School of Life Sciences, University of Sussex, Brighton, BN1 9QJ, UK.
School of Life Sciences, Faculty of Creative Arts, Technologies and Science, University of Bedfordshire, Luton, UK.
AAPS PharmSciTech. 2021 Dec 28;23(1):42. doi: 10.1208/s12249-021-02192-7.
Solubility determination of poorly water-soluble drugs is pivotal for formulation scientists when they want to develop a liquid formulation. Performing such a test with different ratios of cosolvents with water is time-consuming and costly. The scarcity of solubility data for poorly water-soluble drugs increases the importance of developing correlation and prediction equations for these mixtures. Therefore, the aim of the current research is to determine the solubility of acetylsalicylic acid in binary mixtures of ethanol+water at 25 and 37°C. Acetylsalicylic acid is non-stable in aqueous solutions and readily hydrolyze to salicylic acid. So, the solubility of acetylsalicylic acid is measured in ethanolic mixtures by HPLC to follow the concentration of produced salicylic acid as well. Moreover, the solubility of acetylsalicylic acid is modeled using different cosolvency equations. The measured solubility data were also predicted using PC-SAFT EOS model. DSC results ruled out any changes in the polymorphic form of acetylsalicylic acid after the solubility test, whereas XRPD results showed some changes in crystallinity of the precipitated acetylsalicylic acid after the solubility test. Fitting the solubility data to the different cosolvency models showed that the mean relative deviation percentage for the Jouyban-Acree model was less than 10.0% showing that this equation is able to obtain accurate solubility data for acetylsalicylic acid in mixtures of ethanol and water. Also, the predicted data with an average mean relative deviation percentage (MRD%) of less than 29.65% show the capability of the PC-SAFT model for predicting solubility data. A brief comparison of the solubilities of structurally related solutes to acetylsalicylic acid was also provided.
当制剂科学家想要开发液体制剂时,测定疏水性药物的溶解度是至关重要的。用不同比例的共溶剂与水进行这样的测试既耗时又昂贵。疏水性药物的溶解度数据稀缺,这增加了为这些混合物开发相关和预测方程的重要性。因此,目前研究的目的是在 25 和 37°C 的乙醇+水二元混合物中测定乙酰水杨酸的溶解度。乙酰水杨酸在水溶液中不稳定,容易水解为水杨酸。因此,通过 HPLC 测定乙酰水杨酸在乙醇混合物中的溶解度,同时也可以跟踪生成的水杨酸的浓度。此外,还使用不同的共溶方程对乙酰水杨酸的溶解度进行建模。使用 PC-SAFT EOS 模型对测量的溶解度数据进行预测。DSC 结果排除了溶解度测试后乙酰水杨酸多晶型形式发生变化的可能性,而 X 射线粉末衍射(XRPD)结果表明溶解度测试后沉淀的乙酰水杨酸结晶度发生了一些变化。将溶解度数据拟合到不同的共溶模型表明,Jouyban-Acree 模型的平均相对偏差百分比小于 10.0%,表明该方程能够获得乙醇和水混合物中乙酰水杨酸的准确溶解度数据。此外,预测数据的平均相对偏差百分比(MRD%)小于 29.65%,表明 PC-SAFT 模型具有预测溶解度数据的能力。还提供了与乙酰水杨酸结构相关的溶质溶解度的简要比较。