College of Pharmacy, Pusan National University, Busan, Republic of Korea.
Drug Dev Ind Pharm. 2012 Sep;38(9):1117-27. doi: 10.3109/03639045.2011.641563. Epub 2012 Feb 20.
A robust experimental design method was developed with the well-established response surface methodology and time series modeling to facilitate the formulation development process with magnesium stearate incorporated into hydrophilic matrix tablets. Two directional analyses and a time-oriented model were utilized to optimize the experimental responses. Evaluations of tablet gelation and drug release were conducted with two factors x₁ and x₂: one was a formulation factor (the amount of magnesium stearate) and the other was a processing factor (mixing time), respectively. Moreover, different batch sizes (100 and 500 tablet batches) were also evaluated to investigate an effect of batch size. The selected input control factors were arranged in a mixture simplex lattice design with 13 experimental runs. The obtained optimal settings of magnesium stearate for gelation were 0.46 g, 2.76 min (mixing time) for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The optimal settings for drug release were 0.33 g, 7.99 min for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The exact ratio and mixing time of magnesium stearate could be formulated according to the resulting hydrophilic matrix tablet properties. The newly designed experimental method provided very useful information for characterizing significant factors and hence to obtain optimum formulations allowing for a systematic and reliable experimental design method.
开发了一种稳健的实验设计方法,该方法结合了成熟的响应面法和时间序列建模,以促进包含硬脂酸镁的亲水基质片剂的配方开发过程。利用双方向分析和面向时间的模型来优化实验响应。通过两个因素 x₁ 和 x₂ 评估片剂的凝胶化和药物释放:一个是配方因素(硬脂酸镁的量),另一个是加工因素(混合时间)。此外,还评估了不同的批大小(100 和 500 片批),以研究批大小的影响。选择的输入控制因素在混合物单纯形格子设计中排列,有 13 个实验运行。凝胶化的硬脂酸镁的最佳设置为 0.46 g,混合时间为 2.76 min(100 片批)和 1.54 g,混合时间为 6.51 min(500 片批)。对于药物释放的最佳设置为 0.33 g,混合时间为 7.99 min(100 片批)和 1.54 g,混合时间为 6.51 min(500 片批)。根据所得亲水基质片剂的性质,可以确定硬脂酸镁的确切比例和混合时间。新设计的实验方法为表征重要因素提供了非常有用的信息,从而获得允许系统和可靠的实验设计方法的最佳配方。