Prediction Of Drug Solubility Research Articles

Prediction of drug solubility by the general solubility equation (GSE).

The revised general solubility equation (GSE) proposed by Jain and Yalkowsky is used to estimate the aqueous solubility of a set of organic nonelectrolytes studied by Jorgensen and Duffy. The only inputs used in the GSE are the Celsius melting point (MP) and the octanol water partition coefficient (K(ow)). These are generally known, easily measured, or easily calculated. The GSE does not utilize any fitted parameters. The average absolute error for the 150 compounds is 0.43 compared to 0.56 with Jorgensen and Duffy's computational method, which utilitizes five fitted parameters. Thus, the revised GSE is simpler and provides a more accurate estimation of aqueous solubility of the same set of organic compounds. It is also more accurate than the original version of the GSE.

Prediction of drug solubility from Monte Carlo simulations

Monte Carlo statistical mechanics simulations have been carried out for 150 organic solutes in water. Physically significant descriptors such as the solvent-accessible surface area, numbers of hydrogen bonds, and indices for cohesive interactions in solids are correlated with pharmacologically important properties including octanol/water partition coefficient (log P) and aqueous solubility (log S). The regression equation for log S only requires five descriptors to provide a correlation coefficient, r2, of 0.9 and rms error of 0.7 for the 150 solutes. The descriptors can form a basis for structural modifications to guide an analogue's properties into desired ranges.

Prediction of Drug Solubility in Ternary Solvent Mixture

Applicability of the combined, nearly ideal, binary solvent/Redlich-Kister equation for calculating drug solubility in ternary mixtures is presented. The advantages of the proposed model are discussed and compared with a recently published equation that calculates the solute solubility in ternary solvent mixtures based on the mixture response methodology.

The Effects of pH and Mixed Solvent Systems on the Solubility of Oxytetracycline

The solubility of oxytetracycline (OTC) in aqueous and mixed solvent systems was studied. The effects of pH and cosolvent composition on the solubility and apparent dissociation constants (pK′a) of OTC were determined by a solubility method. The pK′a values of OTC in each mixed solvent system were estimated and used to generate expressions for predicting drug solubility in each cosolvent as a function of pH. Cosolvent systems of PEG 400, propylene glycol, glycerin, and 2-pyrrolidone were studied in the pH range of 2.5–9. Solubility results showed increased solubility with increased cosolvent concentration, especially in 2-pyrrolidone solvent systems. These results also showed that cosolvents enhanced drug solubility through either their effects on polarity of the solvent medium or complex formation with OTC. Aqueous and mixed solvent systems at lower pH values resulted in higher OTC solubilization because the drug existed primarily in its cationic form. A mass balance equation including all ionic species of OTC allowed for estimation of the intrinsic solubilities and pK′a values in each solvent system. pK′a values and intrinsic solubility of the OTC zwitterion increased with increasing cosolvent content. These parameters allowed prediction of drug solubility within the pH range and cosolvent concentrations used in this study.

A Statistical Experimental Approach to Cosolvent Formulation of a Water-Insoluble Drug

19-Nor-1α,25-dihydroxyvitamin D2, an analog of vitamin D2, is a nonpolar compound with limited solubility in water. An injectable solution was formulated using a cosolvent system consisting of water, ethanol, and propylene glycol. A statistical response surface approach was used to evaluate the effect of these three solvents on the solubility of the drug (25°C) in the ternary cosolvent system. The data generated from five selected formulations were used to develop a multiple linear regression model that quantitatively defines the solubility of the drug as a function of the cosolvent composition. Close agreement was found between the experimental data and data calculated using the model. The capability of this model to predict drug solubility in cosolvent systems with various combinations of the three solvents was also verified.

The Modified Wilson Model and Predicting Drug Solubility in Water-Cosolvent Mixtures.

Applicability of the modified Wilson model for calculating drug solubility in water-cosolvent mixtures is presented. The accuracy and predictability of the model are compared with those of other models which calculate solute solubility as a function of the solvent composition. Mean of percent deviations from experimental values are 7.77, 8.70, 9.06, 10.72, 10.72 and 18.71, for the modified Wilson, double-log exponential, general single model, combined nearly ideal binary solvent/Redlich-Kister, excess free energy and mixture response surface methods, respectively.

Chameleonic Effect and Some Models for Predicting Drug Solubility in Solvent Mixtures.

A new model derived from an excess free energy approach which expresses drug solubility in solvent mixtures showing multiple solubility peaks, the chameleonic effect, with respect to the concentrations of solvents in a mixture is proposed. Accuracy and predictability of the model are compared with those of a previous model which expresses drug solubility based on Hildebrand, acidic and basic solubility parameters. The results indicate that the new model is more accurate than the previous model and average percent mean errors are 5.32 and 13.66, respectively.

Local composition models in pharmaceutical chemistry. III. Prediction of drug solubility in binary aqueous mixtures

The UNIQUAC local composition model has been tested for its ability to predict the solubilizing effect of organic liquids on aqueous solutions of poorly soluble drugs. A minimum of one single experimentally measured solubility of a drug in pure water was required to predict its solubility profile in a binary mixture of water and an arbitrarily chosen organic solvent. Improved predictions were obtained when measured solubilities in pure organic co-solvent were used as input too. In principle, additional experimental information is not necessary when the number of added organic solvents is increased beyond one. The method was tested for various liquid solutes in acetic acid-water and ethanol-water, and for barbiturates in ethanol-water, xanthines in dioxane-water, hydrocortisone in propylene glycol-water, diethylstilbestrol in ethanol-water, and for a typical neuroleptic drug (pimozide) in acetic acid-water. Excellent predictions were obtained throughout. It is concluded that UNIQUAC provides a sIJPerior and generally applicable method for the computer-aided design of pharmaceutical formulations with increased solubility.

Extended hildebrand solubility approach: Solubility of theophylline in polar binary solvents

A quantitative approach is presented for predicting solubilities of crystalline compounds in binary solvent systems. The solubility of theophylline in mixed solvents consisting of dioxane and water was determined at 25 ± 0.1°. The solubilities across this range of polar solvents were back-calculated using a technique involving an interaction energy term, W. This parameter is regressed against a polynomial expression in δ1, the solubility parameter for the mixed solvents. Except for the end-points, solubilities were predicted within <12% and with considerably better accuracy in most cases. The new approach modifies the well-known Hildebrand solubility equation to make it applicable to polar systems. Although the method may be used with solutes in pure solvents, its greatest application appears to be the prediction of drug solubility in binary solvent mixtures.

Solubility Parameter of Selected Sulfonamides

This investigation was primarily concerned with the application of Hildebrand's solubility equation to the determination of the solubility parameter of selected sulfonamides. The vapor pressure of several selected solvent systems was determined by an isoteniscopic method. These data were used to calculate the solubility parameter of the mixed solvents. The heat of fusion of each sulfonamide was determined by differential thermal analysis. The solubility of the sulfonamides was measured in a series of solvent blends varying in polarity, and the solubility parameter of the sulfonamides was determined from their solubility data. An attempt was made to correlate the solubility parameter with the dielectric constant. The results were found to be linear with respect to the solvent blends of alcohol-water, alcohol-water-propylene glycol, water-glycerin, and dimethylacetamide-water-glycerin. Hildebrand's solubility concept appears to be a useful tool for predicting drug solubility where the solubility parameters of drug and solvent system are close to each other.