Nonrandom Two-liquid Segment Activity Coefficient Research Articles

Celecoxib solubility in two choline chloride-based deep eutectic solvents- Experimental study, thermodynamic modeling, and molecular dynamic simulation

In the present study, we investigated the solubility of celecoxib the in the aqueous solution of two deep eutectic solvents (DESs) at various DES weight fractions within the temperature range of 283.2-323.2 K. Choline chloride (ChCl) as hydrogen bond acceptor (HBA) and ethylene glycol (EG) and 1,2-propanediol (PD) as hydrogen bond donors (HBDs) were used for the preparation of DESs. Experimental results showed that the solubility of celecoxib is significantly enhanced by approximately one million times in DES-contained PD compared to pure water. Also, celecoxib's solubility was enhanced by increasing temperature and the weight fraction of DESs. Besides, DES2 (ChCl + PD) showed a higher solubility for celecoxib compared to DES1 (ChCl + EG) in all experiments. Moreover, two temperature-dependent Buchowski-Ksiazaczak λh and modified Apelblat equations and the local composition models such as Wilson, non-random two-liquid theory (NRTL), and universal quasi-chemical (UNIQUAC) were applied to correlate the experimental solubility data. The correlated solubility was in good agreement with the experimental data. In addition, two-segment-based models, including non-random two-liquid-segment activity coefficient (NRTL-SAC) and universal quasi-chemical segment activity coefficient (UNIQUAC-SAC) models provided relatively good performance in solubility prediction. Furthermore, the calculation of the apparent standard thermodynamic properties showed that enthalpy is the primary contribution term to the apparent standard Gibbs free energy in the dissolution process of celecoxib. Finally, we applied molecular dynamics simulations to describe the drug solubility from the molecular point of view. The radial distribution function (RDF) analysis revealed that the experimental solubility is consistent with the MD simulation results, so the attractive interactions between celecoxib-DES1 and celecoxib-DES2 are much higher than the water-celecoxib.

Comparison of two computational methods for solvent screening in countercurrent and centrifugal partition chromatography

Countercurrent and centrifugal partition chromatography are techniques applied in the separation and isolation of compounds from natural extracts. One of the key design parameters of these processes is the selection of the biphasic solvent system that provides for the adequate partitioning of the solutes. To address this challenging task, the fully predictive Conductor-like Screening Model for Real Solvents (COSMO-RS) and the semi-predictive Non-Random Two-Liquid Segment Activity Coefficient (NRTL-SAC) model were applied to estimate the partition coefficients (K) of four model phenolic compounds (vanillin, ferulic acid, (S)-hesperetin and quercetin) in different solvent systems. Complementing the experimental data collected in the literature, partition coefficients of each solute in binary, or quaternary, solvent systems were measured at 298.2 K.Higher deviations from the experimental data were obtained using the predictive COSMO-RS model, with an average RMSD (root-mean-square deviation) in log(K) of 1.17 of all four solutes (61 data points), providing a satisfactory quantitative description only for the systems containing vanillin (RSMD = 0.57). For the NRTL-SAC model, the molecular parameters of the solutes were initially calculated by correlating a set of K and solubility (x, in mole fraction) data (16 partition coefficients and 44 solubility data points), for which average RMSD values of 0.07 and 0.41 were obtained in log(K) and log(x), respectively. The predictions of the remaining log(K) data (45 partition coefficients) resulted in an average RMSD of 0.43, suggesting that the NRTL-SAC model was a more reliable quantitative solvent screening tool. Depending on the amount of available solubility and partition data, both models can be valuable alternatives in the preliminary stages of solvent screening destined to select the optimal mobile and stationary phases for a given separation.

An ion-specific electrolyte non-random two-liquid segment activity coefficient model with improved predictive capabilities for aqueous electrolyte solutions

The accurate prediction of activity coefficients of electrolyte solutions is of great importance for many engineering applications. The electrolyte non-random two-liquid (eNRTL) model is a commonly used semi-empirical activity coefficient model for electrolyte solutions. This work presents a modified version of the eNRTL model, which aims to extend its predictive capabilities. An ion-specific parameterization scheme is developed to replace the conventionally used salt-specific parameterization scheme. Consequently, this new method allows for the prediction of the properties of electrolytes consisting of ions for which optimal ion-specific parameter values have been determined, which is inherently not possible when using salt-specific parameters. In order to capture the features of solvent-ion interactions, a segment-based local composition term is used and experimental activity data of both the salt and the solvent are utilized for parameter fitting. The modified eNRTL model with optimal ion-specific parameters is applied to aqueous electrolyte solutions and shows satisfying prediction performance.

Thermodynamic modelling and Hansen solubility parameter of N-hydroxy-5-norbornene-2,3-dicarboximide in twelve pure solvents at various temperatures

Solubility of N-hydroxy-5-norbornene-2,3-dicarboximide (HONB) in methanol, ethanol, n-propanol, isopropanol, 2-methoxyethanol, 2-propoxyethanol, 2-ethoxyethanol, 2-butoxyethanol, acetonitrile, ethyl acetate, acetone at (278.15–323.15) K and 1,4-dioxane at (288.15–323.15) K was determined with a laser monitoring method at pressure of 0.1 MPa. The experimental results indicated that solubility of HONB increased positively with the increase of temperature in selected neat solvents. At 298.15 K, solubility data in studied solvents followed the sequence of 2-methoxyethanol (0.1412) > methanol (0.1108) > 2-ethoxyethanol (0.1007) > 1,4-dioxane (0.0963) > 2-propoxyethanol (0.0718) > 2-butoxyethanol (0.0601) > ethanol (0.0592) > acetone (0.0520) > isopropanol (0.0402) > n-propanol (0.0401) > acetonitrile (0.0298) > ethyl acetate (0.0156). The solubility behaviors of HONB in investigated solvents were analyzed by Hansen solubility parameter (Δδd, Δδp, Δδh, Δδt and Δδ), the consequences showed that solubility order of HONB resulted from the comprehensive function of several solubility parameters. Experimental solubility values were correlated with five thermodynamic models including Nonrandom Two-Liquids (NRTL), Two-Suffix Margules, Universal Quasi-chemical (UNIQUAC), Nonrandom Two-Liquid Segment Activity Coefficient (NRTL-SAC) and Wilson model. Results showed that the smallest average values of average relative deviation (ARD) and root-mean square deviation (104RMSD) were obtained by Wilson model with values of 1.06% and 8.73. Moreover, mixing properties (mixing enthalpy ΔmixH, entropy ΔmixS, Gibbs energy ΔmixG) were evaluated based on measured solubility and equation parameters of Wilson model. The positive values of ΔmixS and negative values of ΔmixG revealed that mixing process of HONB in considered solvents was entropy-driven and spontaneous.

Nonrandom Two-Liquid Segment Activity Coefficient Model with Association Theory

Association theory has been extensively applied to equations of state such as statistical associating fluid theory and cubic plus association. This work presents an integration of association theory with the nonrandom two-liquid segment activity coefficient (NRTL-SAC) model. Replacing the four conceptual segments (hydrophobic, hydrophilic, polar attractive, and polar repulsive) in the original NRTL-SAC model, the association NRTL-SAC model represents interacting molecules with two conceptual segments (nonpolar and polar) and two association site types (hydrogen bond acceptor and donor). Given the molecule-specific parameters, the model shows much improved predictive capability than the original NRTL-SAC model for phase equilibria of chemical mixtures in which associations take place.

Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model

An improved framework has been developed for solubility prediction of different forms of a medium-sized antibiotic (i.e., nonelectrolyte, electrolyte, and solvate) in single and mixed solvents using a symmetrically reformulated electrolyte nonrandom two-liquid segment activity coefficient (eNRTL-SAC) model. The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. Moreover, a design of experiments is included in the methodology to generate and use experimental data appropriately for model parameter regression and model validation. Because of the semipredictive nature of the symmetric eNRTL-SAC model, the segment parameter regression is a critical step for solubility prediction accuracy. A particle swarm optimization algorithm is incorporated to preregress conceptual segment parameters of solutes. The preregressed segment parameters were used as initial guesses for further s...

Computation-aided separation of seven components from Spirodela polyrrhiza (L.) via counter-current chromatography

Abstract In this study, seven flavonoids were successfully separated from Spirodela polyrrhiza (L.) Schleid. via high-speed counter-current chromatography (HSCCC) with elution–extrusion and online recycling elution modes. The first step for successful HSCCC separation is the crucial solvent system selection. In this work, nonrandom two-liquid segment activity coefficient (NRTL-SAC) method, a computational strategy, was used to facilitate the solvent system selection process. According to the NRTL-SAC method, a suitable solvent system can be rapidly predicted and screened by calculating the partition coefficient rather than by performing tedious experimental measurements. Based on the method, two solvent systems of hexane/ethyl acetate/ethanol/water (1:3:1:3 and 1:9:1:9, v/v) were predicted as the most suitable systems for HSCCC separation. To avoid unnecessary waste of the stationary or mobile phase, both the mobile and stationary phases were prepared independently based on the calculated phase compositions by thermodynamic method. Consequently, seven compounds were successfully separated with high purity (>90%). The separated compounds were identified through UV spectra and high-resolution tandem mass spectroscopy. These compounds include orientin ( 1 ), vitexin ( 2 ), luteolin 7-O-glucoside ( 3 ), apigenin 7-O-glucoside ( 4 ), luteolin 8-C-(2′′-O-feruloyl-) glucoside ( 5 ), apigenin 8-C-(-2′′-O-feruloyl-) glucoside ( 6 ), and luteolin ( 7 ). This work demonstrates that HSCCC is suitable for separation of natural products, and computational strategy is very helpful for enhancing the efficiency of CCC experiments.

Separation of phenolic acids and flavonoids from Trollius chinensis Bunge by high speed counter-current chromatography.

In this work, eleven compounds were successfully separated from Trollius chinensis Bunge by using a two-step high-speed counter-current chromatography (HSCCC) method. NRTL-SAC (nonrandom two-liquid segment activity coefficient) method, a newly developed solvent system selection strategy, was applied to screening the suitable biphasic liquid systems. Hexane/ethyl acetate/ethanol/water (3:7:3:7, v/v) solvent system was used in the first step, while the hexane/ethyl acetate/methanol/water (1:2:1:2, 1:4:1:4, 1:9:1:9, v/v) systems were employed in the second step. The chemical structures of the separated compounds were identified by UV, high resolution ESI-MS and MS/MS data. The separated compounds are 3,4-dihydroxyphenylethanol (1), vanillic acid (2), orientin (3), vitexin (4), veratric acid (5), 2″-O-(3‴, 4‴-dimethoxybenzoyl) orientin (6), 2″-O-feruloylorientin (7), 2″-O-feruloylvitexin (8), 2″-O-(2‴-methylbutyryl) vitexin (9), 2″-O-(2‴-methylbutyryl) isoswertiajaponin (10), 2″-O-(2‴-methylbutyryl) isoswertisin (11). The results demonstrate that HSCCC is a powerful tool for the separation of compounds from extremely complex samples.

Systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient model for real-life counter-current chromatography separation

Solvent system selection is the first step toward a successful counter-current chromatography (CCC) separation. This paper introduces a systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient (NRTL-SAC) model, which is efficient in predicting the solute partition coefficient. Firstly, the application of the NRTL-SAC method was extended to the ethyl acetate/n-butanol/water and chloroform/methanol/water solvent system families. Moreover, the versatility and predictive capability of the NRTL-SAC method were investigated. The results indicate that the solute molecular parameters identified from hexane/ethyl acetate/methanol/water solvent system family are capable of predicting a large number of partition coefficients in several other different solvent system families. The NRTL-SAC strategy was further validated by successfully separating five components from Salvia plebeian R.Br. We therefore propose that NRTL-SAC is a promising high throughput method for rapid solvent system selection and highly adaptable to screen suitable solvent system for real-life CCC separation.

Correlation and prediction of partition coefficient using nonrandom two-liquid segment activity coefficient model for solvent system selection in counter-current chromatography separation

Selection of a suitable solvent system is the first and foremost step for a successful counter-current chromatography (CCC) separation. In this paper, a thermodynamic model, nonrandom two-liquid segment activity coefficient model (NRTL-SAC) which uses four types of conceptual segments to describe the effective surface interactions for each solvent and solute molecule, was employed to correlate and predict the partition coefficients (K) of a given compound in a specific solvent system. Then a suitable solvent system was selected according to the predicted partition coefficients. Three solvent system families, heptane/methanol/water, heptane/ethyl acetate/methanol/water (Arizona) and hexane/ethyl acetate/methanol/water, and several solutes were selected to investigate the effectiveness of the NRTL-SAC model for predicting the partition coefficients. Comparison between experimental results and predicted results showed that the NRTL-SAC model is of potential for estimating the K value of a given compound. Also a practical separation case on magnolol and honokiol suggests the NRTL-SAC model is effective, reliable and practical for the purpose of predicting partition coefficients and selecting a suitable solvent system for CCC separation.

Solubility of Flavonoids in Pure Solvents

The fast and efficient selection of food-approved solvents is required for a growing number of flavonoids that are continuously being tested for their nutraceutical properties. Solid–liquid equilibrium is an essential source of information for the design of extraction, precipitation, or crystallization processes in the food industry. In this context, the nonrandom two-liquid segment activity coefficient thermodynamic model showed to be an appropriate tool to represent the solubility of several key flavonoids (apigenin, genistein, hesperetin, luteolin) in pure solvents, suggesting its ability to predict solubility in solvents not considered during the correlation procedure. For substances with unknown melting properties the reference solvent approach was successfully applied. Additionally, new solubility data of S-hesperetin in the pure solvents acetone, ethanol, ethyl acetate, methanol, and acetonitrile was measured, between 25 and 40 °C, by the shake-flask method.

Symmetric Nonrandom Two-Liquid Segment Activity Coefficient Model for Electrolytes

The nonrandom two-liquid segment activity coefficient model (NRTL-SAC) [Chen, C.-C.; Song, Y. Solubility Modeling with a Nonrandom Two-Liquid Segment Activity Coefficient Model. Ind. Eng. Chem. Res. 2004, 43, 8354−8362] has been shown to be a simple and practical thermodynamic model for correlating and predicting phase behavior for complex pharmaceutical molecules. The model was later extended for electrolytes [Chen, C.-C.; Song, Y. Extension of Non-Random Two-Liquid Segment Activity Coefficient Model for Electrolytes. Ind. Eng. Chem. Res. 2005, 44, 8909−8921]. However, the electrolyte model was presented as an unsymmetric activity coefficient model with aqueous phase infinite dilution reference state. Such an unsymmetric model becomes rather cumbersome to use when dealing with nonaqueous solvents. In this work, we present a symmetric electrolyte NRTL-SAC model which simplifies the long-range interaction term. We further examine the utility of the model in predicting salt solubilities in nonaqueous solven...

Temperature and solvent effects in the solubility of some pharmaceutical compounds: Measurements and modeling

In this work, pure solvent solubilities of drugs, such as paracetamol, allopurinol, furosemide and budesonide, measured in the temperature range between 298.2–315.2 K are presented. The solvents under study were water, ethanol, acetone, ethyl acetate, carbon tetrachloride and n-hexane. Measurements were performed using the shake-flask method for generating the saturated solutions followed by compositional analysis by HPLC. Previous literature values on the solubilities of paracetamol were used to assess the experimental methodology employed in this work. No literature data was found for any of the other drugs studied in this assay. Melting properties of the pure drugs were also determined by differential scanning calorimetry (DSC) to provide a broader knowledge about the solubilization process and also for modeling purposes. The solubility data as a function of temperature were used to determine the thermodynamic properties of dissolution like, Gibbs energy, enthalpy and entropy. Theoretical work was essentially focused on the evaluation of the Nonrandom Two-Liquid Segment Activity Coefficient (NRTL-SAC) model, which has been referred as a simple and practical thermodynamic framework for drug solubility estimation. A satisfactory agreement was found between experimental and calculated values: the absolute average deviation was 68% for the correlation in the organic solvents and 38% for the prediction in water, where the best results in prediction could be related to the selected solvents.

Correlation and Prediction of Phase Behavior of Organic Compounds in Ionic Liquids Using the Nonrandom Two-Liquid Segment Activity Coefficient Model

Room-temperature ionic liquids have shown great potential as media for reactions and separations. Information on how organic compounds interact with these ionic liquids is crucial in assessing their usefulness. Here, the nonrandom two-liquid segment activity coefficient (NRTL-SAC) model is used first to correlate values of infinite-dilution activity coefficients for organic compounds in ionic liquids and then to predict the phase behavior of various mixtures involving these ionic liquids. NRTL-SAC provides a robust, qualitative predictive model based on four molecular descriptors that are designed to capture molecular surface interaction characteristics: hydrophobicity, hydrophilicity, polarity, and solvation strength.

Modeling Drug Molecule Solubility to Identify Optimal Solvent Systems for Crystallization

The utility of the recently developed nonrandom two-liquid segment activity coefficient (NRTL-SAC) model has been reported for solvent selection in support of industrial crystallization process design. In this paper, we present a recent successful application with NRTL-SAC to screen solvents for a crystallization medium with the goal to maximize API solubility and to minimize solvent usage. The NRTL-SAC model parameters for the molecule in development are first identified from a minimal set of solubility experiments in selected solvents. We then perform numerous in silico virtual experiments to explore the solubility behavior of the molecule in other pure solvents and mixed solvents. The modeling results suggested optimal solvent systems for the crystallization medium which are validated in physical laboratories and chosen for process scale-up. This study demonstrated the effectiveness of the NRTL-SAC model and supports its use as a tool in drug development.

Sigma Profile Database for Predicting Solid Solubility in Pure and Mixed Solvent Mixtures for Organic Pharmacological Compounds with COSMO-Based Thermodynamic Methods

Thermodynamic methods based on COSMO (COnductor-like Screening MOdels), such as COSMO-RS (Real Solvent) and COSMO-SAC (Segment Activity Coefficient), represent significant and recent developments of solvation thermodynamics and computational quantum mechanics. These are a priori prediction methods based on molecular structures and a few parameters that are fixed for all of the compounds. They require no experimental data and rely on sigma profiles specific to each molecule as their only input. A sigma profile is the probability distribution of a molecular surface segment having a specific charge density. Generating sigma profiles by quantum mechanical calculations represents the most time-consuming and computationally expensive aspect of using COSMO-based methods. This article presents a free, web-based VT-2006 Solute Sigma Profile Database for large, pharmaceutical-related solutes, to supplement the published VT-2005 Sigma Profile Database for solvents and small molecules (www.design.che.vt.edu). Together, these databases contain sigma profiles for 1645 unique compounds, enabling the users to predict binary and multicomponent vapor−liquid equilibrium (VLE) and solid−liquid equilibrium (SLE), as well as other thermodynamic properties. We validate the VT-2006 Solute Sigma Profile Database by solid solubility predictions in pure solvents for 2434 literature solubility values, which include 194 solutes, 160 solvents, and 1356 solute−solvent pairs. We also compare solubility predictions for mixed solvents to literature values for 39 systems. By comparison with experimental data, we find a root-mean-squared error (RMSE) of 0.7419 between experimental and predicted solute mole fractions (xsol) on a log10 (xsol) scale for solubilities in pure solvents. This article also presents examples investigating the effects of conformational isomerism on solubility predictions of small, medium-sized, and large drug molecules. To provide better understanding of accuracy, we compare a priori COSMO-SAC solubility predictions, which use molecule-specific sigma profiles, to those by the non-random two-liquid segment activity coefficient (NRTL-SAC) model, which uses regressed molecule-specific parameters, for 17 solutes and 258 experimental solubility values. We find that NRTL-SAC, which contains regressed parameters based on experimental data, is a more accurate method for predicting SLE behavior than the COSMO-SAC model for many of the systems studied. Finally, this article presents a set of guidelines for applying the COSMO-SAC model for solubility predictions for new drug molecules when no experimental data are available.

Correlation and Prediction of Drug Molecule Solubility in Mixed Solvent Systems with the Nonrandom Two-Liquid Segment Activity Coefficient (NRTL−SAC) Model

The recently developed Nonrandom Two-Liquid Segment Activity Coefficient (NRTL−SAC) model [reported by Chen and Song, Ind. Eng. Chem. Res. 2004, 43, 8354] offers a practical thermodynamic framework to predict drug solubility in a wide range of solvents, based on a small initial set of measured solubility data. The model yields satisfactory results in first correlating drug solubility in a few representative pure solvents and then qualitatively predicting drug solubility in other pure solvents. Here, we investigate the applicability of the NRTL−SAC model for predicting drug solubility in mixed solvents for three molecules: acetaminophen, sulfadiazine, and cimetidine. The study shows that the model provides robust correlation and prediction of drug solubility in both pure and mixed solvents, with a qualitative level of accuracy. The model is a useful tool in support of the early stages of crystallization process development and other areas of drug process design.

Extension of Nonrandom Two-Liquid Segment Activity Coefficient Model for Electrolytes

The nonrandom two-liquid segment activity coefficient model of Chen and Song (Ind. Eng. Chem. Res. 2004, 43, 8354) has shown to be a simple and practical tool for chemists and engineers to correlate and estimate solubilities of organic nonelectrolytes in support of chemical and pharmaceutical process design. In this paper, the model is extended for the computation of ionic activity coefficients and solubilities of electrolytes, organic and inorganic, in common solvents and solvent mixtures. In addition to the three types of molecular parameters defined for organic nonelectrolytes, i.e., hydrophobicity X, polarity Y, and hydrophilicity Z, an electrolyte parameter, E, is introduced to characterize both local and long-range ion−ion and ion−molecule interactions attributed to ionized segments of electrolytes. Successful representations of mean ionic activity coefficients and solubilities of electrolytes, inorganic and organic, in aqueous and nonaqueous solvents are presented.

Solubility Modeling with a Nonrandom Two-Liquid Segment Activity Coefficient Model

A segment contribution activity coefficient model, derived from the polymer nonrandom two-liquid model, is proposed for fast, qualitative estimation of the solubilities of organic nonelectrolytes in common solvents. Conceptually, the approach suggests that one account for the liquid nonideality of mixtures of complex pharmaceutical molecules and small solvent molecules in terms of interactions between three pairwise interacting conceptual segments: hydrophobic segment, hydrophilic segment, and polar segment. In practice, these conceptual segments become the molecular descriptors used to represent the molecular surface characteristics of each solute and solvent molecule. The treatment results in component-specific molecular parameters: hydrophobicity X, polarity Y, and hydrophilicity Z. Once the molecular parameters are identified from experimental data for common solvents and solute molecules, the model offers a simple and practical thermodynamic framework to estimate solubilities and to perform other phase equilibrium calculations in support of pharmaceutical process design.