Utility of multivariate analysis in modeling the effects of raw material properties and operating parameters on granule and ribbon properties prepared in roller compaction.
This article aimed to model the effects of raw material properties and roller compactor operating parameters (OPs) on the properties of roller compacted ribbons and granules with the aid of principal component analysis (PCA) and partial least squares (PLS) projection. A database of raw material properties was established through extensive physical and mechanical characterization of several microcrystalline cellulose (MCC) and lactose grades and their blends. A design of experiment (DoE) was used for ribbon production. PLS models constructed with only OP-modeled roller compaction (RC) responded poorly. Inclusion of raw material properties markedly improved the goodness of fit (R(2) = .897) and model predictability (Q(2) = 0.72).
Soh
Josephine L P
JL
Department of Industrial and Physical Pharmacy, School of Pharmacy and Pharmaceutical Sciences, Purdue University, West Lafayette, IN 47907, USA.
Wang
Feng
F
Boersen
Nathan
N
Pinal
Rodolfo
R
Peck
Garnet E
GE
Carvajal
M Teresa
MT
Cheney
James
J
Valthorsson
Hedinn
H
Pazdan
Jim
J
D002482:Cellulose; D005079:Excipients; D007785:Lactose; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D025341:Principal Component Analysis; D013607:Tablets; D013678:Technology, Pharmaceutical
D005079:Excipients; D013607:Tablets; D002482:Cellulose; D007785:Lactose; C109691:microcrystalline cellulose