Evaluation of In-Line Raman Spectroscopic Monitoring of Size Reduction during Wet Media Milling of Biopharmaceutics Classification System Class II Drugs. Issue 12 (December 2014)

• Record Type: Journal Article
• Authors: Ying, Ye; Afolabi, Afolawemi; Bilgili, Ecevit; Iqbal, Zafar
• Is Part Of: Applied spectroscopy. Volume 68:Issue 12(2014)
• Page Start: 1411
• Page End: 1417
• Publication Date: 2014-12
• Subjects: In-line Raman spectroscopy -- Laser diffraction -- Biopharmaceutics Classification System -- BCS class II drugs -- Partial least square analysis -- PLS analysis -- Wet stirred media milling -- Bioavailability enhancement; Spectrum analysis -- Periodicals; 543.505
• DOI: 10.1366/13-07423
• Languages: English
• ISSNs: 0003-7028

Abstract

The aim of this study was to evaluate in-line Raman spectroscopy for monitoring the progress of particle size reduction in real time during wet-stirred media milling of two Biopharmaceutics Classification System (BCS) Class II drugs, griseofulvin and naproxen. To develop a validated online Raman method, Raman analyses were carried out offline by taking samples from the mill at various milling times. A multivariate linear model (partial least squares, PLS) was fitted to the raw data obtained from the Raman measurements and good linearity between online and offline Raman spectra was found. Line intensities (I) of the in-line spectra obtained during the wet media milling were processed by multivariate analyses and correlated with both the median size (d 50 ) and the 90% passing particle size (d 90 ), which were measured offline by laser diffraction. A two-parameter exponential growth model of the form d = exp[ A(I – I 0 )] was found to establish a good correlation ( R 2 > 0.90) as a statistically significant model with statistically significant parameters ( P < 10 −4 ). The correlations were applicable to milled suspensions with particles in the approximate size range of 0.1–6 μm for griseofulvin and 0.1–8 μm for naproxen. These results suggest that in-line Raman spectroscopy can be used to successfully monitor the progress of particle size reduction during wet media milling.