Solubility measurement, model evaluation and Hansen solubility parameter of ipriflavone in three binary solvents

Huang, Zibo; Sha, Jiao; Chang, Yingge; Cao, Zidan; Hu, Xiaoran; Liu, Yu; Li, Tao; Ren, Baozeng

doi:10.1016/j.jct.2020.106285

Cited by 6 publications

(10 citation statements)

References 34 publications

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“…Hildebrand comprehensively treated this concept and defined the term solubility parameter to express the cohesive force between molecules . Hansen improved this concept and divided the summation energy into three parts (contribution of dispersion forces, contribution of polar forces, and contribution of hydrogen forces) using the group contribution method. , From Tables and , we can see that except for isopropanol, DCM, acetonitrile, and acetone, the solubility of AAKG positively correlated with the Hansen solubility parameters in the selected solvents.…”

Section: Resultsmentioning

confidence: 99%

Solubility Behavior of l-Arginine α-Ketoglutarate in Ten Pure and Two Binary Water + Ethanol and Water + Acetone Solvent Systems

Qiu

Guo

et al. 2021

J. Chem. Eng. Data

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The solubility data of L-arginine α-ketoglutarate (AAKG) were determined by the static gravimetric method from 283.15 to 323.15 K in 10 pure solvents (water, methanol, ethanol, isopropanol, acetone, acetonitrile, dichloromethane, ethyl acetate, 2-butanone, and 1,4-dioxane) and two water + ethanol and water + acetone binary solvent systems. According to the experimental results, their solubility positively correlated with the temperature. In the selected solvent systems, there was no polymorph found. In addition, the data analysis results showed that the polarity, hydrogen bond, Hildebrand solubility parameters, and molecular structure all affected the dissolution behavior. Four thermodynamic models including the modified Apelblat model, the λh model, the NRTL model, and the Apelblat−Jouyban−Acree model were used to correlate the solubility data.

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Section: Resultsmentioning

confidence: 99%

Solubility Behavior of l-Arginine α-Ketoglutarate in Ten Pure and Two Binary Water + Ethanol and Water + Acetone Solvent Systems

Qiu

Guo

et al. 2021

J. Chem. Eng. Data

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“…The λ h model was proposed to describe the solubility behavior of solute in solution. It can be calculated as follows where λ and h are two equation parameters and T m is the melting temperature of the solute. The x 1 is the mole fraction solubility of solute, and T is the test temperature.…”

Section: Thermodynamic Modelsmentioning

confidence: 99%

Determination and Correlation of Solubility of Metformin Hydrochloride in Aqueous Binary Solvents from 283.15 to 323.15 K

Sun

Wang

et al. 2022

ACS Omega

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Metformin hydrochloride (MET•HCl) is one of the most widely used oral hypoglycemic drugs in the world. In addition to hypoglycemic effects, MET•HCl also has anti-inflammatory, anti-tumor, anti-aging, and other effects, showing good efficacy and safety of single and combined treatment. The solubility of MET•HCl in water, water + N,N-dimethylformamide, water + acetonitrile, and water + n-propanol was measured by the gravimetric method under atmospheric pressure at temperatures ranging from 283.15 to 323.15 K. The solubility of MET•HCl has a positive correlation with temperature and water content. The experimental solubility data in binary solvents was correlated by the modified Apelblat model, CNIBS/R-K model, Apelblat− Jouyban−Acree model, and λh model. By comparing the average ARD % values of the four models, it is found that the modified Apelblat model (ARD % = 1.26) provides better correlation. Hansen solubility parameters and apparent thermodynamic parameters were calculated to analyze the solubility behavior, indicating that the dissolution process is endothermic and entropically favorable.

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“…To obtain the solubility of drugs in different solvents and at different temperatures more conveniently, the empirical models such as the Apelblat model and the λh model have been widely used in pharmaceutical research, but they have limited applicability in the absence of the empirical parameters regressed from a large number of necessary experimental data. 7 Solid−liquid equilibrium theory is another effective method to calculate the solubility as shown in eq 1, where the activity coefficient can be estimated by the activity coefficient model, such as the Wilson equation, 8 UNIFAC equation, 9 and UNIQUAC equation. 10 Recently, perturbed-chain statistical associating fluid theory (PC-SAFT) has also been successfully applied to describe the solid−liquid equilibrium of drug-related systems and calculate the thermodynamic properties of the systems accurately.…”

Section: Introductionmentioning

confidence: 99%

“…10 Recently, perturbed-chain statistical associating fluid theory (PC-SAFT) has also been successfully applied to describe the solid−liquid equilibrium of drug-related systems and calculate the thermodynamic properties of the systems accurately. 11−15 Furthermore, the Hansen solubility parameter, 7,16 molecular dynamics simulations, 17,18 COSMO-SAC, 19 and other methods are also proposed to achieve solubility prediction. Although many theoretical advances have been made, it is still difficult to achieve an accurate and…”

Section: Introductionmentioning

confidence: 99%

“…Solid–liquid equilibrium theory is another effective method to calculate the solubility as shown in eq , where the activity coefficient can be estimated by the activity coefficient model, such as the Wilson equation, UNIFAC equation, and UNIQUAC equation . Recently, perturbed-chain statistical associating fluid theory (PC-SAFT) has also been successfully applied to describe the solid–liquid equilibrium of drug-related systems and calculate the thermodynamic properties of the systems accurately. − Furthermore, the Hansen solubility parameter, , molecular dynamics simulations, , COSMO-SAC, and other methods are also proposed to achieve solubility prediction. Although many theoretical advances have been made, it is still difficult to achieve an accurate and quantitative prediction of drug solubility as a function of temperature in the full absence of experimental data …”

Section: Introductionmentioning

confidence: 99%

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Novel Computational Approach by Combining Machine Learning with Molecular Thermodynamics for Predicting Drug Solubility in Solvents

2021

Ind. Eng. Chem. Res.

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In this work, a novel strategy that combined molecular thermodynamic and machine learning was proposed to accurately predict the solubility of drugs in various solvents. The strategy was based on 16 molecular descriptors representing drug–drug interactions and drug–solvent interactions including physical parameters, pure perturbed-chain statistical associating fluid theory (PC-SAFT) parameters of drugs and solvents, and mixing rules. These molecular descriptors were inputted into five machine learning algorithms [multiple linear regression (MLR), artificial neural network (ANN), random forest (RF), extremely randomized trees (ET), and support vector machine (SVM)] to train the predictive model. A single-hidden-layer neural network was finally determined as the predictive model for predicting the solubility of drugs in various solvents. The drug solubility in the generalization evaluation set has also been successfully predicted, which indicates the good prediction performance of the model. Three directions for improving the model were summarized as adding molecular descriptors of drug–solvent interactions in the water system and drug–drug interactions in the organic solvent system and expanding the dataset to adequately obtain the features of multiple drugs. These findings show that the proposed model has the capability of solubility prediction, which is expected to provide important information for drug development and drug solvent screening.

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Solubility measurement, model evaluation and Hansen solubility parameter of ipriflavone in three binary solvents

Cited by 6 publications

References 34 publications

Solubility Behavior of l-Arginine α-Ketoglutarate in Ten Pure and Two Binary Water + Ethanol and Water + Acetone Solvent Systems

Solubility Behavior of l-Arginine α-Ketoglutarate in Ten Pure and Two Binary Water + Ethanol and Water + Acetone Solvent Systems

Determination and Correlation of Solubility of Metformin Hydrochloride in Aqueous Binary Solvents from 283.15 to 323.15 K

Novel Computational Approach by Combining Machine Learning with Molecular Thermodynamics for Predicting Drug Solubility in Solvents

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