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Correlation and prediction of drug molecule solubility in mixed solvent systems with the Nonrandom Two-Liquid Segment Activity Coefficient (NRTL-SAC) model
被引:128
作者:
Chen, Chau-Chyun
Crafts, Peter A.
机构:
[1] Aspen Technol Inc, Cambridge, MA 02141 USA
[2] AstraZeneca Pharmaceut Inc, Proc R&D, Macclesfield SK10 2NA, Cheshire, England
关键词:
D O I:
10.1021/ie051326p
中图分类号:
TQ [化学工业];
学科分类号:
0817 ;
摘要:
The recently developed Nonrandom Two-Liquid Segment Activity Coefficient (NRTL-SAC) model [ reported by Chen and Song, Ind. Eng. Chem. Res. 2004, 43, 8354] offers a practical thermodynamic framework to predict drug solubility in a wide range of solvents, based on a small initial set of measured solubility data. The model yields satisfactory results in first correlating drug solubility in a few representative pure solvents and then qualitatively predicting drug solubility in other pure solvents. Here, we investigate the applicability of the NRTL-SAC model for predicting drug solubility in mixed solvents for three molecules: acetaminophen, sulfadiazine, and cimetidine. The study shows that the model provides robust correlation and prediction of drug solubility in both pure and mixed solvents, with a qualitative level of accuracy. The model is a useful tool in support of the early stages of crystallization process development and other areas of drug process design.
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页码:4816 / 4824
页数:9
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