Jouyban Abolghasem
Faculty of Pharmacy and Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Chem Pharm Bull (Tokyo). 2006 Nov;54(11):1561-6. doi: 10.1248/cpb.54.1561.
A numerical method is proposed for predicting solubility of drugs in water-PEG 400 mixtures based on the Jouyban-Acree cosolvency model. The accuracy of the proposed method is evaluated by computing mean percentage deviation (MPD) and compared with that of log-linear model of Yalkowsky. The overall MPDs of the Jouyban-Acree model and the most accurate version of Yalkowsky's model are 39.8 (+/-46.7) % and 175.8 (+/-266.4) %, respectively, and the mean difference is statistically significant (p < 0.0005). The proposed method produces acceptable residual distribution and the probability of solubility prediction with residual log of solubility <0.5 unit is 0.86. The applicability of the proposed method could be extended for predicting the solubility of drugs in water-PEG 400 mixtures at various temperatures. The impact of various log P values computed using different software is also studied and the results of ANOVA revealed that there are no significant differences between the accuracy of the predicted solubilities employing various log P values.
提出了一种基于Jouyban-Acree共溶剂模型预测药物在水-聚乙二醇400混合物中溶解度的数值方法。通过计算平均百分比偏差（MPD）评估所提方法的准确性，并与Yalkowsky的对数线性模型进行比较。Jouyban-Acree模型和Yalkowsky模型最精确版本的总体MPD分别为39.8（±46.7）%和175.8（±266.4）%，平均差异具有统计学意义（p < 0.0005）。所提方法产生了可接受的残差分布，溶解度预测残差对数<0.5单位的概率为0.86。所提方法的适用性可扩展到预测不同温度下药物在水-聚乙二醇400混合物中的溶解度。还研究了使用不同软件计算的各种log P值的影响，方差分析结果表明，采用各种log P值预测溶解度的准确性之间没有显著差异。
