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Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 72,
  • Issue 4,
  • pp. 551-561
  • (2018)

An Application for the Quantitative Analysis of Pharmaceutical Tablets Using a Rapid Switching System Between a Near-Infrared Spectrometer and a Portable Near-Infrared Imaging System Equipped with Fiber Optics

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Abstract

We present a rapid switching system between a newly developed near-infrared (NIR) spectrometer and its imaging system to select the spot size of a diffuse reflectance (DR) probe. In a previous study, we developed a portable NIR imaging system, known as D-NIRs, which has significant advantages over other systems. Its high speed, high spectral resolution, and portability are particularly useful in the process of monitoring pharmaceutical tablets. However, the spectral accuracies relating to the changes in the formulation of the pharmaceutical tablets have not been fully discussed. Therefore, we improved the rapid optical switching system and present a new model of D-NIRs (ND-NIRs) here. This system can automatically switch the optical paths of the DR and NIR imaging probes, greatly contributing to the simultaneous measurement of both the imaging and spot. The NIR spectra of the model tablets, including 0–10% ascorbic acid, were measured and simultaneous NIR images of the tablets were obtained. The predicted results using spot sizes for the DR probe of 1 and 5 mm diameter, resulted in concentrations of R2 = 0.79 and 0.94, with root mean square errors (RMSE) of 1.78 and 0.89, respectively. For tablets with a high concentration of ascorbic acid, the NIR imaging results showed inhomogeneity in concentration. However, the predicted values for the low concentration samples appeared higher than the known concentration of the tablets, although the homogeneity of the concentration was confirmed. In addition, the optimal spot size using NIR imaging data was estimated to be 5–7 mm. The results obtained in this study show that the spot size of the fiber probe, attached to a spectrometer, is important in developing a highly reliable model to determine the component concentration of a tablet.

© 2018 The Author(s)

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