Thermodynamic Analysis of the Solubility of Isoniazid in (PEG 200 + Water) Cosolvent Mixtures from 278.15 K to 318.15 K

Baracaldo-Santamaría, Daniela; Calderón-Ospina, Carlos-Alberto; Ortíz, Claudia Patricia; Cardenas-Torres, Rossember Edén; Martínez, Fleming; Delgado, Daniel Ricardo

doi:10.3390/ijms231710190

Cited by 7 publications

(3 citation statements)

References 53 publications

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“…The energetics of a compounds in water can be estimated through a statistical thermodynamical-like approach [ 38 , 39 ]. Gibbs energy, enthalpy or entropy as thermodynamic analysis of solubility with the purpose of contributing to the understanding of the possible molecular interactions can be used for interpretation of data [ 16 ]. Calculated Gibbs energy, as a thermodynamic paradigm, was adopted in this study to indicate a better mastery of the chemistry involved and improve the clarity of the discussion.…”

Section: Resultsmentioning

confidence: 99%

“…The fingerprint model used in this study is similar to the group contribution methods addressed above, with the advantage that it does not obtain the chemical building blocks in advance. Additionally, the fingerprint model is derived from physicochemical insights [ 16 ], which allows for easier interpretation of the model, and is useful in the context of developing efficient Quantitative Structure–Property Relationships (QSPRs) for the solubility [ 17 ]. The significance of this study lies in the practical utility of the developed fingerprint model, which can aid experts in investigating the impact of different functional groups on solubility predictions, which can have important implications for drug discovery and other related applications.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models

Tayyebi,

Alshami,

Rabiei

et al. 2023

J Cheminform

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A reliable and practical determination of a chemical species’ solubility in water continues to be examined using empirical observations and exhaustive experimental studies alone. Predictions of chemical solubility in water using data-driven algorithms can allow us to create a rationally designed, efficient, and cost-effective tool for next-generation materials and chemical formulations. We present results from two machine learning (ML) modeling studies to adequately predict various species’ solubility using data for over 8400 compounds. Molecular-descriptors, the most used method in previous studies, and Morgan fingerprint, a circular-based hash of the molecules' structures, were applied to produce water solubility estimates. We trained all models on 80% of the total datasets using the Random Forest (RFs) technique as the regressor and tested the prediction performance using the remaining 20%, resulting in coefficient of determination (R2) test values of 0.88 and 0.81 and root-mean-square deviation (RMSE) test values 0.64 and 0.80 for the descriptors and circular fingerprint methods, respectively. We interpreted the produced ML models and reported the most effective features for aqueous solubility measures using the Shapley Additive exPlanations (SHAP) and thermodynamic analysis. Low error, ability to investigate the molecular-level interactions, and compatibility with thermodynamic quantities made the fingerprint method a distinct model compared to other available computational tools. However, it is worth emphasizing that physicochemical descriptor model outperformed the fingerprint model in achieving better predictive accuracy for the given test set.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models

Tayyebi,

Alshami,

Rabiei

et al. 2023

J Cheminform

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show abstract

“…Bhola et al 13 used gravimetric methods to determine the solubility of benzethonium chloride (BTC) in 9 pure solvents and two mixed solvents. Daniela’s group 14 adopted UV–vis spectrophotometry to determine the solubility of isoniazid in nine (PEG 200 + water) cosolvent mixtures and calculated thermodynamic solution, mixing, and transfer functions, which showed that solution entropy was beneficial to the solution dissolution process. Cheng 15 exploited high-performance liquid chromatography (HPLC) to determine the solubility of esculetin in 10 single solvents and concluded that it was highest in methanol and lowest in water.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic Analysis of Eplerenone in 13 Pure Solvents at Temperatures from 283.15 to 323.15 K

Liu,

Zhang

et al. 2024

ACS Omega

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The solubility of eplerenone (EP) in 13 pure solvents (acetonitrile, N,N-dimethylformamide (DMF), acetone, 2-butanone, 4-methyl-2-pentanone, ethyl formate, methyl acetate, ethyl acetate, propyl acetate, butyl acetate, methyl propionate, ethyl propionate, ethanol, and 1-propanol) was determined by the gravimetric method at atmospheric pressure and various temperatures (from 283.15 to 323.15 K). The results showed that the solubility of EP in the selected solvents was positively correlated with the thermodynamic temperature, and the order of solubility of EP at 298.15 K was acetonitrile > DMF > 2-butanone > methyl acetate > 4-methyl-2pentanone > methyl propionate > ethyl acetate > propyl acetate > ethyl formate > acetone > butyl acetate > ethanol >1-propanol. The modified Apelblat model, van't Hoff model, λh model, and polynomial empirical model were used for fitting the solubility data, and then the λh model was found to have the highest fitting accuracy with a minimum ARD of 7.0 × 10 −3 and a minimum RMSD of 6.1 × 10 −6 . The solvent effect between the solute and the solvent was analyzed using linear solvation energy relationship (LSER), and the enthalpy of solvation (Δ sol H°), entropy of solvation (Δ sol S°), and Gibbs free energy of solvation (Δ sol G°) of the dissolution process of EP were calculated by the van't Hoff model, which indicated that the dissolution process of EP in the selected solvents was endothermic, nonspontaneous, and entropyincreasing. In this work, the solubility, dissolution characteristics, and thermodynamic parameters of EP were studied, which will provide data support for the production, crystallization, and purification of EP and will provide important guidance for the crystallization optimization of EP in industry.

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Solubility and Preferential Solvation of Pyrazinamide in Some Aqueous-Cosolvent Mixtures at 298.15 K

Rivas-Ozuna,

Ortiz,

Delgado

et al. 2024

Int J Thermophys

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Equilibrium solubility of antitubercular agent pyrazinamide in mixed solvents is scarce in the literature. Thus, the mole fraction solubility of this drug in aqueous-cosolvent mixtures of 1,4-dioxane or ethanol has been determined at 298.15 K by means of flask shake and UV–Vis analysis. Solubilities were adequately correlated with the modified Nearly Ideal Binary Solvent/Redlich–Kister model. Moreover, some expressions for the local mole fraction of cosolvents and water around the pyrazinamide molecules in solution were derived on the basis of the inverse Kirkwood Buff integrals. Pyrazinamide is preferentially solvated by water in water-rich mixtures and cosolvent-rich mixtures, but preferentially solvated by cosolvent in mixtures with intermediate compositions.

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Thermodynamic Analysis of the Solubility of Isoniazid in (PEG 200 + Water) Cosolvent Mixtures from 278.15 K to 318.15 K

Cited by 7 publications

References 53 publications

Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models

Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models

Thermodynamic Analysis of Eplerenone in 13 Pure Solvents at Temperatures from 283.15 to 323.15 K

Solubility and Preferential Solvation of Pyrazinamide in Some Aqueous-Cosolvent Mixtures at 298.15 K

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