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We have recently developed a novel portable NIR imaging device (D-NIRs), which has a high speed and high wavelength resolution. This NIR imaging approach has been developed by utilizing D-NIRs for studying the dissolution of a model tablet containing 20 % ascorbic acid (AsA) as an active pharmaceutical ingredient and 80 % hydroxypropyl methylcellulose, where the tablet is sealed by a special cell. Diffuse reflectance NIR spectra in the 1,000 to 1,600 nm region were measured during the dissolution of the tablet. A unique band at around 1,361 nm of AsA was identified by the second derivative spectra of tablet and used for AsA distribution NIR imaging. Two-dimensional change of AsA concentration of the tablet due to water penetration is clearly shown by using the band-based image at 1,361 nm in NIR spectra obtained with high speed. Moreover, it is significantly enhanced by using the intensity ratio of two bands at 1,361 and 1,354 nm corresponding to AsA and water absorption, respectively, showing the dissolution process. The imaging results suggest that the amount of AsA in the imaged area decreases with increasing water penetration. The proposed NIR imaging approach using the intensity of a specific band or the ratio of two bands combined with the developed portable NIR imaging instrument, is a potentially useful practical way to evaluate the tablet at every moment during dissolution and to monitor the concentration distribution of each drug component in the tablet.

In the fine chemicals industry, particularly in the pharmaceutical industry, advanced sensing technologies have recently begun being incorporated into the process line in order to improve safety and quality in accordance with process analytical technology. For estimating the quality of powders without preparation during drug formulation, near-infrared (NIR) spectroscopy has been considered the most promising sensing approach. In this study, we have developed a compact polychromator-type NIR spectrometer equipped with a photodiode (PD) array detector. This detector is consisting of 640 InGaAs-PD elements with 20-μm pitch. Some high-specification spectrometers, which use InGaAs-PD with 512 elements, have a wavelength resolution of about 1.56 nm when covering 900-1700 nm range. On the other hand, the newly developed detector, having the PD with one of the world's highest density, enables wavelength resolution of below 1.25 nm. Moreover, thanks to the combination with a highly integrated charge amplifier array circuit, measurement speed of the detector is higher by two orders than that of existing PD array detectors. The developed spectrometer is small (120 mm × 220 mm × 200 mm) and light (6 kg), and it contains various key devices including the high-density and high-sensitivity PD array detector, NIR technology, and spectroscopy technology for a spectroscopic analyzer that has the required detection mechanism and high sensitivity for powder measurement, as well as a high-speed measuring function for blenders. Moreover, we have evaluated the characteristics of the developed NIR spectrometer, and the measurement of powder samples confirmed that it has high functionality.

The feasibility of real-time release testing of bilayer tablets was investigated using near infrared (NIR) spectroscopy. The newly developed polychromator-type NIR spectrometer was used to compare the diffuse reflectance (DR) and transmittance (Tr) NIR spectroscopic techniques. This spectrometer not only performs highly sensitive NIR measurements but also yields the NIR spectra of an intact tablet on a millisecond (ms) timescale; i.e. 500 ms for the DR-NIR measurements and 400 ms for the Tr-NIR measurements. The bilayer tablets were prepared with the first layer comprising 0-10% ascorbic acid (AsA), 20% corn starch, 5% talc, 30% microcrystalline cellulose and 45-35% lactose, and the second layer comprising 20% corn starch, 5% talc, 30% microcrystalline cellulose and 45% lactose; their DRand Tr-NIR spectra were acquired from both sides of the tablet. With these spectra, the feasibility of DR-and Tr-NIR spectroscopy for the quantitative analysis of AsA in the bilayer tablets was compared. The DR-and Tr-NIR spectra of the bilayer tablets and their secondderivative spectra were studied. The AsA bands were not identified in the DR-and Tr-NIR spectra. However, the AsA bands at 995 nm and 1458 nm were observed in the second-derivative spectra. All the developed regression models predicted the AsA concentration, and regression vectors indicated that the prediction was based on the AsA bands. In addition, the model using the Tr-NIR spectra was able to predict the AsA concentration, even when the bilayer tablet was flipped.

An alternative baseline correction method for diffuse reflection near-infrared (NIR) spectra, searching region standard normal variate (SRSNV), was proposed. Standard normal variate (SNV) is an effective pretreatment method for baseline correction of diffuse reflection NIR spectra of powder and granular samples; however, its baseline correction performance depends on the NIR region used for SNV calculation. To search for an optimal NIR region for baseline correction using SNV, SRSNV employs moving window partial least squares regression (MWPLSR), and an optimal NIR region is identified based on the root mean square error (RMSE) of cross-validation of the partial least squares regression (PLSR) models with the first latent variable (LV). The performance of SRSNV was evaluated using diffuse reflection NIR spectra of mixture samples consisting of wheat flour and granular glucose (0-100% glucose at 5% intervals). From the obtained NIR spectra of the mixture in the 10 000-4000 cm(-1) region at 4 cm intervals (1501 spectral channels), a series of spectral windows consisting of 80 spectral channels was constructed, and then SNV spectra were calculated for each spectral window. Using these SNV spectra, a series of PLSR models with the first LV for glucose concentration was built. A plot of RMSE versus the spectral window position obtained using the PLSR models revealed that the 8680–8364 cm(-1) region was optimal for baseline correction using SNV. In the SNV spectra calculated using the 8680–8364 cm(-1) region (SRSNV spectra), a remarkable relative intensity change between a band due to wheat flour at 8500 cm(-1) and that due to glucose at 8364 cm(-1) was observed owing to successful baseline correction using SNV. A PLSR model with the first LV based on the SRSNV spectra yielded a determination coefficient (R2) of 0.999 and an RMSE of 0.70%, while a PLSR model with three LVs based on SNV spectra calculated in the full spectral region gave an R2 of 0.995 and an RMSE of 2.29%. Additional evaluation of SRSNV was carried out using diffuse reflection NIR spectra of marzipan and corn samples, and PLSR models based on SRSNV spectra showed good prediction results. These evaluation results indicate that SRSNV is effective in baseline correction of diffuse reflection NIR spectra and provides regression models with good prediction accuracy.