Quantification of pharmaceuticals via transmission Raman spectroscopy: data sub-selection.
We report the first systematic characterisation of data sub-selection with multivariate analysis to be applied to either TRS or the low-wavenumber Raman region. A model pharmaceutical formulation comprising two polymorphs mixed in the range of 1-99% is investigated. For data sub-selection, sparse partial least squares is for the first time applied to TRS data and compared with principal component analysis. It is found that low-wavenumber data (50-340 cm(-1)) are demonstrably superior for quantitative modelling than data in the more conventional mid-wavenumber range (340-2000 cm(-1)). Our results point the way to enhanced quantitative analytical capabilities for TRS, with potential application areas including pharmaceuticals, security and process-analytical technology, by combining data sub-selection with low-wavenumber-capable optics.
School of Pharmacy, Univeristy of Nottingham, Boots Science Building, NG7 2RD, UK. jonathan.burley@nottingham.ac.uk.
Jonathan C
JC
Burley
Adeyinka
A
Aina
Pavel
P
Matousek
Christopher
C
Brignell
D016208:Databases, Factual; D015999:Multivariate Analysis; D004364:Pharmaceutical Preparations / Q000032:analysis*; D013059:Spectrum Analysis, Raman / Q000379:methods*
D004364:Pharmaceutical Preparations