Thermodynamic analysis and molecular dynamic simulation of the solubility of vortioxetine hydrobromide in three binary solvent mixtures

Ma, Yiming; Cao, Yun; Yang, Yang; Li, Wanya; Shi, Peng; Wang, Shuo; Tang, Weiwei

doi:10.1016/j.molliq.2018.09.130

Cited by 95 publications

(16 citation statements)

References 29 publications

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“…This ordering is not strictly consistent with the polar order of the solvent (acetonitrile > ethanol > n -propanol > iso -propanol) . This inconsistency and the cosolvency phenomenon indicate that the solubility of CST is influenced by complex reasons such as the solute–solvent interaction, the solvent–solvent interaction, the polarities of the solute and the solvent, the formation of hydrogen bond, − and so on.…”

Section: Resultsmentioning

confidence: 96%

Solubility Measurement and Correlation of Ceftiofur Sodium Trihydrate in Four Binary Solvent Mixtures

Liu

et al. 2020

J. Chem. Eng. Data

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The solubility of ceftiofur sodium trihydrate (CST) in binary solvent mixtures of water + acetonitrile, water + ethanol, water + n-propanol, and water + iso-propanol at temperatures from 273.15 to 313.15 K (P = 0.1 MPa) was measured by a laser dynamic method. The experimental results show that the solubility is positively correlated with temperature. In the four binary solvent systems, the solubility value of CST initially increases first and then decreases with increasing organic solvent composition. The maximum solubility values occur in the molar content of organic solvent of about 0.5 for water + acetonitrile, 0.5 for water + ethanol, 0.4 for water + npropanol, and 0.4 for water + iso-propanol. The accuracy of experimental results was examined by the Apelblat model, the Van't-JA model, and the Apel-JA model, and the Apelblat model shows the best fitting performance.

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Section: Resultsmentioning

confidence: 96%

Solubility Measurement and Correlation of Ceftiofur Sodium Trihydrate in Four Binary Solvent Mixtures

Liu

et al. 2020

J. Chem. Eng. Data

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“…In addition to the MOE molecular descriptors, the three kinds of solute–solvent interactions, API–water, API–ethanol, and API–water/ethanol, were taken into account by calculating the solvation free energy. Structure and energy optimization were performed by Materials Studio package, , and the further calculation of solvation free energy was carried out by COSMOthermX19 . For all of the following models, initial studies were conducted to evaluate model performance against the number of descriptors used.…”

Section: Methodsmentioning

confidence: 99%

Design of Spherical Crystallization of Active Pharmaceutical Ingredients via a Highly Efficient Strategy: From Screening to Preparation

Sun

Liu

et al. 2021

ACS Sustainable Chem. Eng.

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This work aims to develop a highly efficient spherical crystallization from screening to preparation stage based on liquid−liquid phase separation (LLPS). Mixtures than can undergo an LLPS split into two liquid phases with different physical properties, and the oil droplets formed during that process make LLPS a promising approach to prepare spherical particles of an active pharmaceutical ingredient (API). In the screening stage, three machine learning (ML) models (artificial neural network, support vector machine, and logistic regression) were established for predicting LLPS for an API. Two linear models, a simple linear model and a machine learning-based linear model, were also constructed to produce further optimization. The ML-based prediction of LLPS was first established in this work and showed high accuracy and reliability. Also, when compared to a method where the screening depended on the results of experiments, the prediction model highly reduced the use of chemical substances and saved labor and time. In the preparation stage, water and ethanol, which have low toxicity to mammals and have environmental advantages over other organic solvents, were applied as the solvents of LLPS-based spherical crystallization. The LLPS-based preparation process of spherical particles possesses advantages in terms of reduction of the number of unit operations as well as energy consumption and processing cost.

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“…In the continuous crystallization process, the quality of LCB inside the crystallizer varies with time and is determined by offline sampling by the previous method [32] . This is applied to determine whether the process has achieved a steady state inside the crystallizer.…”

Section: Methodsmentioning

confidence: 99%

Enhancing continuous reactive crystallization of lithium carbonate in multistage mixed suspension mixed product removal crystallizers with pulsed ultrasound

Shi

et al. 2021

Ultrasonics Sonochemistry

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Thermodynamic analysis and molecular dynamic simulation of the solubility of vortioxetine hydrobromide in three binary solvent mixtures

Cited by 95 publications

References 29 publications

Solubility Measurement and Correlation of Ceftiofur Sodium Trihydrate in Four Binary Solvent Mixtures

Solubility Measurement and Correlation of Ceftiofur Sodium Trihydrate in Four Binary Solvent Mixtures

Design of Spherical Crystallization of Active Pharmaceutical Ingredients via a Highly Efficient Strategy: From Screening to Preparation

Enhancing continuous reactive crystallization of lithium carbonate in multistage mixed suspension mixed product removal crystallizers with pulsed ultrasound

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