Effect of temperature and propylene glycol as a cosolvent on dissolution of clotrimazole.

Herein, the solubility study of clotrimazole was performed in a propylene glycol+water system. The solubility values were fitted to various cosolvency equations. The model accuracies were studied with the computation of the mean relative deviations. The thermodynamic behavior was investigated according to the van't Hoff and Gibbs equations for clotrimazole in the propylene glycol+water system. Furthermore, the density data for clotrimazole were determined in mixtures of propylene glycol+water and fitted to the Jouyban-Acree equation.

A principal component analysis approach for developing retention models in liquid chromatography.

Three retention models for liquid chromatography are developed using principal component analysis (PCA). It is shown that they exhibit features similar to that of the model based on linear solvation energy relationship (LSER). However, the fitting performance of the PCA models is better than that of the LSER model, the performance of which can be considerably improved by the use of artificial neural networks. In addition, the possibility of using the proposed models as well as the LSER model to predict the retention times of solutes under chromatographic conditions at which these solutes have never been studied is also examined by means of three data sets of analytes consisting of non-polar compounds to polar compounds with a variety of functional groups.

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.

Determination of phenytoin and its major metabolite in human serum by MEKC.

Determination of phenytoin in biological fluids is necessary due to its non-linear pharmacokinetics and narrow therapeutic index. A simple and rapid micellar electrokinetic chromatographic method was developed for simultaneous determination of phenytoin and its main metabolite, 5-(4-hydroxyphenyl)-5-phenylhydantoin, in human serum. The separation was carried out using fused-silica capillary and UV detector at 214 nm. The background electrolyte consisted of borate buffer (10 mM, pH 10.5) with 50 mM sodium dodecyl sulphate as pseudostationary phase. The calibration graphs were linear at the concentration range of 5-30 mg/mL, and the detection limits for phenytoin and 5-(4-hydroxyphenyl)-5-phenylhydantoin added to blank serum were 1.8 and 1.5 mg/mL, respectively. The obtained results demonstrated that the proposed method is suitable for the serum phenytoin analysis in terms of selectivity and simplicity.

Mathematical representation of xanthine oxidase activity in hydro-organic mixtures.

A mathematical model is proposed to calculate the enzyme activity in different concentrations of the organic solvent in hydro-organic mixtures. The accuracy and predictability of the model have been evaluated employing experimentally determined xanthine oxidase activity in five hydro-organic mixtures by using absolute percentage mean deviation (APMD). The obtained APMD for correlative and predictive studies were 5.3% and 7.6%, respectively.

Catalytic activity and stability of xanthine oxidase in aqueous-organic mixtures.

In the present study, bovine milk xanthine oxidase activity in various aqueous-organic mixtures and the effects of pH, temperature, and lyophilization on the enzyme activity have been investigated. The enzyme was incubated with xanthine as the substrate in Sorenson's phosphate buffer (pH 7.0) containing 0.1 mM EDTA, and the activity was determined spectrophotometrically in the absence and presence of different fractions of nine water-miscible organic solvents at 27-50 degrees C and at different pH values ranging from 6 to 9. The organic solvents reduced the enzyme activity to different extents. In spite of these inhibitory effects, the enzyme showed relatively good stability in the aqueous-organic mixtures compared with the aqueous medium. A significant increase in the activity of the lyophilized enzyme was observed in pure organic solvents.

Solubility prediction of solutes in aqueous mixtures of ethylene glycols.

The applicability of a trained version of the Jouyban-Acree model, for predicting the solubility of solutes in aqueous mixtures of ethylene glycol and its polymerized forms was shown. The solubilities of 8 drugs in binary mixtures were determined and the mean percentage deviation (MPD) was calculated as a prediction accuracy criterion and the overall MPD (+/- SD) was 23.2 (+/- 13.1)%.

A new definition of solubilization power of a cosolvent.

The solubilization power of a cosolvent is defined based on the maximum solubility of a solute in the water-cosolvent mixtures (X(m,max)) and the corresponding solvent composition (f(c,max)) predicted by trained versions of the Jouyban-Acree model. The applicability of the proposed definition was checked using solubility data of three cosolvent systems where the solubilization power was ordered as: dioxane > ethanol > polyethylene glycol 400. Using this definition, one could select the most appropriate cosolvent for solubilization of a poorly water soluble drug. There are linear relationships between the solubilization power of a cosolvent and the solute's logarithm of partition coefficients.

Deviations of drug solubility in water-cosolvent mixtures from the Jouyban-Acree model--effect of solute structure.

Deviations of the predicted solubilities using the Jouyban-Acree model from experimental data were correlated to the structural descritptors of the drugs computed by HyperChem software. The proposed models are able to predict the solubility in water-cosolvent mixtures and reduced the mean percentage deviations (MPD) of predicted solubilities from 24%, 48%, and 53% to 16%, 33% and 38%, respectively for water-propylene glycol, water-ethanol and water-polyethylene glycol 400 mixtures, with the overall improvement in prediction capability of the model being approximately 13%.

PVC membrane sensor for diclofenac: applications in pharmaceutical analysis and drug binding studies.

A PVC membrane sensor for diclofenac based on its ion pair complex with silver is prepared. The influences of membrane composition (PVC, plasticizer, and ion pair complex), pH of test solution and presence of other anions on the performance of the electrode were investigated. The optimized membrane demonstrates Nernstian response (-58.9 +/- 0.2 mV/decade) for diclofenac anions over a wide linear range from 5.2 x 10(-5) to 1.1 x 10(-2) M at 25 +/- 1 degree C. The potentiometric response is independent from pH at the range of 6.0-9.5. The advantages of the proposed sensor are: easy preparation, good selectivity and fast response time. It was successfully used for determination of diclofenac in pharmaceuticals and also in potentiometric study of interaction of diclofenac with bovine serum albumin. The results of diclofenac assay with the proposed sensor were in good agreement with the official HPLC method.

Solubility prediction of drugs in water-cosolvent mixtures using Abraham solvation parameters.

PURPOSE: To provide predictive cosolvency models, the Abraham solvation parameters of solutes and the solvent coefficients were combined with the Jouyban-Acree and the log-linear models. These models require two and one solubility data points to predict the solubility of drugs in water-cosolvent mixtures. Ab initio prediction methods also were employed and the results were discussed. METHOD: The Jouyban-Acree model constants were correlated with variables derived from the Abraham solvation parameters of solutes and the solvent coefficients to present quantitative structure property relationship (QSPR) models. The calculated model constants using the QSPR models were used to predict the solubility in water-cosolvent mixtures. The mean percentage deviation (MPD), average absolute error (AAE) and root mean square error (RMSE) criteria were calculated to show the accuracy of the predictions. RESULTS: The overall MPD (+/-SD) of the proposed method employing solubility data in mono-solvents, i.e. two data points for each set, was 18.5+/-12.0 which indicates an acceptable prediction error from the practical point of view. The best cosolvency model employing aqueous solubility data was produced overall MPD of 75.2+/-72.6. The overall MPD of the proposed ab initio method was 74.9+/-19.3%. The models produced the same accuracy pattern considering MPD, AAE and RMSE criteria. CONCLUSION: The proposed model employing two solubility data points for each set produced acceptable prediction error (>>18%) and could be recommended for practical applications in pharmaceutical industry. MPD, AAE and RMSE criteria produced similar results considering various models. However, MPD criterion was preferred since its numerical values could be compared with experimental relative standard deviations for repeated experiments.

Prediction of drug solubility in water-propylene glycol mixtures using Jouyban-Acree model.

A trained version of the Jouyban-Acree model was presented to predict drug solubility in water-propylene glycol mixtures at various temperatures. The model is able to predict the solubility in various solubility units and requires the experimental solubility of a solute in mono-solvent systems. The mean percentage deviation (MPD) of predicted solubilities was computed to show the accuracy of the predicted data and 24% was found as the average MPD for 27 data sets studied. The proposed model enables the researchers to predict solubiliy in water-propylene glycol mixtures at various temperatures and reduces the number of required experimental data from five to two points.

Prediction of the optimized solvent composition for solubilization of drugs in water-cosolvent mixtures.

The capability of the Jouyban-Acree model for predicting the optimized solvent composition of binary solvents for solubilization of drugs is shown employing solubility of drugs in aqueous mixtures of dioxane, ethanol and polyethylene glycol 400. The established model constants of the Jouyban-Acree model and solubility of drugs in water and cosolvent are used to predict the maximum solubility of in the binary solvent mixture (log Xm(max)) and the corresponding solvent composition (f1,max). The accuracy of the predicted log Xm(max) and f1,max is studied using average absolute error (AAE) of predicted and observed values. The AAEs were 0.10 +/- 0.12 and 0.08 +/- 0.10, respectively for log Xm(max) and f1,max. The method provided acceptable predictions and is recommended for practical applications. The main advantage of the proposed method is its extension to temperatures higher/lower than room temperature.

In silico prediction of drug solubility in water-dioxane mixtures using the Jouyban-Acree model.

A numerical method based on the Jouyban-Acree model was presented for prediction of drug solubility in water-dioxane mixtures at various temperatures. The method requires drug solubility in monosolvent systems, i.e. two data points for each temperature of interest. The mean percentage deviation (MPD) of predicted solubilities was calculated to show the accuracy of the predicted data and 27% was found as the average MPD for 36 data sets studied. The proposed numerical method reduced the number of required experimental data from five to two points and could also be extended to predict solubility at various temperatures.

Mathematical representation of solubility of amino acids in binary aqueous-organic solvent mixtures at various temperatures using the Jouyban-Acree model.

Applicability of a solution model for calculating solubility of amino acids in binary aqueous-organic solvent mixtures at various temperatures was shown. The accuracy of the proposed model was evaluated by computing mean percentage deviation (MPD) employing available solubility data of amino acids in binary solvents at various temperatures from the literature. The overall MPD (+/- SD) for correlation of solubility data was 16.5 +/- 8.8%. In addition, the equations calculating solubility of amino acids in binary solvent mixtures at a fixed temperature was revisited.

In silico prediction of drug solubility in water-ethanol mixtures using Jouyban-Acree model.

PURPOSE: A predictive method was proposed to predict solubility of drugs in water-ethanol mixtures at various temperatures based on the Jouyban-Acree model. The model requires the experimental solubility data of the drug in mono-solvent systems. METHODS: The accuracy of the proposed prediction method was evaluated using collected experimental solubility data from the literature. The proposed method is: log Xm,T = fc log Xc,T + fw log Xw,T + fcfw[724.21/T + 485.17(fc-fw)/T + 194.41(fc-fw)2/T] Where Xm,T, Xc,T and Xw,T are the solute solubility at temperature (T) in mixed solvent and neat cosolvent and water, respectively, fc and fw denote the solute free fraction of cosolvent (ethanol) and water. The average absolute error (AAE) of the experimental and the predicted solubilities was computed as an accuracy criterion and compared with that of a well-established log-linear model. RESULTS: The AAE (+/-SD) of the Jouyban-Acree and log-linear models were 0.19 (+/-0.13) and 0.48 (+/-0.28), respectively. The mean difference of AAEs was statistically significant (p < 0.0005) revealing that the Jouyban-Acree model was provided more accurate predictions. Although the log-linear model was used to predict solubility at a fixed temperature (25 or 23 degrees C), the results also showed that the model could be employed to predict the solubility in solvent mixtures at various temperatures. CONCLUSION: More accurate predictions were provided using the Jouyban-Acree model in comparison with a previously established log-linear model of Yalkowsky. The prediction methods were successfully extended to predict the solubility in water-ethanol mixtures at various 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).

Correlation of retention factor of analytes in quaternary solvent mobile phases using the Jouyban-Acree model.

The Jouyban-Acree model has been used for the mathematical representation of retention factors of phenobarbital, phenytoin and carbamazepine in quaternary aqueous-organic solvent mobile phases. The accuracy of the proposed model is evaluated using average percentage deviation (APD) of experimental and calculated values as an accuracy criterion. The obtained mean and standard deviation of APDs of the model is 4.2 +/- 0.5%. The results showed that the Jouyban-Acree model provided accurate calculations and could be used in practice to speed up the method development process in which quaternary solvent mobile phases are required.

Mathematical representation of analyte's capacity factor in binary solvent mobile phases using the Jouyban-Acree model.

Applicability of a solution model, namely the Jouyban-Acree model, for mathematical representation of capacity factors of phenobarbital, phenytoin and carbamazepine in mobile phases containing water and the organic modifiers: methanol, acetonitrile, acetone and tetrahydrofuran and also a number of data sets collected from the literature has been shown. The accuracy of the proposed model is compared with those of the linear model and the quadratic equation using average percentage deviation (APD) as an accuracy criterion. The obtained mean and standard deviation of APDs of the Jouyban-Acree, linear and quadratic models are 8.1 +/- 8.4, 25.2 +/- 18.0 and 14.5 +/- 16.2%, respectively. The results showed that the Jouyban-Acree model provided more accurate calculations than the previously published models and the mean differences were statistically significant (p < 0.002).