Journal
ANALYTICA CHIMICA ACTA
Volume 961, Issue -, Pages 119-127Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2017.01.021
Keywords
Microwave resonance technology; Moisture measurement; Granule moisture; Process analytical technology (PAT); ICH Q2 method validation; Multiple linear regression
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Funding
- German Federal Environmental Foundation (Deutsche Bundesstiftung Umwelt, DBU) [30816]
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Microwave sensor systems using resonance technology at a single resonance in the range of 2-3 GHz have been shown to be a rapid and reliable tool for moisture determination in solid materials including pharmaceutical granules. So far, their application is limited to lower moisture ranges or limitations above certain moisture contents had to be accepted. Aim of the present study was to develop a novel multi resonance sensor system in order to expand the measurement range. Therefore, a novel sensor using additional resonances over a wide frequency band was designed and used to investigate inherent limitations of first generation sensor systems and material-related limits. Using granule samples with different moisture contents, an experimental protocol for calibration and validation of the method was established. Pursuant to this protocol, a multiple linear regression (MLR) prediction model built by correlating microwave moisture values to the moisture determined by Karl Fischer titration was chosen and rated using conventional criteria such as coefficient of determination (R-2) and root mean square error of calibration (RMSEC). Using different operators, different analysis dates and different ambient conditions the method was fully validated following the guidance of ICH Q2(R1). The study clearly showed explanations for measurement uncertainties of first generation sensor systems which confirmed the approach to overcome these by using additional resonances. The established prediction model could be validated in the range of 7.6-19.6%, demonstrating its fit for its future purpose, the moisture content determination during wet granulations. (C) 2017 Elsevier B.V. All rights reserved.
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