Abstract
Raman spectroscopy is widely used for quantitative pharmaceutical analysis, but a common obstacle to its use is sample fluorescence masking the Raman signal. Time-gating provides an instrument-based method for rejecting fluorescence through temporal resolution of the spectral signal and allows Raman spectra of fluorescent materials to be obtained. An additional practical advantage is that analysis is possible in ambient lighting. This study assesses the efficacy of time-gated Raman spectroscopy for the quantitative measurement of fluorescent pharmaceuticals. Time-gated Raman spectroscopy with a 128 × (2) × 4 CMOS SPAD detector was applied for quantitative analysis of ternary mixtures of solid-state forms of the model drug, piroxicam (PRX). Partial least-squares (PLS) regression allowed quantification, with Raman-active time domain selection (based on visual inspection) improving performance. Model performance was further improved by using kernel-based regularized least-squares (RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized. Overall, time-gated Raman spectroscopy, especially with optimized data analysis in both the spectral and time dimensions, shows potential for sensitive and relatively routine quantitative analysis of photoluminescent pharmaceuticals during drug development and manufacturing.
Highlights
Model performance was further improved by using kernel-based regularized least-squares (RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized
Raman spectroscopy is an established method for qualitative and quantitative analysis of active pharmaceutical ingredients (APIs) exhibiting different solid-state forms and often enables rapid, nondestructive measurements with no sample preparation needed.[7−9] The spectra can be measured through container walls, blisters, plastic bags, and in an aqueous environment because Raman spectroscopy has low sensitivity for water.[10]
The aim of this study was to investigate the potential of timegated Raman spectroscopy for quantitative analysis of fluorescent pharmaceutical solids
Summary
(RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized. Effective methods for evaluating the possible changes in solidstate structure during research and development, manufacturing, and storing are needed.[5,6] Raman spectroscopy is an established method for qualitative and quantitative analysis of APIs exhibiting different solid-state forms and often enables rapid, nondestructive measurements with no sample preparation needed.[7−9] The spectra can be measured through container walls, blisters, plastic bags, and in an aqueous environment because Raman spectroscopy has low sensitivity for water.[10] The form of the sample is flexible; powders, slurries, pellets, emulsions, and films are all suitable for Raman spectroscopy. Kernel-based regularized leastsquares (kernel-based RLS) regression is another approach that has the ability to learn functions from the nonlinear data features which, when combined with feature selection algorithms such as greedy forward feature selection, optimizes the use of information provided by the data features.[18,19] PLS and RLS are quite similar in that they aim to shrink the solution away from the ordinary least-squares solution toward the directions of the variable space of large sample spread with lower variability.[20]
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