Extended hildebrand solubility approach: satranidazole in mixtures of dioxane and water

The extended Hildebrand solubility parameter approach is used to estimate the solubility of satranidazole in binary solvent systems. The solubility of satranidazole in various dioxane-water mixtures was analyzed in terms of solute-solvent interactions using a modified version of Hildebrand-Scatchard treatment for regular solutions. The solubility of satranidazole in the binary solvent, dioxane-water shows a bell-shaped profile with a solubility maximum well above the ideal solubility of the drug. This is attributed to solvation of the drug with the dioxane-water mixture, and indicates that the solute-solvent interaction energy is larger than the geometric mean (δ(1)δ(2)) of regular solution theory. The new approach provides an accurate prediction of solubility once the interaction energy is obtained. In this case, the energy term is regressed against a polynomial in δ(1) of the binary mixture. A quartic expression of W in terms of solvent solubility parameter was found for predicting the solubility of satranidazole in dioxane-water mixtures. The method has potential usefulness in preformulation and formulation studies during which solubility prediction is important for drug design.     

Solubility behavior of polymorphs I and II of mefenamic acid in solvent mixtures

The dissolution profile and solubility of two polymorphic forms of mefenamic acid were studied in solvent mixtures of ethanol-water and ethyl acetate-ethanol. The solubility parameter (delta) was used to study the effect of polarity on the solubility behavior of the two polymorphs. Differential scanning calorimetry and infrared spectroscopy were performed on the original powders and on the solid phases after contact with the solvent systems for the characterization and identification of the polymorphs. The dissolution rates of both polymorphs is greater in the less polar mixtures (ethyl acetate-ethanol) of lower solubility parameter values. Form II showed larger dissolution rates and saturation concentrations than Form I in all the solvent systems studied. The solid phase of Form II converts totally to Form I after equilibration with the solvents. The rate of conversion was faster in the least polar mixtures. The solubility of both polymorphs reaches a single maximum at 80% ethyl acetate in ethanol, delta = 20.09 MPa1/2. The modified extended Hildebrand method was used to predict the solubility profile of each polymorph. A single equation was obtained for both polymorphs which includes the solubility parameter of the mixtures and the logarithm of the solubility mole fraction of each polymorph in water. The Hildebrand solubility parameter of mefenamic acid is independent of the crystalline form and was determined from two methods giving quite similar values, delta 2 = 20-21 MPa1/2.     

Extended Hildebrand solubility approach: p-hydroxybenzoic acid in mixtures of dioxane and water

The extended Hildebrand solubility approach was used to reproduce the solubilities of p-hydroxybenzoic acid in a dioxane-water system. The solubility parameter of p-hydroxybenzoic acid was determined and found to be approximately 15 (cal/cm3)1/2. Residual plots (scattergrams) were used in conjunction with R2, F, and standard deviation values to determine whether a quadratic, cubic, quartic, or higher degree polynomial was required in the calculations. The earlier iteration method for back-calculations of solubilities was replaced by the more reliable root-finder method. The solubility profile of p-hydroxybenzoic acid in dioxane-water mixtures did not follow a log linear relationship even in the ranges where the solubility parameters of the water-cosolvent mixture might be expected to produce a straight-line function, as observed in other studies.     

Prediction of xanthine solubilities using statistical techniques

Mixture response-surface methodology can be used as a technique to predict solubility in mixed solvent systems. The present report shows that if the intent is to predict solubility in nonideal solutions, mixture response-surface methodology is a better technique than one which assumes a particular mechanism to hold true. This is demonstrated by comparing the predictive ability of the mixture response-surface model with that of an extended Hildebrand approach to nonideal solutions. The nonideal systems are those used by Martin and co-workers involving the solubility of theobromine, caffeine, and theophylline in dioxane-water mixtures.     

Solubility Prediction of Satranidazole in Aqueous N,N-dimethylformamide Mixtures Using Extended Hildebrand Solubility Approach

The solubility of satranidazole in several water–N,N-dimethylformamide mixtures was analysed in terms of solute–solvent interactions and data were treated on the basis of extended Hildebrand solubility approach. The solubility profile of satranidazole in water–N,N-dimethylformamide mixtures shows a curve with a solubility maxima well above the ideal solubility of drug. This is attributed to solvation of the drug with the water–N,N-dimethylformamide mixture, and indicates that the solute–solvent interaction energy (W) is larger than the geometric mean (δ₁δ₂) of regular solution theory. The new approach provides an accurate prediction of solubility once the interaction energy (W) is obtained. In this case, the energy term is regressed against a polynomial in δ₁ of the binary solvent mixture. A quartic expression of W in terms of solvent solubility parameter was found for predicting the mole fraction solubility of satranidazole in the studied mixtures. The method has potential usefulness in preformulation and formulation studies during which solubility prediction is important for drug design.     

A Modification of the Extended Hildebrand Approach to Predict the Solubility of Structurally Related Drugs in Solvent Mixtures

Abstract— A modification of the extended Hildebrand equation is proposed to estimate the solubility of an organic drug in solvent mixtures. The equation accurately reproduces the solubility of four sulphonamides in dioxane-water mixtures without requiring the heat of fusion of the solute. A single equation is obtained for predicting the solubility of related drugs using the solubilities of the drugs in the pure solvents, dioxane and water, and solute-solvent interaction terms consisting of the solubility parameter, δ₂, of the solute and the solubility parameter, δ₁, and basic partial solubility parameter, δ_1b, of the solvent mixture. By this procedure a single equation was obtained to estimate the solubilities of three xanthines in dioxane-water and another equation to obtain the solubilities of four sulphonamides. The equation obtained for sulphonamides is able to predict the experimental solubilities of two parent compounds, sulphasomidine and sulphathiazole, and the solubilities of a drug of different structure, p-hydroxybenzoic acid. This suggests that the intermolecular solute-solvent interaction of sulphonamides and p-hydroxybenzoic acid are similar. The results indicate that the solubility behaviour of drugs having different structures may be modelled using a common equation provided that they show similar solute-solvent interactions.     

Estimation of the solubility parameter of trimethoprim by current methods

Group contribution, the extended Hildebrand solubility (EHS) and the extended Hansen solubility approaches are utilised to estimate the solubility parameter value of trimethoprim. The solubility data in the binary solvent series showed peak solubility at the solubility parameter of solvent, 11.7 H. The regression expression on the lines of the EHS approach yielded 12.06 H. The data on the solubility of trimethoprim in individual solvents was processed as per the extended Hansen approach. The partial solubility parameters were obtained and are used to estimate the solubility parameter, 12.93 H. Extending the Flory-Huggins size correction to this approach gave a value of 10.95 H and improved the correlation coefficient by 3 percent. Partitioning of hydrogen bonding (four parameter approach) didn't improve the value.     

Solubility Prediction of Satranidazole in Propylene Glycol-Water Mixtures Using Extended Hildebrand Solubility Approach

Extended Hildebrand solubility approach is used to estimate the solubility of satranidazole in binary solvent systems. The solubility of satranidazole in various propylene glycol-water mixtures was analyzed in terms of solute-solvent interactions using a modified version of Hildebrand-Scatchard treatment for regular solutions. The solubility equation employs term interaction energy (W) to replace the geometric mean (δ₁δ₂), where δ₁ and δ₂ are the cohesive energy densities for the solvent and solute, respectively. The new equation provides an accurate prediction of solubility once the interaction energy, W, is obtained. In this case, the energy term is regressed against a polynomial in δ₁ of the binary mixture. A quartic expression of W in terms of solvent solubility parameter was found for predicting the solubility of satranidazole in propylene glycol-water mixtures. The expression yields an error in mole fraction solubility of ~3.74%, a value approximating that of the experimentally determined solubility. The method has potential usefulness in preformulation and formulation studies during which solubility prediction is important for drug design.     

Predicting the Solubility of Drugs in Solvent Mixtures: Multiple Solubility Maxima and the Chameleonic Effect

Abstract— An approach to reproduce the solubility profile of a drug in several solvent mixtures showing two solubility maxima is proposed in this work. The solubility of sulphamethoxypyridazine was determined at 25°C in several mixtures of varying polarity (hexane: ethyl acetate, ethyl acetate:ethanol and ethanol: water). Sulphamethoxypyridazine was chosen as a model drug because of its proton-donor and proton-acceptor properties. A plot of the mole fraction of the drug vs the solubility parameter of the solvent mixtures shows two solubility peaks. The two peaks found for sulphamethoxypyridazine demonstrate the chameleonic effect as described by Hoy and suggest that the solute-solvent interaction does not vary uniformly from one mixture to another. The different behaviour of the drug in mixtures of two proton-donor and proton-acceptor solvents (alcohol and water), and in mixtures of one proton acceptor (ethyl acetate) and one proton donor-proton acceptor (ethanol) is rationalized in terms of differences in the proton donor-acceptor ability of the solvent mixtures. An approach based on the acidic and basic partial solubility parameters together with the Hildebrand solubility parameter of the solvent mixtures is developed to reproduce the experimental results quantitatively. The equation predicts the two solubility maxima as found experimentally, and the calculated values closely correspond to the experimental values through the range composition of the solvent mixtures. These results show that the chameleonic effect can be described in a quantitative way in terms of Lewis acid-base interactions; this approach can assist the product formulator to choose the proper solvent mixture for a new drug. A good solvent blend should result in a solubility parameter close to that of the drug; the acidic and basic partial solubility parameter values should provide maximum acid-base interaction of the mixed solvent with the drug. The failure in one of these conditions results in decreased solubility. Solubility parameters as well as the acidic and basic parameters are tabulated or they can be obtained from group contribution methods, making easier the evaluation of the best solvent mixture for a drug.     

Relationship between swelling of hydroxypropylmethylcellulose and the Hansen and Karger partial solubility parameters

A model that relates the equilibrium swelling of hydroxypropylmethylcellulose to the partial solubility parameters of both the polymer and the solvents is proposed to interpret and correlate the experimental data. The non-specific interactions are expressed as the dispersion delta(d) and polar delta(p) solubility parameters of Hansen, or as a combination of both. Hydrogen bonding is represented by the acidic delta(a) and the basic delta(b) Karger solubility parameters. The results are compared with models including the same parameters for non-specific interactions (delta(d) and delta(p)) and the Hansen hydrogen bonding parameter delta(h). Equilibrium swelling of this hydrophilic polymer that is widely used in drug formulation is measured in pure solvents covering a wide polarity range. In a qualitative way, swelling increases in solvents with higher Hildebrand solubility parameters and stronger hydrogen bonding capability, and it decreases in non-polar solvents. Single polarity indexes, such as the Hildebrand solubility parameter or the partition coefficient (PC), do not fit well the overall experimental data. The best correlations were obtained with the proposed model, providing at the same time an interpretation consistent with the physical meaning of the terms included in the equation. Swelling increases as the non-specific interactions of the polymer and the solvents become alike, and as the Lewis acid-base interactions of the polymer (1) and the solvent (2) represented by the products delta(1a)delta(2b) and delta(1b)delta(2a) become greater. Conversely, hydrogen bonding self association of the solvents (the product delta(1a)delta(1b)) lowers swelling. The results show that the Karger hydrogen bonding parameters provide a better approach than the Hansen hydrogen bonding parameter to correlate the swelling behavior of a hydrophilic polymer.     

Thermodynamics of cosolvent action: phenacetin, salicylic acid and probenecid

The solubility of phenacetin, salicylic acid, and probenecid in ethanol-water and ethanol-ethyl acetate mixtures at several temperatures (15-40 degrees C) was measured. The solubility profiles are related to medium polarity changes. The apparent thermodynamic magnitudes and enthalpy-entropy relationships are related to the cosolvent action. Salicylic acid and probenecid show a single peak against the solubility parameter delta(1) of both solvent mixtures, at 40% (delta(1) = 21.70 MPa(1/2)) and 30% (delta(1) = 20.91 MPa(1/2)) ethanol in ethyl acetate, respectively. Phenacetin displays two peaks at 60% ethanol in ethyl acetate (23.30 MPa(1/2)) and 90% ethanol in water (delta(1) = 28.64 MPa(1/2)). The apparent enthalpies of solution display a maximum at 30% (phenacetin and salicylic acid) and 40% (probenecid) ethanol in water, respectively. Two different mechanisms, entropy at low ethanol ratios, and enthalpy at high ethanol ratios control the solubility enhancement in the aqueous mixture. In the nonaqueous mixture (ethanol-ethyl acetate) enthalpy is the driving force throughout the whole solvent composition for salicylic acid and phenacetin. For probenecid, the dominant mechanism shifts from entropy to enthalpy as the ethanol in ethyl acetate concentration increases. The enthalpy-entropy compensation plots corroborate the different mechanisms involved in the solubility enhancement by cosolvents.     

Solubility of pioglitazone hydrochloride in ethanol,N-methyl pyrrolidone,polyethylene glycols and water mixtures at 298.20 °K

Background and the purpose of the study

Solubility of pharmaceuticals is still a challenging subject and solubilization using cosolvents is the most common technique used in the pharmaceutical industry. The purpose of this study was reporting and modeling the experimental molar solubility of pioglitazone hydrochloride (PGZ-HCl) in binary and ternary mixtures of ethanol (EtOH), N-methyl pyrrolidone (NMP), polyethylene glycols (PEGs) 200, 400, 600 and water along with the density of saturated solutions at 298.2 °K.

Methods

To provide a computational method, the Jouyban-Acree model was fitted to the solubilities of the binary solvents, and solubilities of the ternary solvents were back-calculated by employing the solubility data in mono-solvents. In the next step, the ternary interaction terms were added to the model and the prediction overall mean percentage deviation (MPD) of the ternary data was reduced. Also a previously proposed version of the model was used to predict the solubility of PGZ-HCl in binary and ternary mixtures employing the experimental solubility data in mono-solvents.

Results

The overall MPD of the model for fitting the binary data and predicted data of ternary solvents were 2.0 % and 50.5 %, respectively. The overall MPD of the predicted solubilities in ternary solvents using the ternary interaction terms in the model was 34.2 %, and by using the proposed version of the Jouyban-Acree model for binary and ternary data the overall correlation and prediction errors were 18.0 and 15.0 %, respectively.

Conclusion

The solubility of PGZ-HCl was increased by addition of EtOH, NMP, PEGs 200, 400 and 600 to aqueous solutions. The reported data extended the available solubility data of pharmaceuticals which are crucial in formulation of liquid dosage forms. The constants of the Jouyban-Acree model using the generated data are also reported which provides the possibility of solubility prediction in other solvent mixtures and temperatures.     

Solubility prediction of salicylic acid in water-ethanol-propylene glycol mixtures using the Jouyban-Acree model

To show the applicability of a solution model, i.e. the Jouyban-Acree model, for predicting the solubility of a solute in ternary solvent systems based on model constants computed using solubility data of the solute in binary solvent systems, the solubility of salicylic acid in water-ethanol, water-propylene glycol, ethanol-propylene glycol mixtures was determined. A minimum number of three data points from each binary system was used to calculate the binary interaction parameters of the model. Then the solubility in other binary solvent compositions and also in a number of ternary solvents was predicted, and the mean percentage deviation (MPD) was calculated as an accuracy criterion. The overall MPD (+/-SD) was 7.3 (+/-7.3)% and those of a similar predictive model was 15.7 (+/-11.5)%. The mean difference between the proposed and a previous model was statistically significant (paired t-test, p < 0.004).     

Enthalpy-entropy compensation for the solubility of drugs in solvent mixtures: paracetamol, acetanilide, and nalidixic acid in dioxane-water

In earlier work, a nonlinear enthalpy-entropy compensation was observed for the solubility of phenacetin in dioxane-water mixtures. This effect had not been earlier reported for the solubility of drugs in solvent mixtures. To gain insight into the compensation effect, the behavior of the apparent thermodynamic magnitudes for the solubility of paracetamol, acetanilide, and nalidixic acid is studied in this work. The solubility of these drugs was measured at several temperatures in dioxane-water mixtures. DSC analysis was performed on the original powders and on the solid phases after equilibration with the solvent mixture. The thermal properties of the solid phases did not show significant changes. The three drugs display a solubility maximum against the cosolvent ratio. The solubility peaks of acetanilide and nalidixic acid shift to a more polar region at the higher temperatures. Nonlinear van't Hoff plots were observed for nalidixic acid whereas acetanilide and paracetamol show linear behavior at the temperature range studied. The apparent enthalpies of solution are endothermic going through a maximum at 50% dioxane. Two different mechanisms, entropy and enthalpy, are suggested to be the driving forces that increase the solubility of the three drugs. Solubility is entropy controlled at the water-rich region (0-50% dioxane) and enthalpy controlled at the dioxane-rich region (50-100% dioxane). The enthalpy-entropy compensation analysis also suggests that two different mechanisms, dependent on cosolvent ratio, are involved in the solubility enhancement of the three drugs. The plots of deltaH versus deltaG are nonlinear, and the slope changes from positive to negative above 50% dioxane. The compensation effect for the thermodynamic magnitudes of transfer from water to the aqueous mixtures can be described by a common empirical nonlinear relationship, with the exception of paracetamol, which follows a separate linear relationship at dioxane ratios above 50%. The results corroborate earlier findings with phenacetin. The similar pattern shown by the drugs studied suggests that the nonlinear enthalpy-entropy compensation effect may be characteristic of the solubility of semipolar drugs in dioxane-water mixtures.     

Thermodynamic modeling of activity coefficient and prediction of solubility: Part 1. Predictive models

A new activity coefficient model was developed from excess Gibbs free energy in the form G(ex) = cA(a) x(1)(b)...x(n)(b). The constants of the proposed model were considered to be function of solute and solvent dielectric constants, Hildebrand solubility parameters and specific volumes of solute and solvent molecules. The proposed model obeys the Gibbs-Duhem condition for activity coefficient models. To generalize the model and make it as a purely predictive model without any adjustable parameters, its constants were found using the experimental activity coefficient and physical properties of 20 vapor-liquid systems. The predictive capability of the proposed model was tested by calculating the activity coefficients of 41 binary vapor-liquid equilibrium systems and showed good agreement with the experimental data in comparison with two other predictive models, the UNIFAC and Hildebrand models. The only data used for the prediction of activity coefficients, were dielectric constants, Hildebrand solubility parameters, and specific volumes of the solute and solvent molecules. Furthermore, the proposed model was used to predict the activity coefficient of an organic compound, stearic acid, whose physical properties were available in methanol and 2-butanone. The predicted activity coefficient along with the thermal properties of the stearic acid were used to calculate the solubility of stearic acid in these two solvents and resulted in a better agreement with the experimental data compared to the UNIFAC and Hildebrand predictive models.