Papers by Keyword: Ibuprofen

Abstract: Nanocomposite hydrogels using poly(ethylene glycol) dimethacrylate (PEGDMA) as matrix, cellulose nanosphere (CNS) as reinforcing filler, and ibuprofen as model drug was prepared by UV-curing. Gel content was found to decrease with the addition of CNS to the hydrogel matrix. The water uptake analysis demonstrated that the hydrogels exhibit a higher water absorption over time when CNS is present. Entrapment efficiency analysis showed that ibuprofen was entrapped uniformly in the nanocomposite hydrogels. Drug release tests revealed that the inclusion of CNS caused a delay in the initial burst release of ibuprofen from the polymeric system. The drug's migration into the dissolution fluid is determined by the rate at which water infiltrates and the erosion of the hydrogel. Incorporating CNS into the hydrogel matrix enhances its density and creates attractive forces for the drug, hence enhancing the properties of the hydrogel matrix.

Abstract: Mesoporous silica nanocomposite (MSNC) with a wall thick of around 10 nm were created using Fe₃O₄ nanoparticles as the inorganic template. In accordance with the results of SEM and BET analysis, MSNC were homogenous spherical particles with good dispersion, and their specific surface area it possible that Ibuprofen will become stuck within the MSNC carrier. Loading of drug shows a decline in a surface area from 225.08 to 69.25 m² g^-1, pore volume from 0.56 to 0.13cm g^-1 and the pore diameter from 7.96 to 6.74 nm correspondingly. The amount of Ibuprofen entrapped in the carrier was measured by UV spectroscopy and total glycerol (TG) measurement, respectively. It was determined pore size distribution of MSNC changed before and after Ibuprofen entrapment. The release profile of Ibuprofen from MSNC was characterised by a three-stage pattern with an influence on the time between each stage.

Abstract: A study of the molecular anchoring and inclusion complex of the R/S-ibuprofen chiral compound with α-1-acid glycoprotein (AGP) has been carried out. This study aimed to predict the chiral separation of ibuprofen using chiral column filled with AGP protein. The geometrical optimization of R/S-ibuprofen was conducted on different calculation methods to obtain the optimal molecular structure. Molecular docking approaches, specifically docking using AutodockTools software were used to predict R/S-ibuprofen separation in AGP chiral column by comparing the binding energy values and the type of interaction. Results of the study show that the best method for optimizing the geometry of ibuprofen is Density Functional Theory (DFT). Furthermore, the results of the specific anchoring of ibuprofen on the AGP shows that the binding energy of S-ibuprofen with AGP is more negative than that of R-ibuprofen, namely -5.63 and -5.55 kcal/mol, respectively, indicating that S-ibuprofen interacts more strongly with AGP and therefore it will be eluted from the AGP chiral column later after R-ibuprofen.

Abstract: Ibuprofen is a nonsteroidal anti-inflammatory drug classified as one of the emerging contaminants from the pharmaceuticals group. Ibuprofen detected in the environment indicates that wastewater treatment facilities have a limited ability to remove this substance. Residual ibuprofen that accumulates continuously can harm ecosystems in the waters and indirectly affect human health. Adsorption using porous material is a method that can reduce the amount of ibuprofen in wastewater. This research synthesized porous carbon by pyrolysis of phenolic polymer. The resulting material was then characterized using an N₂-sorption analyzer, SEM, and XRD. After being characterized, the material was used to adsorb ibuprofen at various concentrations. SEM characterization showed that carbon had voids or channels for adsorbing ibuprofen molecules. N₂-sorption analyzer delivered that the polymer-derived carbon has a specific surface area of about ​​594 m² g^-1. Based on the adsorption test result, the porous carbon could adsorb the ibuprofen molecules in the simulated wastewater well and followed the Freundlich equilibrium model.

Abstract: Wood sawdust, one the high volume agricultural wastes in Nigeria, occupies space and constitutes environmental nuisance. Burning, it produces green house gases. Converting it to adsorbents is economical and environmental benign. This work assessed the adsorptive capacities of two Danielliaoliveri sawdust-based adsorbents for the removal of ibuprofen from waste stream. The sawdust was carbonized and activated with ZnCl₂ and H₃PO₄ to produce adsorbents code-named ZCAC and PAAC respectively. The physicochemical properties of the adsorbents were determined and batch adsorption experiments performed. The optimum pH for the adsorption of ibuprofen onto the ZCAC and PAAC was 3. The isotherm studies revealed that the Ibuprofen (IBU)-ZCAC system data fitted Redlich-Peterson and Langmuir models. The data also fitted Pseudo-second order and Boyd kinetics, defined intraparticle diffusion of the adsorbate molecules. The process was physical and endothermic. For the adsorption onto PAAC, the data fitted the Freundlich and the Halsey models. The data also fitted the Pseudo-second order and the Elovich kinetics. The process was endothermic. The adsorption capacities of ZCAC and PAAC for IBU were 3.876 and 15.385 mg/g respectively. ZCAC and PAAC were promising adsorbents for remediation of wastewater contaminated with ibuprofen.

Abstract: The paper presents the co-crystal screening study of carbamazepine (CBZ) and ibuprofen (IBU) as a co-crystal former (CCF) using non-stoichiometric (solid addition of CBZ to saturated solution of co-crystal former (CCF) and stoichiometric (1:1 mol of CBZ and CCF) methods. In the non-stoichiometric method, CBZ-IBU co-crystal was prepared in various solvents and left to equilibrate in three conditions; stagnant, manually agitated and shaking in 72 hours whereas in the stoichiometric method, evaporation, solvent drop grinding and dry grinding were used. The crystals produced from the screening process were characterized using differential scanning calorimetry (DSC) and optical microscopy. The co-crystal of CBZ-IBU was found to have successfully formed via the non-stoichiometric method in formic acid. DSC analysis revealed that the remaining crystals produced were either CBZ or IBU as indicated by their respective melting point.

Abstract: Co-crystallization process has been used in pharmaceutical industry in producing new class of API solids due to its advantages such as physical stability and solubility.The objective of this study is to characterize the co-crystal formation of ibuprofen with saccharin as a co-crystal former through wet milling by using XRD, FTIR and DSC. A study of co-crystal formation from ibuprofen and saccharin has been conducted by using wet milling with the presence of solvent. The PXRD results showed a new phase which is believed a new crystalline has been successfully formed. The DSC analysis showed a new melting point for the new phase. However, the functional group assessment showed the presence of an unknown functional group in the system.

Abstract: The purpose of this study was to prepare ibuprofen loaded solid lipid nanoparticles (IBU-SLNs) that is, effective in oral drug delivery. IBU-SLNs were synthesized by co-precipitation of rapid expansion of supercritical solution (CO-RESS). The produced SLNs consisted of stearic acid as lipid matrix. The unprocessed stearic acid, ibuprofen and IBU-SLNs were characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), differential scanning calorimetry (DSC), fourier transform infrared spectrophotometry (FTIR) and high performance liquid chromatography (HPLC). XRD patterns along with DSC showed that ibuprofen was present in both amorphous and crystalline form within lipid matrix. FTIR showed that molecular interactions that could alter the chemical structure of the IBU did not occur. The RESS process could produce ultrafine spherical particles of SLNs with high drug loading capacity. The IBU dissolution profile showed that the formulated SLNs have effectively increased the IBU solubility

Abstract: The aim of the study was to develop neural network model to predict the yield obtained from ultrasound-assisted anti-solvent crystallization of ibuprofen in terms of formulation and processing factors. The different factors of anti-solvent crystallization method, such as type of additive, concentration of additive, sonication time and harvesting time, were used as independent variables. The ibuprofen yield was used as response variable. The correlation between independent and response variables was investigated using feed forward-back propagation neural networks. The goodness of fit test and predictability were used for optimization of in silico models. The results revealed that the type of polyethylene glycol (PEG) was a critical factor that affected the response variable in different patterns. The best artificial neural networks (ANNs) model with a configuration of 3-4-1 for input, hidden, and output layers gave the r² of 0.7067 and 0.8729 and the root mean square error of 0.3693 and 0.2667 for the model using PEG 400 and PEG 4000, respectively. The predictive ability of these models was validated by a set of 4 formulations that were not included in the training set. The predicted and experimental of ibuprofen yields were correlated.

Abstract: In this study, the vertically aligned titania nanotube arrays (TNTs) was fabricated on the surface of titanium substrate in fluoride-containing electrolytes via self-ordering electrochemical anodization. The prepared TNTs loaded with ibuprofen (IBU) by solvothermal to achieve a local drug delivery system and its release properties were investigated. The samples were characterized by field emission scanning electronic microscope (FE-SEM), X-ray diffraction (XRD), Fourier transform infrared (FT-IR). The results indicated that the IBU drug molecules were successfully loaded on the surface of TNTs and the drug release shows a sustained release process. It suggested that TNTs as drug carrier had the properties of sustained release which have a good application prospect in biomedical field.