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Benchtop NIR data standardization on handheld spectrometers to identify paracetamol tablets

近红外光谱 分光计 移动设备 标准化 过程分析技术 化学计量学 可追溯性 校准 计算机科学 数学 光学 工程类 统计 化学工程 操作系统 软件工程 机器学习 物理 生物过程
作者
Corenthin Mees,Jean‐Michel Kauffmann,Juan Antonio Fernández Pierna,Kris De Braekeleer
出处
期刊:Journal of Chemometrics [Wiley]
卷期号:36 (3) 被引量:1
标识
DOI:10.1002/cem.3389
摘要

Abstract Near‐infrared spectroscopy (NIRS) allows innovative applications in terms of quality control, for example, in raw materials verification, in process analytical technology (PAT), and in discrimination between genuine and falsified medicines. The development of small and cheap handheld devices is expanding in the field, while trying to keep similar performances as benchtop instruments have. Considering traceability and quality control of drug compounds, this work is intended to identify 13 different paracetamol tablets on the Belgian market by using NIRS. The performances of a Fourier‐transform near‐infrared spectroscopy (FT‐NIR) benchtop and two handheld NIR spectrometers were investigated comparatively. All spectra were collected through the blister in the reflectance diffuse mode. NIR spectral fingerprints were pretreated and analyzed using principal component analysis (PCA) and classified with soft independent modeling of class analogy (SIMCA). The performances of the spectrometers were evaluated after standardization of the reference benchtop database to the handheld spectrometers. The instrumental response of the benchtop spectrometer was standardized towards the handheld device using the piecewise direct standardization (PDS) algorithm. These investigations permitted the advantages and limitations of NIR data standardization on predictive models to be pointed out. The SIMCA models based on the spectral data of the benchtop (B), handheld 1 (H1), and handheld 2 (H2) instruments had an accuracy of 99.2%, 97.7%, and 96.2%, respectively. The same accuracy was obtained with the models of the transferred benchtop spectra for the H1 and H2 devices. However, adding handheld spectra to the transferred benchtop spectra resulted in models with improved accuracy: from 97.7% to 98.5% for the H1 instrument and from 96.2% to 97.7% for the H2 instrument. The proposed strategy highlights the potential of using a reference database collected by NIRS for pharmaceutical analyses by handheld NIR spectrometers in terms of traceability.
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