Sunovion Pharmaceuticals, 84 Waterford Dr, Marlborough, Massachusetts, 01752, USA.
Quality Chemical Laboratories, 3220A Corporate Dr, Wilmington, North Carolina, 28405, USA.
AAPS PharmSciTech. 2021 Apr 21;22(4):140. doi: 10.1208/s12249-021-02011-z.
A discriminatory dissolution model was built through DOE with multivariate analysis of variance (MANOVA) and multiple linear regression (MLR) modeling to assess dissolution operational space for a highly water soluble immediate-release solid dosage drug product. The dissolution was utilized in the following five aspects: (1) understand the impact of individual variables and their interactions on dissolution performance through effect analysis; (2) explain the lack of discriminatory power of the initial dissolution condition used in early phase development by prediction profiler; (3) predict discriminatory dissolution operational space to differentiate photo degraded drug products from control with contour profiler analysis; (4) validate by the external experimental data acquired with the initial nondiscriminatory dissolution condition and the predicted discriminatory dissolution condition, followed by model independent statistical analysis (e.g., f2); and (5) establish correlation of the discriminatory dissolution with disintegration. The selected discriminatory dissolution method was validated by demonstrating accuracy, precision and linearity, specificity, repeatability, intermediate precision, stability, filter verification, and robustness.
采用 DOE 建立了一个判别性溶出模型，通过多元方差分析（MANOVA）和多元线性回归（MLR）建模，评估高水溶性即释固体制剂的溶出操作空间。溶出在以下五个方面得到了利用：（1）通过效应分析了解单个变量及其相互作用对溶出性能的影响；（2）通过预测轮廓图解释早期开发阶段中初始溶出条件缺乏判别能力；（3）通过轮廓图分析预测区分光降解药物与对照品的溶出操作空间；（4）通过初始非判别性溶出条件和预测的判别性溶出条件获得的外部实验数据进行验证，然后进行模型独立的统计分析（例如，f2）；（5）建立判别性溶出与崩解的相关性。通过证明准确性、精密度和线性、特异性、重复性、中间精密度、稳定性、过滤验证和稳健性，验证了所选的判别性溶出方法。
