The Use of High Surface Area Silica and Supercritical Carbon Dioxide to Enhance Solubility of Poorly Water-Soluble Drugs

Purpose Poor water-solubility of BCS class II drugs can limit their commercialization because of reduced oral bioavailability. It has been reported that loading of drug by adsorption onto porous silica would enhance drug solubility due to the increased surface area available for solvent diffusion. In this work, solid dispersions are formed using supercritical carbon dioxide (scCO2). The aim of this research was to characterise the solid-state properties of scCO2 dispersion and to investigate the impact of altering scCO2 processing conditions on final amorphous product performance that could lead to enhancement of drug dissolution rate for BCS class II drugs. Methods Indomethacin (IND) was purchased from Sigma-Aldrich (Dorset, UK) and was used as a model drug with two grades of high surface area silica (average particle sizes 3&[micro] and 7&[micro]), which were obtained directly from Grace-Davison (Germany). Material crystallinity was evaluated using powder X-ray diffraction (PXRD, Rigaku™, miniflex II, Japan) and high-speed differential scanning calorimetry (Hyper-DSC 8000, Perkin Elmer, USA). Materials were placed in a high-pressure vessel consisting of a CO2 cylinder, a Thar™ Technologies P50 high-pressure pump and a 750 ml high-pressure vessel (Thar, USA). Physical mixtures were exposed to CO2 gas above its critical conditions. SEM imaging and elemental analysis were conducted using a Jeol 6500 FEGSEM (Advanced MicroBeam Inc., Austria). Drug release was examined using USP type II dissolution tester (Caleva™, UK). Results The two grades of silica were found to be amorphous using PXRD and Hyper-DSC. Using PXRD, it was shown that an increase in incubation time and pressure resulted in a decrease in the crystalline content. Drug release profiles from the two different silica formulations prepared under the same conditions are shown in Figure 1. It was found that there was a significant enhancement in drug release, which was influenced, by silica type and other experiment conditions such as temperature, pressure and exposure time. SEM imaging and elemental analysis showed drug deposited inside silica pores as well as on the outer surface. Conclusion This project has shown that silica carrier platforms may be used as an alternative approach to generating polymeric solid dispersions of amorphous drugs exhibiting enhanced solubility.

Properties of Hydraulic Jump over Apparent Corrugated Beds

The characteristics of hydraulic jumps were investigated for three shapes of artificial apparent corrugated beds in a horizontal rectangular flume. Rectangular, triangular, and circular-shaped tire waste corrugated beds were used. Froude number ranged from 2.75 to 4.25. The experimental observations included water surface profiles, bed shear stress, and the hydraulic jump length. Results showed that the shape of the corrugation had relatively insignificant effects on hydraulic jump properties for small Froude numbers. The rectangular, triangular, and circular-shaped corrugated beds reduced the hydraulic jump length by up to 7, 10, and 11%, respectively. The corrugated bed also reduced the tailwater depth by up to 11.5% compared with the smooth bed. The apparent conditions of corrugated bed reduced the hydraulic jump relative length and height by about 0.4 and 0.5, respectively. The circular-shaped tire waste was found to be more effective in reducing the length and depth of the hydraulic jump.

Modelling the fresh properties of self-compacting concrete using support vector machine approach

The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.