Hogan J, Shue P I, Podczeck F, Newton J M
Department of Pharmaceutics, School of Pharmacy, University of London, offland.
Pharm Res. 1996 Jun;13(6):944-9. doi: 10.1023/a:1016025817183.
The aim of the present work is to identify complex relationships between formulation variables and dosage form properties to aid the development of hard gelatin capsules.
Multivariate statistical analysis was employed based on a statistical design, which considered drug solubility, particle size and concentration, type and concentration of filler and disintegrant, and concentration of standard lubricant and glidant as the main influence factors. Both the filling properties of the formulations and the disintegration/dissolution properties of the capsule content were studied.
From the two multivariate statistical methods used, nonparametric canonical analysis proved to be the superior method to deal with the complex information included in the data. While the filling performance of the formulation could clearly be attributed to the formulation variables such as drug particle size, type of filler, concentration of drug and glidant, the disintegration of the capsules and the dissolution of the drugs was not strongly related to the formulation variables chosen. In this respect as a trend, the drug solubility, and the type of disintegrant and filler appear to be more important factors.
Based on an appropriate number of experiments, organised in a statistical design, nonparametric canonical analysis can be used to identify relationships in a set of data that is grouped in influence and response variables to aid the development of a dosage form.
本研究的目的是确定制剂变量与剂型性质之间的复杂关系，以辅助硬明胶胶囊的研发。
基于一种统计设计采用多变量统计分析，该设计将药物溶解度、粒径和浓度、填充剂和崩解剂的类型和浓度以及标准润滑剂和助流剂的浓度视为主要影响因素。研究了制剂的填充性能以及胶囊内容物的崩解/溶解性能。
在所使用的两种多变量统计方法中，非参数典范分析被证明是处理数据中包含的复杂信息的更优方法。虽然制剂的填充性能显然可归因于制剂变量，如药物粒径、填充剂类型、药物和助流剂的浓度，但胶囊的崩解和药物的溶解与所选的制剂变量没有强烈关联。在这方面，作为一种趋势，药物溶解度、崩解剂和填充剂的类型似乎是更重要的因素。
基于在统计设计中组织的适当数量的实验，非参数典范分析可用于识别一组按影响变量和响应变量分组的数据中的关系，以辅助剂型的研发。
