Laboratory of Thermodynamics, Technische Universität Dortmund, Emil-Figge-Str. 70, D-44227 Dortmund, Germany.
J Pharm Sci. 2009 Nov;98(11):4205-15. doi: 10.1002/jps.21725.
The knowledge of the solubility of pharmaceuticals in pure solvents and solvent mixtures is crucial for designing the crystallization process of drug substances. The first step in finding optimal crystallization conditions is usually a solvent screening. Since experiments are very time consuming, a model which allows for solubility predictions in pure solvents and solvent mixtures based only on a small amount of experimental data is required. In this work, we investigated the applicability of the thermodynamic model perturbed-chain statistical associating fluid theory (PC-SAFT) to correlate and to predict the solubility of exemplary five typical drug substances and intermediates (paracetamol, ibuprofen, sulfadiazine, p-hydroxyphenylacetic acid, and p-aminophenylacetic acid) in pure solvents and solvent mixtures.
药物在纯溶剂和混合溶剂中的溶解度知识对于设计药物物质的结晶过程至关重要。寻找最佳结晶条件的第一步通常是溶剂筛选。由于实验非常耗时，因此需要一种仅基于少量实验数据即可对纯溶剂和混合溶剂中的溶解度进行预测的模型。在这项工作中，我们研究了热力学模型受扰链统计关联流体理论（PC-SAFT）在关联和预测五个典型药物物质和中间体（对乙酰氨基酚、布洛芬、磺胺嘧啶、对羟基苯乙酸和对氨基苯乙酸）在纯溶剂和混合溶剂中的溶解度的适用性。
