Nonlinear enthalpy-entropy compensation for the solubility of phenacetin in dioxane-water solvent mixtures

Dissolution Thermodynamics of the Solubility of Sulfamethazine in (Acetonitrile + 1-Propanol) Mixtures

Background: Solubility is one of the most important parameters in the research and development processes of the pharmaceutical industry. In this context, cosolubility is one of the most used strategies to improve the solubility of poorly soluble drugs, besides allowing to identify some factors involved in the dissolution process. The aim of this research is to evaluate the solubility of sulfamethazine in acetotinitrile + 1-propanol cosolvent mixtures at 9 temperatures (278.15, 283.15, 288.15, 293.15, 298.15, 303.15, 308.15, 313.15, and 318.15 K); a drug used in human and veterinary therapy and two solvents of great chemical-pharmaceutical interest. Methods: The determination was carried out by the shaking flask method and the drug was quantified by UV/Vis spectrophotometry. Results: The solubility of sulfamethazine increases from pure 1-propanol (solvent in which it reaches its lowest solubility at 278.15 K) to pure acetonitrile (solvent in which it reaches its maximum solubility at 318.15 K), behaving in a logarithmic-linear fashion. Conclusions: The increase in solubility is related to the acid/base character of the cosolvent mixtures and not to the solubility parameter of the mixtures. The dissolution process is endothermic and favored by the solution entropy, and also shows a strong entropic compensation.

Thermodynamic Assessment of the Pyrazinamide Dissolution Process in Some Organic Solvents

Pyrazinamide is a first line drug used for the treatment of tuberculosis, a pathology that caused the death of more than 1.3 million people in the world during 2022, according to WHO, being a drug of current interest due to its relevance in pharmaceutical and medical sciences. In this context, solubility is one of the most important physicochemical parameters in the development and/or optimization of new pharmaceutical forms, so the present work aims to present a thermodynamic study of the solubility of pyrazinamide in nine organic solvents of pharmaceutical interest. Using the shake-flask method and UV/Vis spectrophotometry, the solubility of this drug was determined at 9 temperatures; the maximum solubility was obtained in dimethyl sulfoxide at 318.15 K (x2=0.0816±0.004) and the minimum in cyclohexane at 283.15 K (1.73±0.05×10-5). From the apparent solubility data, the thermodynamic functions of solution and mixing were calculated, indicating an endothermic process. In addition, the solubility parameter of pyrazinamide was calculated using the Hoftyzer-van Krevelen (32.90 MPa1/2) and Bustamante (28.14 MPa1/2) methods. The maximum solubility was reached in dimethyl sulfoxide and the minimum in cyclohexane. As for the thermodynamic functions, the entropy drives the solution process in all cases. In relation to the solubility parameter, it can be analyzed that the mathematical models offer approximations; however, the experimental data are still primordial at the time of inferring any process.

Thermodynamic Assessment of Triclocarban Dissolution Process in N-Methyl-2-pyrrolidone + Water Cosolvent Mixtures

Solubility is one of the most important physicochemical properties due to its involvement in physiological (bioavailability), industrial (design) and environmental (biotoxicity) processes, and in this regard, cosolvency is one of the best strategies to increase the solubility of poorly soluble drugs in aqueous systems. Thus, the aim of this research is to thermodynamically evaluate the dissolution process of triclocarban (TCC) in cosolvent mixtures of {N-methyl-2-pyrrolidone (NMP) + water (W)} at seven temperatures (288.15, 293.15, 298.15, 303.15, 308.15, 313.15 and 318.15 K). Solubility is determined by UV/vis spectrophotometry using the flask-shaking method. The dissolution process of the TCC is endothermic and strongly dependent on the cosolvent composition, achieving the minimum solubility in pure water and the maximum solubility in NMP. The activity coefficient decreases from pure water to NMP, reaching values less than one, demonstrating the excellent positive cosolvent effect of NMP, which is corroborated by the negative values of the Gibbs energy of transfer. In general terms, the dissolution process is endothermic, and the increase in TCC solubility may be due to the affinity of TCC with NMP, in addition to the water de-structuring capacity of NMP generating a higher number of free water molecules.

Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media

The solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen and phenacetin solubility data in neat and binary solvent mixtures was used for the development of a nonlinear deep machine learning model using new intuitive molecular descriptors derived from COSMO-RS computations. The literature dataset was augmented with results of new measurements in aqueous binary mixtures of 4-formylmorpholine, DMSO and DMF. The solubility values back-computed with the developed ensemble of neural networks are in perfect agreement with the experimental data, which enables the extensive screening of many combinations of solvents not studied experimentally within the applicability domain of the trained model. The final predictions were presented not only in the form of the set of optimal hyperparameters but also in a more intuitive way by the set of parameters of the Jouyban-Acree equation often used in the co-solvency domain. This new and effective approach is easily extendible to other systems, enabling the fast and reliable selection of candidates for new solvents and directing the experimental solubility screening of active pharmaceutical ingredients.

New Screening Protocol for Effective Green Solvents Selection of Benzamide, Salicylamide and Ethenzamide

New protocol for screening efficient and environmentally friendly solvents was proposed and experimentally verified. The guidance for solvent selection comes from computed solubility via COSMO-RS approach. Furthermore, solute-solvent affinities computed using advanced quantum chemistry level were used as a rationale for observed solvents ranking. The screening protocol pointed out that 4-formylomorpholine (4FM) is an attractive solubilizer compared to commonly used aprotic solvents such as DMSO and DMF. This was tested experimentally by measuring the solubility of the title compounds in aqueous binary mixtures in the temperature range between 298.15 K and 313.15 K. Additional measurements were also performed for aqueous binary mixtures of DMSO and DMF. It has been found that the solubility of studied aromatic amides is very high and quite similar in all three aprotic solvents. For most aqueous binary mixtures, a significant decrease in solubility with a decrease in the organic fraction is observed, indicating that all systems can be regarded as efficient solvent-anti-solvent pairs. In the case of salicylamide dissolved in aqueous-4FM binary mixtures, a strong synergistic effect has been found leading to the highest solubility for 0.6 mole fraction of 4-FM.

Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility

Solubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived molecular descriptors, adequate for development of an ensemble of neural networks model (ENNM), for solubility computations of sulfamethizole (SMT) in neat and aqueous binary solvent mixtures. The machine learning procedure utilized information encoded in σ-potential profiles computed using the COSMO-RS approach. The resulting nonlinear model is accurate in backcomputing SMT solubility and allowed for extensive screening of green solvents. Since the experimental characteristics of SMT solubility are limited, the data pool was extended by new solubility measurements in water, five neat organic solvents (acetonitrile, N,N-dimethylformamide, dimethyl sulfoxide, 1,4-dioxane, and methanol), and their aqueous binary mixtures at 298.15, 303.15, 308.15, and 313.15 K. Experimentally determined order of decreasing SMT solubility in neat solvents is the following: N,N-dimethylformamide > dimethyl sulfoxide > methanol > acetonitrile > 1,4dioxane >> water, in all studied temperatures. Similar trends are observed for aqueous binary mixtures. Since N,N-dimethylformamide is not considered as a green solvent, the more acceptable replacers were searched for using the developed model. This step led to the conclusion that 4-formylmorpholine is a real alternative to N,N-dimethylformamide, fulfilling all requirements of both high dissolution potential and environmental friendliness.

Thermodynamic Characteristics of Phenacetin in Solid State and Saturated Solutions in Several Neat and Binary Solvents

The thermodynamic properties of phenacetin in solid state and in saturated conditions in neat and binary solvents were characterized based on differential scanning calorimetry and spectroscopic solubility measurements. The temperature-related heat capacity values measured for both the solid and melt states were provided and used for precise determination of the values for ideal solubility, fusion thermodynamic functions, and activity coefficients in the studied solutions. Factors affecting the accuracy of these values were discussed in terms of various models of specific heat capacity difference for phenacetin in crystal and super-cooled liquid states. It was concluded that different properties have varying sensitivity in relation to the accuracy of heat capacity values. The values of temperature-related excess solubility in aqueous binary mixtures were interpreted using the Jouyban–Acree solubility equation for aqueous binary mixtures of methanol, DMSO, DMF, 1,4-dioxane, and acetonitrile. All binary solvent systems studied exhibited strong positive non-ideal deviations from an algebraic rule of mixing. Additionally, an interesting co-solvency phenomenon was observed with phenacetin solubility in aqueous mixtures with acetonitrile or 1,4-dioxane. The remaining three solvents acted as strong co-solvents.

Faster dispersive liquid-liquid microextraction methods using magnetic ionic liquids as solvents

Three hydrophobic magnetic ionic liquids (MILs) containing the tetrachloromanganate(II) (MnCl4(2-)) anion, namely, aliquat tetrachloromanganate(II) ([Aliquat(+)]2[MnCl4(2-)]), methyltrioctylammonium [MnCl4(2-)] ([N1,8,8,8(+)]2[MnCl4(2-)]), and trihexyltetradecylphosphonium [MnCl4(2-)] ([P6,6,6,14(+)]2[MnCl4(2-)]) were employed as extraction solvents in DLLME coupled to high-performance liquid chromatography (HPLC) employing UV detection. The MILs were developed with the features of magnetic susceptibility to permit rapid retrieval of the extraction solvent, hydrophobicity to allow for phase separation from water, and mobile phase compatibility with reversed phase HPLC. Additionally, the MILs were customized to minimize hydrolysis of the anionic component in aqueous media as well as reduce absorbance when subjected to HPLC. The three MILs were applied for the extraction of pharmaceutical drugs, phenolics, insecticides, and polycyclic aromatic hydrocarbons. The disperser solvent type, disperser solvent volume, mass of MIL, extraction time, the pH of the sample solution, and salt concentration were studied in order to achieve optimal extraction efficiency for each MIL. The [P6,6,6,14(+)]2[MnCl4(2-)] MIL exhibited the best extraction efficiencies for most of the target analytes compared to the other MILs. Good linearity was obtained using this MIL with correlation coefficients (R) varying from 0.997 to 0.999. The limits of detection (LODs) of all analytes ranged from 0.25 to 1.00μgL(-1). The relative recovery was studied in lake water and river water. The relative recovery in lake water varied from 53.8% to 114.7% at a spiked concentration of 20μgL(-1) (5μgL(-1) for phenanthrene) and from 52.1% to 106.7% at 150μgL(-1) (37.5μgL(-1) for phenanthrene). In river water, the relative recovery varied from 44.6% to 110.7% at a spiked concentration of 20μgL(-1) (5μgL(-1) for phenanthrene) and 42.9% to 83.6% at 150μgL(-1) (37.5μgL(-1) for phenanthrene).

Crosslinked polymeric ionic liquids as solid-phase microextraction sorbent coatings for high performance liquid chromatography

Neat crosslinked polymeric ionic liquid (PIL) sorbent coatings for solid-phase microextraction (SPME) compatible with high-performance liquid chromatography (HPLC) are reported for the first time. Six structurally different PILs were crosslinked to nitinol supports and applied for the determination of select pharmaceutical drugs, phenolics, and insecticides. Sampling conditions including sample solution pH, extraction time, desorption solvent, desorption time, and desorption solvent volume were optimized using design of experiment (DOE). The developed PIL sorbent coatings were stable when performing extractions under acidic pH and remained intact in various organic desorption solvents (i.e., methanol, acetonitrile, acetone). The PIL-based sorbent coating polymerized from the IL monomer 1-vinyl-3-(10-hydroxydecyl) imidazolium chloride [VC10OHIM][Cl] and IL crosslinker 1,12-di(3-vinylbenzylimidazolium) dodecane dichloride [(VBIM)2C12] 2[Cl] exhibited superior extraction performance compared to the other studied PILs. The extraction efficiency of pharmaceutical drugs and phenolics increased when the film thickness of the PIL-based sorbent coating was increased while many insecticides were largely unaffected. Satisfactory analytical performance was obtained with limits of detection (LODs) ranging from 0.2 to 2 μg L(-1) for the target analytes. The accuracy of the analytical method was examined by studying the relative recovery of analytes in real water samples, including tap water and lake water, with recoveries varying from 50.2% to 115.9% and from 48.8% to 116.6%, respectively.

Solubility behavior and prediction for antihelmintics at several temperatures in aqueous and nonaqueous mixtures

A model based on solubility parameters is proposed to predict the solubility curves of antihelmintic drugs at several temperatures, including aqueous and non-aqueous mixtures. The solubility of the drugs was measured in ethanol-water and ethanol-ethyl acetate mixtures at 15-35 degrees C (mebendazole) and at 25 degrees C (thiabendazole and metronidazole). The solid phases were analyzed by differential scanning calorimerty. The polymorphic form A of mebendazole was also characterized from infrared spectroscopy. Markedly different solubility profile shapes were obtained against the solubility parameter of the mixtures: two symmetrical peaks (metronidazole), two maxima of different height (mebendazole) and a single peak (thiabendazole). The solubility parameter of the drugs was related to the co-solvent action of both mixtures and to the solubility peaks. The single equation proposed was able to predict solubility profiles of different shape, including both mixtures and all temperatures, providing reasonable physical meaning for the regression coefficients. The model was successfully tested for its predictive capability using a limited number of experimental data. More than 100 solubilities were predicted at several temperatures using 20 data point for each drug.

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.

A unified cosolvency model for calculating solute solubility in mixed solvents

Organic solvents are amongst the most powerful solubilization agents for a large number of water-insoluble drugs. A number of equations has been reported for mathematical representation of solute solubility in mixed solvents. The question is then posed--is there a mathematical difference between these models? To address this point, it has been demonstrated that all cosolvency models could be made equivalent by using algebraic manipulations. In order to familiarize the readers with the available cosolvency models, they are briefly reviewed. The models can be divided into two mathematical categories, i.e. linear and non-linear models. The linear models include: the log-linear, extended Hildebrand solubility approach, excess free energy equations, combined nearly ideal binary solvent/Redlich-Kister equation and Margule equations which can be converted to a general single model which expresses the logarithm of mole fraction solubility of a solute as a power series of volume fraction of the cosolvent. The non-linear models include the mixture response surface methods, two step solvation model and modified Wilson model which can be converted to a non-linear general form. Also, it has been shown that both the general single model and a non-linear general model are mathematically identical. To show the applicability of the models on real experimental data, 35 data sets have been collected from the literature. Both linear and nonlinear models produced comparable accuracies when an equal number of constant terms was employed in numerical analyses.

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.

Thermodynamic origin of the solubility profile of drugs showing one or two maxima against the polarity of aqueous and nonaqueous mixtures: niflumic acid and caffeine

The purpose of this work was to investigate the origin of the different solubility profiles of drugs against the polarity of solvent mixtures with a common cosolvent. Niflumic acid and caffeine where chosen as model drugs. The solubilities were measured at five or six temperatures in aqueous (ethanol-water) and nonaqueous (ethyl acetate-ethanol) mixtures. The enthalpies of solution were obtained at the harmonic mean of the experimental temperature. Solid phase changes were analyzed using differential scanning calorimetry and thermomicroscopy. A single solubility maximum was obtained for niflumic acid against the solubility parameter of both mixtures that is not related to solid phase changes. In contrast, caffeine displays two maxima and anhydrous-hydrate transition occurs at the solubility peak in the amphiprotic mixture. The apparent enthalpies of solution of both drugs show endothermic maxima against solvent composition that are related to hydrophobic hydration. A general explanation for the cosolvent action in aqueous mixtures is proposed. The dominant mechanism shifts from entropy to enthalpy at a certain cosolvent ratio dependent on the hydrophobicity and the solubility parameter of the drug. Niflumic acid and caffeine show enthalpy-entropy compensation in ethanol-water, and this relationship is demonstrated for the first time in nonaqueous mixtures. The results support that enthalpy-entropy compensation is a general effect for the solubility of drugs in solvent mixtures. The shape of the solubility curves is correlated with the compensation plots. The solubility peaks separate different enthalpy-entropy relationships that also differentiate the solubility behavior of the hydrate and the anhydrous forms of caffeine.

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.

The hydrophobic effect. 2. Relative importance of the hydrophobic effect on the solubility of hydrophobes and pharmaceuticals in H-bonded solvents

The quantitative development of the nonergodic mobile order thermodynamics involving the new interpretation of the hydrophobic effect leads to a general solubility equation. This equation is applied to predict the aqueous and alcohol solubility of chemicals ranging from nonpolar or slightly polar with no H-bonding capacity to polyfunctional polar compounds including pharmaceuticals. The analysis of the relative importance of the contributions involved in the solubility model [i.e., the fluidization of the solute (for solids), the correction for the mixing entropy, the change of the nonspecific cohesion forces, and the formation of solvent-solvent (hydrophobic effect), solute-solute, and solute-solvent H-bonds] unambiguously demonstrates that the hydrophobic effect is essential for predicting the aqueous or alcohol solubility of any substance in general, and of nonpolar compounds in particular. The difference between the origin of the solubility of hydrocarbons in water and of water in hydrocarbons is furthermore presented. In both cases, the quasilinear solubility dependence on the molar volume of the hydrocarbon is of an entropic nature.