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.     

Solubility prediction of clonazepam in aqueous mixtures of ethanol,polyethylene glycol 200 and propylene glycol at 30 °C

Solubility of clonazepam in aqueous binary mixtures of ethanol, polyethylene glycol 200 and propylene glycol was determined at 30 °C using the shake flask method. The maximum solubility of clonazepam was observed at volume fraction of 0.90 of ethanol, whereas for aqueous mixtures of polyethylene glycol 200 and propylene glycol, the maximum values were observed in the neat cosolvents. The generated data was fitted to the Jouyban-Acree model and its constants were computed, then the back-calculated solubilities were compared with the corresponding experimental values by calculating the mean percentage deviation (MPD) in which the overall MPD for three cosolvent systems was 7.0 %. The solubility data in cosolvent + water mixtures was predicted using previously trained versions of the Jouyban-Acree model and the prediction MPDs were 13.4, 54.2 and 24.9 %, respectively for ethanol, polyethylene glycol 200 and propylene glycol mixtures and the overall MPD was 30.8 %.     

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)%.     

Influence of solute structure on deviations from the log-linear solubility equation in propylene glycol:water mixtures

The solubilities of the methyl, ethyl, propyl, and butyl esters of p-hydroxy- and p-aminobenzoates have been determined in propylene glycol:water mixtures. The log of the observed solubility data in propylene glycol:water mixtures was examined for deviations from the following equation: In Xi = f In (Xc) + (1 - f) In (Xw), where Xi is the calculated mole fractional solubility of the solute, f is the volume fraction of cosolvent, Xc is the observed mole fractional solubility in the neat cosolvent, and Xw is the solubility in water. In each case, the deviations from the predicted solubilities demonstrated a characteristic pattern. Positive deviations were observed at high volume fractions of cosolvent, while negative deviations were observed at low volume fractions. The magnitude of the deviations at low volume fractions of cosolvent was related to the carbon chain length within each group of esters. A similar phenomenon was not observed at high volume fractions of cosolvent; however, the magnitude of the deviations was dependent on the nature of the polar group on the ester. The data are interpreted in terms of the possible effects of solvent structure on the solubility of the solutes.     

Moisture sorption kinetics for water-soluble substances. IV: Studies with mixtures of solids

This paper extends earlier work from this laboratory concerning the sorption kinetics of water vapor on deliquescent water-soluble substances to mixtures of these solids. A theoretical model, based on heat transport control, excellently predicted a priori the rate of water uptake by a variety of binary mixtures of alkali halides and sugars. The rates for mixtures containing highly water-soluble quaternary ammonium salts, as either one or both of the components, were less successfully predicted as the combined water solubilities of the two components increased. It is concluded that water-soluble deliquescent substances, normally encountered in pharmaceutical dosage forms, rapidly form saturated aqueous solutions in the aqueous film formed as water vapor uptake proceeds, and that the water uptake rate can be predicted a priori from known and experimentally determinable parameters using the heat transport model.     

Modeling drug solubility in water-cosolvent mixtures using an artificial neural network

Application of the artificial neural network (ANN) to calculate the solubility of drugs in water-cosolvent mixtures was shown using 35 experimental data sets. The networks employed were feedforward backpropagation errors with one hidden layer. The topology of neural network was optimized and the optimum topology achieved was a 6-5-1 architecture. All data points in each set were used to train the ANN and the solubilities were back-calculated employing the trained networks. The differences between calculated solubilities and experimental values was used as an accuracy criterion and defined as mean percentage deviation (MPD). The overall MPD (OMPD) and its S.D. obtained for 35 data sets was 0.90 +/- 0.65%. To assess the prediction capability of the method, five data points in each set were used as training set and the solubility at other solvent compositions were predicted using trained ANNs whereby the OMPD (+/-S.D.) for this analysis was 9.04 +/- 3.84%. All 496 data points from 35 data sets were used to train a general ANN model, then the solubilities were back-calculated using the trained network and MPD (+/-S.D.) was 24.76 +/- 14.76%. To test the prediction capability of the general ANN model, all data points with odd set numbers from 35 data sets were employed to train the ANN model, the solubility for the even data set numbers were predicted and the OMPD (+/-S.D.) was 55.97 +/- 57.88%. To provide a general ANN model for a given cosolvent, the experimental data points from each binary solvent were used to train ANN and back-calculated solubilities were used to calculate MPD values. The OMPD (+/-S.D.) for five cosolvent systems studied was 2.02 +/- 1.05%. A similar numerical analysis was used to calculate the solubility of structurally related drugs in a given binary solvent and the OMPD (+/-S.D.) was 4.70 +/- 2.02%. ANN model also trained using solubility data from a given drug in different cosolvent mixtures and the OMPD (+/-S.D.) obtained was 3.36 +/- 1.66%. The results for different numerical analyses using ANN were compared with those obtained from the most accurate multiple linear regression model, namely the combined nearly ideal binary solvent/Redlich-Kister equation, and the ANN model showed excellent superiority to the regression model.     

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.     

Thermochemical investigations of associated solutions: 5. Calculation of solute-solvent equilibrium constants from solubility in mixtures containing two complexing solvents

Solubilities are reported for carbazole in binary dibutyl ether plus 1-chlorohexane mixtures at 25 degrees C. Results of these measurements are compared with solution models developed for solubility in systems containing specific solute-solvent interactions. A simple stoichiometric complexation model based on a 1:1 carbazole:dibutyl ether complex could describe the measured solubility to within an average absolute deviation of 1.7%. The calculated equilibrium constant, though, was about one-half of values previously determined from carbazole solubilities in several binary dibutyl ether plus alkane mixtures. A more sophisticated solution model, derived by assuming both 1:1 carbazole: dibutyl ether and carbazole:chlorohexane complexes, could describe the solubilities to within 2.4%. This latter model enables the carbazole-chlorohexane association constant to be calculated from experimental carbazole solubilities and a priori knowledge of the carbazole-dibutyl ether equilibrium constant.     

Prediction of solubility in nonideal multicomponent systems using the UNIFAC group contribution model

There is a need to identify suitable blends of solvents to dissolve drugs. Empirical approaches, such as trial-and-error and response surface, require several solubility measurements. In this study the UNIFAC method was used to predict solubility in highly nonideal multicomponent systems in which only the solute enthalpy of fusion and melting point must by measured. UNIFAC combines a group contribution approach with the UNIQUAC model for activity coefficients. Parameters characterizing interactions among constituent groups of a molecule have been previously determined from binary vapor pressure data. These tabulated group parameters are used to predict activity coefficients for newly synthesized compounds. These coefficients, together with the ideal solubility, permit a prediction of solubility. The solubility of 4-hexylresorcinol in ethyl acetate, ethyl myristate, and hexane mixtures was both measured and calculated using UNIFAC. The predicted solubilities were within 10% of the experimental solubilities for all but 3 of 21 mixtures. Since the method accounted for positive and negative deviations from ideality in a hydrogen-bonding system of molecules having different sizes, it shows great potential for use in pharmacy.     

Thermochemical investigations of nearly ideal binary solvents. VII: Monomer and dimer models for solubility of benzoic acid in simple binary and ternary solvents

Solubilities are reported for benzoic acid at 25.0 degrees in binary mixtures of carbon tetrachloride with cyclohexane, n-hexane, or n-heptane and of cyclohexane with n-hexane or n-heptane and in ternary mixtures of carbon tetrachloride-cyclohexane-n-hexane and carbon tetrachloride-cyclohexane-n-heptane. Solubilities also are reported for benzoic acid in some binary solvents at 30.0 degrees and for m-toluic acid in binary mixtures of cyclohexane and n-hexane at 25.0 degrees. The results are compared to the predictions of equations developed previously for solubility in systems of purely nonspecific interactions, with the benzoic acids considered as either monomeric or dimeric molecules in solution. The dimer model gave more accurate predictions, with a maximum deviation of 4.4% between observed and predicted solubilities in all systems studied. Solubility maxima were predicted and observed for benzoic and m-toluic acids in cyclohexane-n-hexane and for benzoic acid in cyclohexane-n-heptane. The application of these solubility relationships to liquid-liquid partition coefficients is discussed.     

Mathematical representation of solute solubility in binary mixture of supercritical fluids by the Jouyban-Acree model

Applicability of a solution model for calculating the solute solubility in binary mixtures of supercritical fluids at different SCF compositions and pressures was shown using phenanthrene solubility data in supercritical carbon dioxide and supercritical ethane at 313 K and a pressure range of 100-350 bar. The correlation ability of the proposed model was evaluated by fitting all data points and computing error term employing back-calculated solubilities. The prediction capability of the model was assessed by dividing each data set to two subsets, namely training and test subsets. The predicted solubilities using trained models were used to calculate the prediction error term. The results show that both correlative and predictive error terms were less than the experimentally obtained RSD values.     

Solubility in binary solvent systems. IV. Prediction of naphthalene solubilities using the UNIFAC group contribution model

This work extends the UNIFAC group contribution method of solid-liquid equilibria to binary solvent mixtures, and compares its predictions to experimental solubilities for naphthalene in 16 different solvent mixtures. Deviations between experimental and calculated values are of the order of 10–20% for most solvent systems, and are comparable in magnitude to deviations noted in the pure solvents. The ability of the UNIFAC model to provide reasonable estimates of naphthalene solubilities based only on heat of fusion data and group contribution parameters suggests that the model may be useful in the area of drug design.     

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.     

Prediction of drug solubility in amphiphilic di-block copolymer micelles: the role of polymer-drug compatibility

The goal of the current study was to assess the value of predictive computational approaches for estimating drug solubility in hydrated micelles formed from di-block copolymers of polyethylene glycol (PEG) and random copolyesters of epsilon-caprolactone (CL) and trimethylene carbonate (TMC) using drug-polymer compatibility as assessed through the Flory-Huggins interaction parameter (chi). In order to accomplish this, the compatibility of several well-known model drugs (associated with the four biopharmaceutics classification system (BCS) classes) was assessed with both segments of the amphiphilic di-block copolymer PEG-b-P(CL-co-TMC). Compatibilities were estimated based on the Hansen modification of the Hildebrand approach using Molecular Modeling Pro software. Experimental solubilities for model drugs were determined using a shake-flask technique at various polymer concentrations. The solubilities of 8 compounds in 10% w/v micelle solutions were in relatively good agreement with the predicted drug-polymer compatibility. In addition, the approach allows for the selection of a suitable di-block copolymer for optimal solubilization of a specific drug. Furosemide was assessed as a model with results suggesting that it can be best entrapped in a di-block copolyester containing a relatively high CL content. The data suggests that prediction of drug solubilization of block copolymer-based micelles may be facilitated by assessing the compatibility of the drug for the component polymeric domains.     

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).     

Influence of propylene glycol as cosolvent on mechanisms of drug transport from hydrogels

The in vitro penetration of topical glucocorticoids (GC) betamethasone 17-valerate (BMV), hydrocortisone 17-butyrate (HCB) and hydrocortisone (HC) into an artificial lipid acceptor and excised human skin was examined using binary hydrogels with varying propylene glycol (PG) content. The relationship between the physicochemical properties of the model drugs in binary PG/water mixtures and the rate and extent of their penetration into artificial lipid membranes was studied. As a function of the drug solubility and partition behavior between lipid acceptor and PG/water mixtures, two directions were found in which PG affects the penetration of the GCs used. The lipophilic BMV, providing a higher solubility in the acceptor lipid than in PG/water mixtures of the formulations, penetrates thermodynamically controlled. In this case, PG acts only as cosolvent. For the more hydrophilic HC with higher solubilities in PG/water mixtures than in the acceptor medium, the amount penetrated increases with increasing PG content of the formulation. This result is surprising because of the expectation that the rate and extent of penetration decrease with decreasing partition coefficients. PG penetrates rapidly into the artificial acceptor and into excised human skin. It acts as both cosolvent and enhancer. In the case of HC transport, the enhancer effect is supposed to be a solvent drag effect of PG. HCB seems to penetrate thermodynamically controlled up to 40% PG. However, if PG contents of 60 and 80% are used in the gels the drag transport mechanism dominates. The results obtained from the studies with the lipophilic acceptor membranes were confirmed using excised human skin.