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Veterinary pharmacology and therapeutics

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.

Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility.

Solubility of sulfamerazine in (ethylene glycol + water) mixtures: Measurement, correlation, dissolution thermodynamics and preferential solvation

Liver ischemia-reperfusion injury (IRI) is a phenomenon inherent to hepatic surgery that severely compromises the organ functionality, whose underlying mechanisms involve cellular and molecular interrelated processes leading to the development of an excessive inflammatory response. Liver resident cells and those recruited in response to injury generate pro-inflammatory signals such as reactive oxygen species, cytokines, chemokines, proteases and lipid mediators that contribute to hepatocellular necrosis and apoptosis. Besides, dying hepatocytes release damage-associated molecular patterns that activate inflammasomes to further stimulate inflammatory responses leading to massive cell death. Since liver IRI is a complication of hepatic surgery in man, extensive preclinical studies have assessed potential protective strategies, including the supplementation with natural compounds, with the objective to downregulate nuclear factor-κB functioning, the main effector of inflammatory responses. This can be accomplished by either the activation of peroxisome proliferator-activated receptor-α, G protein-coupled receptor 120 or antioxidant signaling pathways, the synthesis of specific pro-resolving mediators, downregulation of Toll-like receptor 4 activity or additional contributory mechanisms that are beginning to be understood. The latter aspect is a crucial issue to be accomplished in preclinical studies, in order to establish adequate conditions for the supplementation with natural products before major liver surgeries in man involving warm IR, such as hepatic trauma or resection of large intrahepatic tumors.

Beneficial effects of natural compounds on experimental liver ischemia-reperfusion injury.

Prediction of sulfonamides’ solubilities in the mixed solvents using solvation parameters

The solubility of sulfamethazine (SMT) in ethylene glycol (EG) + water (W) cosolvent mixtures was determined at nine temperatures (278.15, 283.15, 288.15, 293.15, 298.15, 303.15, 308.15, 313.15 and 318.15 K) by means of the stirring method. From the solubility data, the thermodynamic functions of solution, transfer and mixing were calculated using the Gibbs and van´t Hoff equations. On the other hand, the preferential solvation parameters of SMT were determined by means of the method of the inverse integrals of Kirkwood-Buff (IKBI). In general terms, the solubility of SMT is favored by the increase in temperature and the decrease in the polarity of the cosolvent system, thus the maximum solubility is reached in pure EG at 318.15 K and the minimum in pure water at 278.15 K. Gibbs energy is positive in all cases, with a higher contribution from the energy component (enthalpy of solution). Regarding enthalpy-entropic compensation, the process is driven in all cases by the enthalpy of solution. Finally, SMT is preferentially solvated by water in mixtures with higher polarity and by EG in less polar mixtures.

https://repository.ucc.edu.co/bitstream/20.500.12494/32654/1/Journal%20of%20the%20Taiwan%20Institute%20of%20Chemical%20Engineers.pdf

Solution thermodynamics and preferential solvation of sulfamethazine in ethylene glycol + water mixtures

The equilibrium solubility of amygdalin in [ethanol (1) + water (2)] mixtures at 293.15 K to 328.15 K was reported. The thermodynamic properties (standard enthalpy ΔsolnH°, standard entropy ΔsolnS°, and standard Gibbs energy of solution ΔsolnG°) were computed using the generated solubility data via van't Hoff and Gibbs equations. The dissolution process of amygdalin is endothermic and the driving mechanism in all mixtures is entropy. Maximal solubility was achieved in 0.4 mole fraction of ethanol at 328.15 K and the minimal one in neat ethanol at 293.15 K. Van't Hoff, Jouyban-Acree-van't Hoff, and Buchowski-Ksiazczak models were used to simulate the obtained solubility data. The calculated solubilities deviate reasonably from experimental data. Preferential solvation parameters of amygdalin in mixture solvents were analyzed using the inverse Kirkwood-Buff integrals (IKBI) method. Amygdalin is preferentially solvated by water in ethanol-rich mixtures, whereas in water-rich mixtures, there is no clear evidence that determines which of water or ethanol solvents would be most likely to solvate the molecule.

Solubility, Solution Thermodynamics, and Preferential Solvation of Amygdalin in Ethanol + Water Solvent Mixtures.

Hydroxytyrosol (HXT) (also known as 3,4-dihydroxyphenylethanol,) is a biophenol extracted from olive. HXT is known for its high antioxidant significance effect. In this work, we focused on the study of the behavior of the solubility of HXT in binary solvent mixtures (ethanol + water) as well as the thermodynamic proprieties. The solubility of HXT in water, ethanol and in binary solvent mixtures (ethanol + water) was measured at five different temperatures from (293.15 to 318.15) K. The enthalpy of fusion and the melting point of HXT were experimentally determined since they are essential for the study of the of solubility and crystallization process. Thermodynamic properties of dissolution of the HXT (Gibbs energy (ΔsolG°), molar enthalpy of dissolution (ΔsolH°), and molar entropy of dissolution (ΔsolS°)) are predicted using the van’t Hoff analysis, the Gibbs equation, and the measured solubilities data. The preferential solvation has been determined using the inverse Kirkwood–Buff integral (IKBI) theory.

Solubility of Hydroxytyrosol in binary mixture of ethanol + water from (293.15 to 318.15) K: Measurement, correlation, dissolution thermodynamics and preferential solvation

Abdelkarim Aydi

Papers

Solution thermodynamics and preferential solvation of sulfamethazine in ethylene glycol + water mixtures

Solubility, Solution Thermodynamics, and Preferential Solvation of Amygdalin in Ethanol + Water Solvent Mixtures.

Solubility of Hydroxytyrosol in binary mixture of ethanol + water from (293.15 to 318.15) K: Measurement, correlation, dissolution thermodynamics and preferential solvation