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Solubility of a hydrophobic model drug in a binary solvent system of interest for industrial freeze-drying

Abstract : The aim of this work is to investigate the solubility behavior of a hydrophobic model drug, diazepam, in a binary solvent of industrial interest for freeze-drying, the water + tert-butyl alcohol mixture. Firstly, a model describing the dependence of the excess volume of the solvent on both composition and temperature was validated from experimental data obtained during this work and literature data. This model was used to derive expressions for excess partial thermodynamic quantities and their variations with respect to composition and temperature were discussed in terms of molecular interactions and structural arrangements in solution. Secondly, the solubility of diazepam in neat solvents and different binary solvent mixtures was determined. The density of drug-saturated mixtures was also determined as well as the thermophysical properties of original diazepam crystals and excess solid phases from solid-liquid equilibria. The thermodynamic properties relative to the dissolution process of the drug under saturation condition were obtained from solubility temperature dependence using van’t Hoff plots. From these, the excess partial thermodynamic properties of diazepam in saturated mixtures were computed and the forces driving the drug solubility variation with respect to the solvent composition were identified. Finally, two excess Gibbs energy models, the Scatchard-Hildebrand and combined Scatchard-Hildebrand/Flory-Huggins models were tested to represent the solubility data. Their capabilities in correlating the dependence of the drug solubility on both the solvent composition and temperature were evaluated and compared
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Submitted on : Monday, February 26, 2018 - 6:06:05 PM
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  • HAL Id : tel-01717820, version 1

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Fabrice Aman-Pommier. Solubility of a hydrophobic model drug in a binary solvent system of interest for industrial freeze-drying. Chemical and Process Engineering. Université de Lyon, 2017. English. ⟨NNT : 2017LYSE1220⟩. ⟨tel-01717820⟩

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