Application of principal component analysis enables to effectively find important physical variables for optimization of fluid bed granulator conditions

作者：Otsuka Tomoko; Iwao Yasunori; Miyagishima Atsuo; Itai Shigeru^*

来源：International Journal of Pharmaceutics, 2011, 409(1-2): 81-88.

DOI：10.1016/j.ijpharm.2011.02.044

• Principal component analysis
• Multiple regression analysis
• Fluid bed granulation
• Powder property
• Compactability
• Tablet property

Principal component analysis was applied to effectively optimize the operational conditions of a fluidized bed granulator for preparing granules with excellent compaction and tablet physical properties. The crucial variables that affect the properties of the granules, their compactability and the resulting tablet properties were determined through analysis of a series of granulation and tabletting experiments. Granulation was performed while the flow rate and concentration of the binder were changed as independent operational variables, according to a two-factor central composite design. Thirteen physicochemical properties of granules and tablets were examined: powder properties (particle size, size distribution width. Carr's index, Hausner ratio and aspect ratio), compactability properties (pressure transmission ratio, die wall force and ejection force) and tablet properties (tensile strength, friability, disintegration time, weight variation and drug content uniformity). Principal component analysis showed that the pressure transmission ratio, die wall force and Carr's index were the most important variables in granule preparation. Multiple regression analysis also confirmed these results. Furthermore, optimized operational conditions obtained from the multiple regression analysis enabled the production of granules with desirable properties for tabletting. This study presents the first use of principle component analysis for identifying and successfully predicting the most important variables in the process of granulation and tabletting.

• 出版日期2011-5-16