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基于真实溶剂的导体类筛选模型预测药物溶解度

Prediction of solubility of drugs by conductor-like screening model for real solvents.

作者信息

Ikeda Hirotaka, Chiba Kouji, Kanou Atsushi, Hirayama Noriaki

机构信息

Computational Science Department, Science & Technology Systems Division, Ryoka Systems Inc, Chiba, Japan.

出版信息

Chem Pharm Bull (Tokyo). 2005 Feb;53(2):253-5. doi: 10.1248/cpb.53.253.

Abstract

The solubility of drugs in solvents is fundamentally important for drug development and manufacturing. As the experimental measurements of the solubility are extremely laborious tasks, reliable prediction methods are highly required. We have employed the conductor-like screening model for real solvents (COSMO-RS) in predicting the solubility of drugs and drug-like compounds in various solvent systems. We also evaluated the salt effect on the solubility of caffeine using this method. The present results demonstrated that COSMO-RS has reasonably reproduced the experimental data and have proved that this method is generally available in predicting the solubility of drugs.

摘要

药物在溶剂中的溶解度对药物研发和生产至关重要。由于溶解度的实验测量是极其费力的任务,因此非常需要可靠的预测方法。我们已采用真实溶剂的导体类筛选模型(COSMO-RS)来预测药物及类药物化合物在各种溶剂体系中的溶解度。我们还用此方法评估了盐对咖啡因溶解度的影响。目前的结果表明,COSMO-RS已合理地重现了实验数据,并证明该方法在预测药物溶解度方面普遍可用。

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