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The present study aims to suggest a method to identify defective tablets by near infrared (NIR) imaging. A newly developed portable imaging system (D-NIRs) was used in this study, in which the spectrometer is equipped with a high-density photodiode array detector to record high-quality spectra with 1.25 nm spectral resolution. This system is highly portable and allows an image of a target tablet to be developed in approximately 10 s. Normal tablets containing 0.1–20 % magnesium stearate, ascorbic acid, corn starch and talc were prepared. NIR spectra in the 950–1700 nm region of each pixel in a tablet were measured, and NIR images were generated from the second derivative of the spectra at 1213 nm. It was confirmed that the spectral distribution in a tablet passed as a normal distribution by the goodness-of-fit test (p ≤ 0.05). Consequently, the average of the spectra obtained from each pixel of the whole tablet was used to predict the concentration of magnesium stearate. The quantitative accuracy of the prediction model by the second derivative spectra achieved R2 = 0.931 and RMSE = 1.90 %. Defective tablets were prepared with localised magnesium stearate. The skewness of the second derivative in the defective tablet was larger than that of the standard distribution. Specifically, the distribution of defective tablets was biased to the right as compared to the standard distribution. The results of the presented study suggest that spectral imaging combined with distribution analysis is an effective method to identify defective tablets.

In the present study we have developed a new version (ND-NIRs) of a polychromator-type near-infrared (NIR) spectrometer with a high-resolution photo diode array detector, which we built before (D-NIRs). The new version has four 5 W halogen lamps compared with the three lamps for the older version. The new version also has a condenser lens with a shorter focal point length. The increase in the number of the lamps and the shortening of the focal point of the condenser lens realize high signal-to-noise ratio and high-speed NIR imaging measurement. By using the ND-NIRs we carried out the in-line monitoring of pharmaceutical blending and determined an end point of the blending process. Moreover, to determinate a more accurate end point, a NIR image of the blending sample was acquired by means of a portable NIR imaging device based on ND-NIRs. The imaging result has demonstrated that the mixing time of 8 min is enough for homogeneous mixing. In this way the present study has demonstrated that ND-NIRs and the imaging system based on a ND-NIRs hold considerable promise for process analysis.