Evaluation of the physicochemical properties of fine globular granules prepared by a multi-functional rotor processor.
Multiple regression analysis (MRA) and principal component analysis (PCA) have been used in the present study to examine the relationships between the operational conditions of a unique multi-functional rotor processor, material attributes such as water content during granulation, and a series of associated micromeritics, including the flowability, granule mean size and granule density values. A variety of different operational conditions were tested, including the binder flow rate, atomization pressure, slit air flow rate, rotating speed and temperature of the inlet air. The results of MRA revealed several trends, including (1) the granule mean size was negatively affected by the atomization pressure, and positively affected by the binder flow rate; (2) the granule flow property, Carr's index was positively affected by the atomization pressure, and negatively affected by the slit air flow rate; and (3) the granule density was positively affected by the rotating speed. Taken together, these results suggested that the binder flow rate, atomization pressure and slit airflow rate were critical process parameters for the preparation of fine globular granules. Using PCA, it was possible to examine each relationship of all 19 batches and 10 variables, as well as determine which process parameters or material attributes impacted on the quality of the final product. The PCA results revealed that the roundness was positively correlated with the water content. Therefore, we believe this fundamental information will be important for the development of processes for the facile manufacture of fine globular granules.
Department of Pharmacy Practice and Science, School of Pharmaceutical Sciences, University of Shizuoka.
Shin-ichiro
S
Kimura
Yasunori
Y
Iwao
Masayuki
M
Ishida
Shuji
S
Noguchi
Shigeru
S
Itai
Shinya
S
Uchida
Masaki
M
Yamada
Noriyuki
N
Namiki
D004304:Dosage Forms; D004867:Equipment Design; D010316:Particle Size; D025341:Principal Component Analysis; D012044:Regression Analysis; D013678:Technology, Pharmaceutical / Q000295:instrumentation* / Q000379:methods*
D004304:Dosage Forms