Application of CO2 Supercritical Fluid to Optimize the Solubility of Oxaprozin: Development of Novel Machine Learning Predictive Models.

Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO2) for particle engineering. SCCO2 has great potential for application as a green and eco-friendly technique to reach small crystalline particles with narrow particle size distribution. In this paper, an artificial intelligence (AI) method has been used as an efficient and versatile tool to predict and consequently optimize the solubility of oxaprozin in SCCO2 systems. Three learning methods, including multi-layer perceptron (MLP), Kriging or Gaussian process regression (GPR), and k-nearest neighbors (KNN) are selected to make models on the tiny dataset. The dataset includes 32 data points with two input parameters (temperature and pressure) and one output (solubility). The optimized models were tested with standard metrics. MLP, GPR, and KNN have error rates of 2.079 × 10-8, 2.173 × 10-9, and 1.372 × 10-8, respectively, using MSE metrics. Additionally, in terms of R-squared, they have scores of 0.868, 0.997, and 0.999, respectively. The optimal inputs are the same as the maximum possible values and are paired with a solubility of 1.26 × 10-3 as an output.

Development and optimization of oral nanoemulsion of rutin for enhancing its dissolution rate, permeability, and oral bioavailability.

Rutin-loaded nanoemulsion (NE-RU) formulation is the core research work in this report. Labrafil® M 1944 CS was used as the oil phase, Tween 80 as the surfactant, and Transcutol P as the co-surfactant in the preparation of nanoemulsion. By utilizing a three-level central composite design (CCD), the composition was optimized. The optimized formulation showed a droplet size of 98.53 ± 3.22 nm, zeta potential -46.70 ± 4.78 mV, and drug loading 92.34 ± 3.87%. The results of dissolution, permeability, and oral bioavailability showed about 25.55 folds, 1.98 folds, and 33.68 folds, respectively, in the case of NE-RU as compared to its naïve form. The response of fresh and aged NE was non-significantly different in terms of particle size, zeta potential, and drug loading, indicating that the formulation was stable. The successful development of NE-RU with an improved bioavailability profile suggested that this formulation might be used to examine the pharmacodynamics of oxidative stress-related metabolic disorders.

Efficacy of SPG-ODN 1826 Nanovehicles in Inducing M1 Phenotype through TLR-9 Activation in Murine Alveolar J774A.1 Cells: Plausible Nano-Immunotherapy for Lung Carcinoma.

Alveolar macrophages are the first line of defense against intruding pathogens and play a critical role in cancer immunology. The Toll-like receptor (TLR) family mediates an important role in recognizing and mounting an immune response against intruding microbes. TLR-9 is a member of the intracellular TLR family, which recognizes unmethylated CG motifs from the prokaryotic genome. Upon its activation, TLR-9 triggers downstream of the MyD-88-dependent transcriptional activation of NF-κB, and subsequently results in abundant inflammatory cytokines expression that induces a profound inflammatory milieu. The present exploratory investigation aimed at elucidating the potency of schizophyllan for entrapping ODN 1826 (SPG-ODN 1826)-mediated stimulation of TLR-9 in provoking an inflammatory-type response in murine alveolar macrophages. Schizophyllan (SPG), a representative of the ß-glucan family, was used in the present study as a nanovehicle for endosomal trafficking of CpG ODN 1826. TEM analysis of SPG-ODN 1826 nanovehicles revealed that the prepared nanovehicles are spherical and have an average size of about 100 nm. Interestingly, SPG-ODN 1826 nanovehicles were competent in delivering their therapeutic payload within endosomes of murine alveolar macrophage (J774A.1) cells. Exposure of these nanovehicles within LPS stimulated J774A.1, resulted in a significant provocation of reactive oxygen species (ROS) (p < 0.01) in comparison to CpG ODN 1826 alone. Moreover, the formulated nanovehicles succeeded in generating a profound Th1-based cytokine profile constituted by enhanced expression of IFN-γ (p < 0.001) and IL-1ß (p < 0.001) inflammatory cytokines. These findings clearly indicated the immunostimulatory potential of SPG-ODN 1826 nanovehicles for inducing the Th1-type phenotype, which would certainly assist in skewing M2 phenotype into the much-desired M1 type during lung cancer.

Sustained release and enhanced oral bioavailability of rivaroxaban by PLGA nanoparticles with no food effect.

The purpose of the currents study was to enhance bioavailability of rivaroxaban (RXB) and reduce the food effect. RXB loaded PLGA nanoparticles (RXB-PLGA-NPs) were prepared by emulsion solvent evaporation method and optimized using central composite design (CDD). The optimized RXB-PLGA-NPs (F8) with composition, PLGA (125 mg), PVA (0.5%w/w) and RXB (20 mg) was found optimum with particle size (496 ± 8.5 nm), PDI (0.607), ZP (- 18.41 ± 3.14 mV), %EE (87.9 ± 8.6) and %DL (9.5 ± 1.6). The optimized NPs (F8) was further evaluated in vitro for DSC, FTIR, SEM and in vitro release studies. A comparative pharmacokinetic studies with commercial tablet (XARELTO®) were conducted on fasted and fed state rats. Compared to commercial tablet (XARELTO®), the RXB-PLGA-NPs (F8) exhibited a significant enhancement of bioavailability in both fasted and fed state. In addition, the bioavailability of RXB from NPs (F8) was found unaffected in the presence of food.

Development of spray-dried amorphous solid dispersions of tadalafil using glycyrrhizin for enhanced dissolution and aphrodisiac activity in male rats.

Tadalafil (TDL) is a phosphodiesterase-5 inhibitor (PDE5I), indicated for erectile dysfunction (ED). However, TDL exhibits poor aqueous solubility and dissolution rate, which may limit its application. This study aims to prepare amorphous solid dispersion (ASD) by spray-drying, using glycyrrhizin-a natural drug carrier. Particle and physicochemical characterizations were performed by particle size, polydispersity index measurement, yield, drug content estimation, Fourier Transformed Infrared (FTIR) spectroscopy, Differential scanning calorimetry (DSC), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and dissolution study. In order to evaluate the aphrodisiac activity of the prepared ASD, sexual behavior study was performed in male rats. It is further considered for the stability study. Our results revealed that TDL-GLZ spray-dried dispersion was a successful drug-carrier binary mixture. XRD and SEM showed that ASD of TDL with GLZ presented in the amorphous state and dented-spherical shape, unlike the drug indicating crystalline and spiked shaped. The optimized ASD3 formulation with particle size (1.92 µm), PDI (0.32), yield (97.78%) and drug content (85.00%) showed 4.07 folds' increase in dissolution rate compared to pure TDL. The results obtained from the in vivo study exhibit significantly improved aphrodisiac activity with ASD3. The stability study revealed that the prepared ASD3 did not show any remarkable changes in the dissolution and drug content for 1 month storage at room temperature.

Co-delivery of gemcitabine and simvastatin through PLGA polymeric nanoparticles for the treatment of pancreatic cancer: in-vitro characterization, cellular uptake, and pharmacokinetic studies.

Despite the ongoing extensive research, cancer therapeutics still remains an area with unmet needs which is hampered by shortfall in the development of newer medicines. The present study discusses a nano-based combinational approach for treating solid tumor. Dual-loaded nanoparticles encapsulating gemcitabine HCl (GM) and simvastatin (SV) were fabricated by double emulsion solvent evaporation method and optimized. Optimized nanoparticles showed a particle size of 258 ± 2.4 nm, polydispersity index of 0.32 ± 0.052, and zeta potential of -12.5 mV. The size and the morphology of the particles wee further confirmed by transmission electron microscopy (TEM) and scanning electron microscopy, respectively of the particles. The entrapment efficiency of GM and SV in the nanoparticles was 38.5 ± 4.5% and 72.2 ± 5.6%, respectively. The in vitro release profile was studied for 60 h and showed Higuchi release pattern. The cell toxicity was done using MTT assay and lower IC50 was obtained with the nanoparticles as compared to the pure drug. The bioavailability of GM and SV in PLGA nanoparticles was enhanced by 1.4-fold and 1.3-fold respectively, compared to drug solution. The results revealed that co-delivery of GM and SV could be used for its oral delivery for the effective treatment of pancreatic cancer.

Estimating the Solubility, Solution Thermodynamics, and Molecular Interaction of Aliskiren Hemifumarate in Alkylimidazolium Based Ionic Liquids.

Estimating the solubility and solution thermodynamics parameters of aliskiren hemifumarate (AHF) in three different room temperature ionic liquids (RTILs), Transcutol-HP (THP) and water are interesting as there is no solubility data available in the literature. In the current study, the solubility and solution thermodynamics of AHF in three different RTILs, THP and water at the temperature range from 298.2 to 318.2 K under air pressure 0.1 MP were evaluated. The solid phase evaluation by Differential Scanning Calorimetry (DSC) and Powder X-ray Diffraction (PXRD) indicated no conversion of AHF into polymorph. The mole fraction solubility of AHF was found to be highest in 1-hexyl-3-methylimidazolium hexafluorophosphate (HMMHFP) ionic liquid (7.46 × 10-2) at 318.2 K. The obtained solubility values of AHF was regressed by the Apelblat and van't Hoff models with overall root mean square deviations (RMSD) of 0.62% and 1.42%, respectively. The ideal solubility of AHF was higher compared to experimental solubility values at different temperatures. The lowest activity coefficient was found in HMMHFP, which confirmed highest molecular interaction between AHF-HMMHFP. The estimated thermodynamic parameters confirmed endothermic and entropy driven dissolution of AHF in different RTILs, THP, and water.

Nano-encapsulation and characterization of baricitinib using poly-lactic-glycolic acid co-polymer.

Baricitinib is a recently approved anti-rheumatic drug having very poor aqueous solubility and hence its performance suffers from low or inconsistent oral bioavailability. The purpose of the study was to develop and evaluate poly lactic-co-glycolic acid (PLGA) nanoparticles of baricitinib in order to enhance in vitro dissolution and performance. Nano-suspension of baricitinib with or without PLGA, a biodegradable, FDA approved semi-synthetic polymer, was developed by nanoprecipitation method. Research methodology employed a quantitative research utilizing experimental design wherein effect of independent variables such as amount of polymer, drug: polymer ratio, types of solvent, and solvent: anti-solvent ratio were evaluated over the size and size distribution of nanoparticles along with entrapment efficiencies. Among the several organic phases evaluated, acetone was found to be suitable solvent for drug and polymer. The aqueous phase (anti-solvent) was deionized water containing 1% w/v pluronic 127 as the stabilizer of nanoparticle suspension. The optimized nanoparticles had particle size less than 100 nm (91 nm ±â€¯6.23) with a very narrow size distribution (0.169 ±â€¯0.003), high zeta potential (-12.5 mV ±â€¯5.46) and entrapment efficiency (88.0%). The optimized nanoparticles were characterized by scanning electron microscopy, X-ray diffraction, differential scanning calorimetry, infrared spectroscopy and in vitro dissolution studies. In-vitro dissolution study of PLGA nanoparticles exhibited sustained release with approximately 93% release of baricitinib during 24-h period.

Patient-centered medical home care access among adults with chronic conditions: National Estimates from the medical expenditure panel survey.

BACKGROUND: The Patient-Centered Medical Home (PCMH) model is a coordinated-care model that has served as a means to improve several chronic disease outcomes and reduce management costs. However, access to PCMH has not been explored among adults suffering from chronic conditions in the United States. Therefore, the aim of this study was to describe the changes in receiving PCMH among adults suffering from chronic conditions that occurred from 2010 through 2015 and to identify predisposing, enabling, and need factors associated with receiving a PCMH. METHODS: A cross-sectional analysis was conducted for adults with chronic conditions, using data from the 2010-2015 Medical Expenditure Panel Surveys (MEPS). Most common chronic conditions in the United States were identified by using the most recent data published by the Agency for Healthcare Research and Quality (AHRQ). The definition established by the AHRQ was used as the basis to determine whether respondents had access to PCMH. Multivariate logistic regression analyses were conducted to detect the association between the different variables and access to PCMH care. RESULTS: A total of 20,403 patients with chronic conditions were identified, representing 213.7 million U.S. lives. Approximately 19.7% of the patients were categorized as the PCMH group at baseline who met all the PCMH criteria defined in this paper. Overall, the percentage of adults with chronic conditions who received a PCMH decreased from 22.3% in 2010 to 17.8% in 2015. The multivariate analyses revealed that several subgroups, including individuals aged 66 and older, separated, insured by public insurance or uninsured, from low-income families, residing in the South or the West, and with poor health, were less likely to have access to PCMH. CONCLUSION: Our findings showed strong insufficiencies in access to a PCMH between 2010 and 2015, potentially driven by many factors. Thus, more resources and efforts need to be devoted to reducing the barriers to PCMH care which may improve the overall health of Americans with chronic conditions.

Mixing of low-dose cohesive drug and overcoming of pre-blending step using a new gentle-wing high-shear mixer granulator.

The objective of this study was to examine the influence of drug amount and mixing time on the homogeneity and content uniformity of a low-dose drug formulation during the dry mixing step using a new gentle-wing high-shear mixer. Moreover, the study investigated the influence of drug incorporation mode on the content uniformity of tablets manufactured by different methods. Albuterol sulfate was selected as a model drug and was blended with the other excipients at two different levels, 1% w/w and 5% w/w at impeller speed of 300 rpm and chopper speed of 3000 rpm for 30 min. Utilizing a 1 ml unit side-sampling thief probe, triplicate samples were taken from nine different positions in the mixer bowl at selected time points. Two methods were used for manufacturing of tablets, direct compression and wet granulation. The produced tablets were sampled at the beginning, middle, and end of the compression cycle. An analysis of variance analysis indicated the significant effect (p < .05) of drug amount on the content uniformity of the powder blend and the corresponding tablets. For 1% w/w and 5% w/w formulations, incorporation of the drug in the granulating fluid provided tablets with excellent content uniformity and very low relative standard deviation (∼0.61%) during the whole tableting cycle compared to direct compression and granulation method with dry incorporation mode of the drug. Overall, gentle-wing mixer is a good candidate for mixing of low-dose cohesive drug and provides tablets with acceptable content uniformity with no need for pre-blending step.

Anticancer Efficacy of Self-Nanoemulsifying Drug Delivery System of Sunitinib Malate.

Sunitinib malate (SM) is reported as a weakly soluble drug in water due to its poor dissolution rate and oral bioavailability. Hence, in the current study, various "self-nanoemulsifying drug delivery systems (SNEDDS)" of SM were prepared, characterized and evaluated for the enhancement of its in vitro dissolution rate and anticancer efficacy. On the basis of solubilization potential of SM in various excipients, "Lauroglycol-90 (oil), Triton-X100 (surfactant) and Transcutol-P (cosurfactant)" were selected for the preparation of SM SNEDDS. SM-loaded SNEDDS were developed by spontaneous emulsification method, characterized and evaluated for "thermodynamic stability, self-nanoemulsification efficiency, droplet size, polydispersity index (PDI), zeta potential (ZP), surface morphology, refractive index (RI), the percent of transmittance (% T) and drug release profile." In vitro dissolution rate of SM was significantly enhanced from an optimized SNEDDS in comparison with SM suspension. The optimized SNEDDS of SM with droplet size of 42.3 nm, PDI value of 0.174, ZP value of -36.4 mV, RI value of 1.339, % T value of 97.3%, and drug release profile of 95.4% (after 24 h via dialysis membrane) was selected for in vitro anticancer efficacy in human colon cancer cells (HT-29) by MTT assay. MTT assay indicated significant anticancer efficacy of optimized SM SNEDDS against HT-29 cells in comparison with free SM. The results of this study showed the great potential of SNEDDS in the enhancement of in vitro dissolution rate and anticancer efficacy of poorly soluble drug such as SM.

Optimization of hot melt extrusion parameters for sphericity and hardness of polymeric face-cut pellets.

The aim of this study was to formulate face-cut, melt-extruded pellets, and to optimize hot melt process parameters to obtain maximized sphericity and hardness by utilizing Soluplus(®) as a polymeric carrier and carbamazepine (CBZ) as a model drug. Thermal gravimetric analysis (TGA) was used to detect thermal stability of CBZ. The Box-Behnken design for response surface methodology was developed using three factors, processing temperature ( °C), feeding rate (%), and screw speed (rpm), which resulted in 17 experimental runs. The influence of these factors on pellet sphericity and mechanical characteristics was assessed and evaluated for each experimental run. Pellets with optimal sphericity and mechanical properties were chosen for further characterization. This included differential scanning calorimetry, drug release, hardness friability index (HFI), flowability, bulk density, tapped density, Carr's index, and fourier transform infrared radiation (FTIR) spectroscopy. TGA data showed no drug degradation upon heating to 190 °C. Hot melt extrusion processing conditions were found to have a significant effect on the pellet shape and hardness profile. Pellets with maximum sphericity and hardness exhibited no crystalline peak after extrusion. The rate of drug release was affected mainly by pellet size, where smaller pellets released the drug faster. All optimized formulations were found to be of superior hardness and not friable. The flow properties of optimized pellets were excellent with high bulk and tapped density.

Influence of Molecular Weight of Carriers and Processing Parameters on the Extrudability, Drug Release, and Stability of Fenofibrate Formulations Processed by Hot-Melt Extrusion.

The objective of this study was to investigate the extrudability, drug release, and stability of fenofibrate (FF) formulations utilizing various hot-melt extrusion processing parameters and polyvinylpyrrolidone (PVP) polymers of various molecular weights. The different PVP grades selected for this study were Kollidon® 12 PF (K12), Kollidon® 30 (K30), and Kollidon® 90 F (K90). FF was extruded with these polymers at three drug loadings (15%, 25%, and 35% w/w). Additionally, for FF combined with each of the successfully extruded PVP grades (K12 and K30), the effects of two levels of processing parameters for screw design, screw speed, and barrel temperature were assessed. It was found that the FF with (K90) was not extrudable up to 35% drug loading. With low drug loading, the polymer viscosity significantly influenced the release of FF. The crystallinity remaining was vital in the highest drug-loaded formulation dissolution profile, and the glass transition temperature of the polymer significantly affected its stability. Modifying the screw configuration resulted in more than 95% post-extrusion drug content of the FF-K30 formulations. In contrast to FF-K30 formulations, FF release and stability with K12 were significantly influenced by the extrusion temperature and screw speed.

Stability-enhanced hot-melt extruded amorphous solid dispersions via combinations of Soluplus® and HPMCAS-HF.

The aim of this study was to evaluate a novel combination of Soluplus® and hypromellose acetate succinate (HPMCAS-HF) polymers for solubility enhancement as well as enhanced physicochemical stability of the produced amorphous solid dispersions. This was accomplished by converting the poorly water-soluble crystalline form of carbamazepine into a more soluble amorphous form within the polymeric blends. Carbamazepine (CBZ), a Biopharmaceutics Classification System class II active pharmaceutical ingredient (API) with multiple polymorphs, was utilized as a model drug. Hot-melt extrusion (HME) processing was used to prepare solid dispersions utilizing blends of polymers. Drug loading showed a significant effect on the dissolution rate of CBZ in all of the tested ratios of Soluplus® and HPMCAS-HF. CBZ was completely miscible in the polymeric blends of Soluplus® and HPMCAS-HF up to 40% drug loading. The extrudates were characterized by differential scanning calorimetry (DSC), X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy and dissolution studies. DSC and XRD data confirmed the formation of amorphous solid dispersions of CBZ in the polymeric blends of Soluplus® and HPMCAS-HF. Drug loading and release of CBZ was increased with Soluplus® (when used as the primary matrix polymer) when formulations contained Soluplus® with 7-21% (w/w) HPMCAS-HF. In addition, this blend of polymers was found to be physically and chemically stable at 40°C, 75% RH over 12 months without any dissolution rate changes.

Modeling and validation of drug release kinetics using hybrid method for prediction of drug efficiency and novel formulations.

This paper presents a thorough examination for drug release from a polymeric matrix to improve understanding of drug release behavior for tissue regeneration. A comprehensive model was developed utilizing mass transfer and machine learning (ML). In the machine learning section, three distinct regression models, namely, Decision Tree Regression (DTR), Passive Aggressive Regression (PAR), and Quadratic Polynomial Regression (QPR) applied to a comprehensive dataset of drug release. The dataset includes r(m) and z(m) inputs, with corresponding concentration of solute in the matrix (C) as response. The primary objective is to assess and compare the predictive performance of these models in finding the correlation between input parameters and chemical concentrations. The hyper-parameter optimization process is executed using Sequential Model-Based Optimization (SMBO), ensuring the robustness of the models in handling the complexity of the controlled drug release. The Decision Tree Regression model exhibits outstanding predictive accuracy, with an R2 score of 0.99887, RMSE of 9.0092E-06, MAE of 3.51486E-06, and a Max Error of 6.87000E-05. This exceptional performance underscores the model's capability to discern intricate patterns within the drug release dataset. The Passive Aggressive Regression model, while displaying a slightly lower R2 score of 0.94652, demonstrates commendable predictive capabilities with an RMSE of 6.0438E-05, MAE of 4.82782E-05, and a Max Error of 2.36600E-04. The model's effectiveness in capturing non-linear relationships within the dataset is evident. The Quadratic Polynomial Regression model, designed to accommodate quadratic relationships, yields a noteworthy R2 score of 0.95382, along with an RMSE of 5.6655E-05, MAE of 4.49198E-05, and a Max Error of 1.86375E-04. These results affirm the model's proficiency in capturing the inherent complexities of the drug release system.

Optimization of tamoxifen solubility in carbon dioxide supercritical fluid and investigating other molecular targets using advanced artificial intelligence models.

Particle size, shape and morphology can be considered as the most significant functional parameters, their effects on increasing the performance of oral solid dosage formulation are indisputable. Supercritical Carbon dioxide fluid (SCCO2) technology is an effective approach to control the above-mentioned parameters in oral solid dosage formulation. In this study, drug solubility measuring is investigated based on artificial intelligence model using carbon dioxide as a common supercritical solvent, at different pressure and temperature, 120-400 bar, 308-338 K. The results indicate that pressure has a strong effect on drug solubility. In this investigation, Decision Tree (DT), Adaptive Boosted Decision Trees (ADA-DT), and Nu-SVR regression models are used for the first time as a novel model on the available data, which have two inputs, including pressure, X1 = P(bar) and temperature, X2 = T(K). Also, output is Y = solubility. With an R-squared score, DT, ADA-DT, and Nu-SVR showed results of 0.836, 0.921, and 0.813. Also, in terms of MAE, they showed error rates of 4.30E-06, 1.95E-06, and 3.45E-06. Another metric is RMSE, in which DT, ADA-DT, and Nu-SVR showed error rates of 4.96E-06, 2.34E-06, and 5.26E-06, respectively. Due to the analysis outputs, ADA-DT selected as the best and novel model and the find optimal outputs can be shown via vector: (x1 = 309, x2 = 317.39, Y1 = 7.03e-05).

Optimization and Characterization of Cuscuta reflexa Extract Loaded Phytosomes by the Box-Behnken Design to Improve the Oral Bioavailability.

The purpose of this study is to determine whether the complexing hydroalcoholic extract of Cuscuta reflexa (HECR) with phosphatidyl choline increases its bioavailability. As a result, a novel phytosomal delivery system for the HECR-soya lecithin complex was developed (HECR-phytosome). The HECR-phytosome complex was synthesized and characterized as phytovesicles. The formulation was prepared using a variable concentration of soya lecithin (1:1-1:3 percent w/v), a temperature range of (45-65°C), and sonication time (4-8 min). Optimization of HECR-loaded phytosomal formulations was performed using Design Expert software. A three-factor, three-level Box-Behnken design was used to optimize this HECR delivery system, as dependent variables, vesicular size and entrapment efficiency were evaluated using a Box Behnken factorial design. Further characterization of the optimized formulation included vesicle size, PDI, zeta potential, entrapment efficiency, FTIR, DSC, TEM, and in vitro release. Vesicle sizes ranged from 173.5±6.17 nm to 215.9±6.53 nm, and response rates for entrapment efficiency ranged from 52.9±1.65 to 77.2±1.1%. The uniform structure and spherical shape were demonstrated by transmission electron microscopy. Among the drug release kinetic models, the formulation followed the Higuchi model (R2 = 0.9978), releasing 96.3±3.7% of the polyphenol and flavonoids phytoconstituents from HECR-loaded phytosomes in 12 hours, compared to 49.3±2.5% in the plain extract. In addition, the optimized formulation passes the stability test. Therefore, the results demonstrated that phytosomal nanocarriers have the potential to increase the bioavailability of Cuscuta reflexa extract.

Formulation of Chitosan-Coated Brigatinib Nanospanlastics: Optimization, Characterization, Stability Assessment and In-Vitro Cytotoxicity Activity against H-1975 Cell Lines.

The purpose of the current study was to develop Brigatinib (BGT)-loaded nanospanlastics (BGT-loaded NSPs) (S1-S13) containing Span 60 with different edge activators (Tween 80 and Pluronic F127) and optimized based on the vesicle size, zeta potential (ZP), and percent entrapment efficiency (%EE) using Design-Expert® software. The optimum formula was recommended with desirability of 0.819 and composed of Span-60:Tween 80 at a ratio of 4:1 and 10 min as a sonication time (S13). It showed predicted EE% (81.58%), vesicle size (386.55 nm), and ZP (-29.51 mv). The optimized nanospanlastics (S13) was further coated with chitosan and further evaluated for Differential Scanning Calorimetry (DSC), X-ray Diffraction (XRD), in vitro release, Transmission Electron Microscopy (TEM), stability and in-vitro cytotoxicity studies against H-1975 lung cancer cell lines. The DSC and XRD revealed complete encapsulation of the drug. TEM imagery revealed spherical nanovesicles with a smooth surface. Also, the coated formula showed high stability for three months in two different conditions. Moreover, it resulted in improved and sustained drug release than free BGT suspension and exhibited Higuchi kinetic release mechanism. The cytotoxic activity of BGT-loaded SPs (S13) was enhanced three times in comparison to free the BGT drug against the H-1975 cell lines. Overall, these results confirmed that BGT-loaded SPs could be a promising nanocarrier to improve the anticancer efficacy of BGT.

Amphotericin B-PEG Conjugates of ZnO Nanoparticles: Enhancement Antifungal Activity with Minimal Toxicity.

Amphotericin B (AMB) is commonly used to treat life-threatening systemic fungal infections. AMB formulations that are more efficient and less nephrotoxic are currently unmet needs. In the current study, new ZnO-PEGylated AMB (ZnO-AMB-PEG) nanoparticles (NPs) were synthesized and their antifungal effects on the Candida spp. were investigated. The size and zeta potential values of AMB-PEG and ZnO-AMB-PEG NPs were 216.2 ± 26.9 to 662.3 ± 24.7 nm and -11.8 ± 2.02 to -14.2 ± 0.94 mV, respectively. The FTIR, XRD, and EDX spectra indicated that the PEG-enclosed AMB was capped by ZnO, and SEM images revealed the ZnO distribution on the surface NPs. In comparison to ZnO-AMB NPs and free AMB against C.albicans and C.neoformans, ZnO-AMB-PEG NPs significantly reduced the MIC and MFC. After a week of single and multiple dosage, the toxicity was investigated utilizing in vitro blood hemolysis, in vivo nephrotoxicity, and hepatic functions. ZnO-AMB-PEG significantly lowered WBC count and hematocrit concentrations when compared to AMB and ZnO-AMB. RBC count and hemoglobulin content, on the other hand, were unaltered. ZnO-AMB-PEG considerably lowered creatinine and blood urea nitrogen (BUN) levels when compared to AMB and ZnO-AMB. The difference in liver function indicators was determined to be minor by all formulae. These findings imply that ZnO-AMB-PEG could be utilized in the clinic with little nephrotoxicity, although more research is needed to determine the formulation's in vivo efficacy.

Computational simulation and target prediction studies of solubility optimization of decitabine through supercritical solvent.

Computational analysis of drug solubility was carried out using machine learning approach. The solubility of Decitabine as model drug in supercritical CO2 was studied as function of pressure and temperature to assess the feasibility of that for production of nanomedicine to enhance the solubility. The data was collected for solubility optimization of Decitabine at the temperature 308-338 K, and pressure 120-400 bar used as the inputs to the machine learning models. A dataset of 32 data points and two inputs (P and T) have been applied to optimize the solubility. The only output is Y = solubility, which is Decitabine mole fraction solubility in the solvent. The developed models are three models including Kernel Ridge Regression (KRR), Decision tree Regression (DTR), and Gaussian process (GPR), which are used for the first time as a novel model. These models are optimized using their hyper-parameters tuning and then assessed using standard metrics, which shows R2-score, KRR, DTR, and GPR equal to 0.806, 0.891, and 0.998. Also, the MAE metric shows 1.08E-04, 7.40E-05, and 9.73E-06 error rates in the same order. The other metric is MAPE, in which the KRR error rate is 4.64E-01, DTR shows an error rate equal to 1.63E-01, and GPR as the best mode illustrates 5.06E-02. Finally, analysis using the best model (GPR) reveals that increasing both inputs results in an increase in the solubility of Decitabine. The optimal values are (P = 400, T = 3.38E + 02, Y = 1.07E-03).