Tabriz University of Medical Sciences.
J Pharm Pharm Sci. 2019;22(1):466-485. doi: 10.18433/jpps30611.
The cosolvency models frequently used in solubility data modeling of drugs in mixed solvents were reviewed and their accuracies for calculating the solubility of solutes were briefly discussed. The models could be used either for correlation of the generated solubility data with temperature, solvent composition etc or for prediction of unmeasured solubility data using interpolation/extrapolation technique. Concerning the correlation results employing a given number of independent variables, the accuracies of the investigated models were comparable, since they could be converted to a single mathematical form, however, the accuracies were decreased when models emplyed more independent variables. The accurate correlative models could be employed for prediction purpose and/or screening the experimental solubility data to detect possible outliers. With regard to prediction results, the best predictions were made using the cosolvency models trained by a minimum number of experimental data points and an ab initio accurate prediction is not possible so far and further mathematical efforts are needed to provide such a tool. To connect this gap between available accurate correlative models with the ab initio predictive model, the generally trained models for calculating the solubility of various drugs in different binary mixtures, various drugs in a given binary solvent and also a given drug in various binary solvents at isothermal condition and/or different temperatures were reported. Available accuracy criteria used in the recent publications were reviewed including mean percentage deviation (MPD). The MPD for correlative models is 1-10% whereas the corresponding range for predictive models is 10-80% depend on the model capability and the number of independent variables employed by the model. This is an update for a review article published in this journal in 2008.
本文回顾了常用于混合溶剂中药物溶解度数据建模的共溶剂模型，并简要讨论了它们计算溶质溶解度的准确性。这些模型既可以用于相关生成的溶解度数据与温度、溶剂组成等，也可以用于使用内插/外推技术预测未测量的溶解度数据。对于使用给定数量的独立变量的相关结果，所研究的模型的准确性相当，因为它们可以转换为单一的数学形式，但是当模型使用更多的独立变量时，准确性会降低。准确的相关模型可用于预测目的和/或筛选实验溶解度数据以检测可能的异常值。关于预测结果，使用经过最少实验数据点训练的共溶剂模型可以进行最佳预测，目前还不可能进行从头预测，因此需要进一步的数学努力来提供这样的工具。为了连接具有从头预测模型的可用准确相关模型之间的差距，报告了用于计算各种药物在不同二元混合物、给定二元溶剂中的各种药物以及等温条件和/或不同温度下各种二元溶剂中溶解度的一般训练模型。回顾了最近出版物中使用的可用准确性标准，包括平均百分比偏差（MPD）。相关模型的 MPD 为 1-10%，而预测模型的相应范围为 10-80%，具体取决于模型的能力和模型使用的独立变量的数量。这是 2008 年在本期刊上发表的评论文章的更新。
