Time-Gated Raman Spectroscopy for Quantitative Determination of Solid-State Forms of Fluorescent Pharmaceuticals
Author(s) -
Tiina Lipiäinen,
Jenni Pessi,
Parisa Movahedi,
Juha Koivistoinen,
Lauri Kurki,
Mari Tenhunen,
Jouko Yliruusi,
Anne Juppo,
Jukka Heikkonen,
Tapio Pahikkala,
Clare J. Strachan
Publication year - 2018
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/acs.analchem.8b00298
Subject(s) - raman spectroscopy , chemistry , partial least squares regression , analytical chemistry (journal) , fluorescence , biological system , spectroscopy , chemometrics , quantitative analysis (chemistry) , raman scattering , optics , chromatography , statistics , mathematics , physics , quantum mechanics , biology
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.
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