Near-infrared spectral imaging for quality assurance of pharmaceutical products: Analysis of tablets to assess powder blend homogeneity

Abstract

The objective of this study was to evaluate near-infrared (NIR) spectroscopic imaging as a tool to assess a pharmaceutical quality assurance problem--blend uniformity in the final dosage product. A system based on array detector technology was used to rapidly collect high-contrast NIR images of furosemide tablets. By varying the mixing, 5 grades of experimental tablets containing the same amount of furosemide and microcrystalline cellulose were produced, ranging from well blended to unblended. For comparison, these tablets were also analyzed by traditional NIR spectroscopy, and both approaches were used to evaluate drug product homogeneity. NIR spectral imaging was capable of clearly differentiating between each grade of blending, both qualitatively and quantitatively. The spatial distribution of the components was based on the variation or contrast in pixel intensity, which is due to the NIR spectral contribution to each pixel. The chemical nature of each pixel could be identified by the localized spectrum associated with each pixel. Both univariate and partial least squares (PLS) images were evaluated. In the suboptimal blends, the regions of heterogeneity were obvious by visual inspection of the images. A quantitative measure of blending was determined by calculating the standard deviation of the distribution of pixel intensities in the PLS score images. The percent standard deviation increased progressively from 11% to 240% from well blended to unblended tablets. The NIR spectral imaging system provides a rapid approach for acquiring spatial and spectral information on pharmaceuticals. The technique has potential for a variety of applications in product quality assurance and could affect the control of manufacturing processes.

Recent applications of Chemical Imaging to pharmaceutical process monitoring and quality control

“…Future innovations in CI equipment manufacture are likely to depress purchase costs and encourage more widespread utilisation of this emerging technology in the pharmaceutical sector. Compositional information [28], [29] Quality assessment [20], [30] Process related information [31], [32] Blend uniformity [33], [34] Coating thickness [35] Counterfeit drug detection [36], [37] Remote identification [38], [41] Staring imager High throughput analysis [38], [39] [22], [49] Tablet characterisation [17], [29], [50], [51], [52], [53], […”

“…Lyon et al published a paper in 2002 [33] comparing the ability of NIR-CI and NIRS in distinguishing blending grade for a selection of final dosage forms. Individual tablets with different blending grades were imaged at 71 wavelengths from 1000-1700 nm using a staring imager configuration Chemical Imaging system.…”

Hyperspectral Sensing Techniques Applied to Bio-masses Characterization: The Olive Husk Case

“…The "pushbroom" [18] configuration is based on the acquisition of simultaneous spectral measurements from a series of adjacent spatial positions, this requires relative movement between the object and the detector. Some devices produce hyperspectral images based on a point step and acquire mode: spectra are obtained at single points on a sample, then the sample is moved and another spectrum taken.…”

A quantitative method using near infrared imaging spectroscopy for determination of surface composition of tablet dosage forms: an example of spirolactone tablets

“…[12][13][14][15][16][17][18] In a review of the literature, it is possible to find that the principal method used to develop calibration models using imaging NIR data is the single wavelength approach, in which the intensity of a single wavelength is related to the concentration of a specific compound. 14,17,[19][20][21][22][23] It is obvious that the wavelength must be selective for the compound to be quantified, turning this a risky strategy. The principal multivariate method used to analyze NIR imaging data is the principal component analysis (PCA), however, PCA cannot be directly used as a prediction method for concentraion.…”

“…32,36,37 For quantification, most of works present PLS models built using pure spectra and do not take into account possible spectral changes due to interactions of the compounds. 14,15,19,26,[38][39][40][41] PLS is employed in few works to quantify compounds by NIR imaging using a calibration set, 18,[42][43][44] and none of them presented interval PLS (iPLS) to calculate concentration maps (chemical images) in tablets.…”