Abstract
Using partial least square discriminate analysis (PLSDA), we studied the spectroscopic differences between the commonly used filler-binder microcrystalline cellulose (MCC) from five manufactures. These samples had subtle differences in the chemical and physical properties, which are often the cause of differences in excipient performance. Studying these differences allowed us to build and validate a model to classify five manufacturers of MCC using near-infrared (NIR) spectra. The sample training set includes 39 MCC samples collected from five manufactures with regions spanning the United States of America, Japan, Taiwan, Germany, and Brazil. The samples from individual manufacturers include diverse grades that differ in moisture content, particle size, and bulk density. Optimized pretreatment methods were identified as standard normal variate normalization, followed by Savitzky-Golay second derivative, mean centering, and orthogonal signal correction. The model was optimized with cross-validation and validated with an independent sample set comprising nine samples collected from those five manufacturers. The results showed that none of the samples in the independent validation set was misclassified. The score and loading plots revealed that the differences in content of oxidized cellulose group, water content and states, hydrogen bonding, and degree of polymerization of the MCC samples are responsible for the class differentiation. Permutation test demonstrated that the outcome of the PLSDA model was significantly different from that of the randomly generated model. The advantages and limitations of the method in this type of application were discussed.
PDF Article
More Like This
Comprehensive study of solid pharmaceutical tablets in visible, near infrared (NIR), and longwave infrared (LWIR) spectral regions using a rapid simultaneous ultraviolet/visible/NIR (UVN) + LWIR laser-induced breakdown spectroscopy linear arrays detection system and a fast acousto-optic tunable filter NIR spectrometer
Clayton S.C Yang, Feng Jin, Siva R. Swaminathan, Sita Patel, Evan D. Ramer, Sudhir B. Trivedi, Ei E. Brown, Uwe Hommerich, and Alan C. Samuels
Opt. Express 25(22) 26885-26897 (2017)
Cited By
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription