ribosomal peptide antibiotic, vancomycin (VCM). Hunter screening design was constructed using seven independent variables namely melting temperature (X1), congealing temperature (X2), mixing time (X3), type of capsule shell (X4), filling method (X5), molecular weight of polyethylene glycol (PEG, X6) and surfactant type (X7), and responses measured were cumulative percentage of VCM released in 45 min (Y1) and potency (Y2). The SD formulations were prepared by melt-fusion method, and tested for dissolution, potency, and characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD) and near infrared chemical imaging (NIR-CI). Statistically significant (p<0.05) effect of congealing temperature (X2), type of capsule shell (X4), filling method (X5), molecular weight of PEG (X6) was revealed on Y1, and R(2) of 0.992 was obtained between experimental and predicted value. None of the factors have statistically significant (p>0.05) influence on Y2. SEM, DSC and PXRD indicated crystalline nature of SD formulations. Homogeneity of SD formulations was shown by NIR-CI images. In summary, the quality of VCM SD formulations could be assured by controlling the critical factors during manufacturing.

Evaluation of anticancer drug-loaded nanoparticle characteristics by nondestructive methodologies

The purpose of this study was to utilize near-infrared (NIR) spectroscopy and near-infrared chemical imaging (NIR-CI) as non-invasive techniques to evaluate the drug loading in letrozole-loaded PLGA nanoparticle formulations prepared by the emulsification-solvent evaporation method. A Plackett-Burman design was applied to evaluate the main effects of amount of drug (X(1)), amount of polymer (X(2)), stirring rate (X(3)), emulsifier concentration (X(4)), organic to aqueous phase volume ratio (X(5)), type of organic solvent (X(6)), and homogenization time (X(7)) on drug entrapment efficiency. The influence of three different spectral pretreatment methods (multiplicative scatter correction, standard normal variate, and Savitzky-Golay second derivative transformation with third-order polynomial) and two different regression methods (PLS regression and principal component regression (PCR)) on model prediction ability were compared. PLS of spectra that were pretreated with Savitzky-Golay second derivative transformation provided better model prediction than PCR as it revealed better linear correlation (correlation coefficient of 0.991) for both calibration and prediction models. Relatively low values of root mean square errors of calibration (RMSEC = 0.748) and prediction (RMSEP = 0.786) and low standard errors of calibration (SEC = 0.758) and prediction (SEP = 0.589) suggested good predictability for estimation of the loading of letrozole in PLGA nanoparticles. NIR-CI analysis also revealed mutual homogenous distribution of both polymer and drug and was capable of clearly distinguishing the 12 formulations both quantitatively and qualitatively. In conclusion, NIR and NIR-CI could be potentially used to characterize anticancer drug-loaded nanoparticulate matrix.

Risperidone solid dispersion for orally disintegrating tablet: its formulation design and non-destructive methods of evaluation

The focus of present investigation was to assess the utility of non-destructive techniques in the evaluation of risperidone solid dispersions (SD) with methyl-β-cyclodextrin (MBCD) and subsequent incorporation of the SD into orally disintegrating tablets (ODT) for a faster release of risperidone. The SD was prepared by a solvent evaporation method and evaluated by scanning electron microscopy (SEM), Fourier transform infrared (FTIR), near infrared spectroscopy (NIR), NIR-chemical imaging (NIR-CI), powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC). DSC and XRD analysis indicated that crystallinity of SD has reduced significantly. FTIR showed no interaction between risperidone and MBCD. Partial least square (PLS) was applied to the NIR data for the construction of chemometric models to determine both components of the SD. Good correlations were obtained for calibration and prediction as indicated by correlation coefficients >0.9965. The model was more accurate and less biased in predicting the MBCD than risperidone as indicated by its lower mean accuracy and mean bias values. SD-3 (risperidone:MBCD, 1:3) was incorporated into ODT tablets containing diluent (D-mannitol, FlowLac(®) 100 or galenIQ™-721) and superdisintegrant (Kollidon(®) CL-SF, Ac-Di-Sol or sodium starch glycolate). Disintegration time, T(50) and T(90) were decreased in the formulations containing mannitol and Kollidon(®) CL-SF, but increased with galenIQ™-721 and sodium starch glycolate, respectively. NIR-CI images confirmed the homogeneity of SD and ODT formulations.