The depth near-infrared (NIR) radiation penetrates into a sample during spectral acquisitions in NIR reflectance microscopy was investigated for pharmaceutical materials. Cellulose and its derivatives are widely used as excipients for pharmaceuticals and hence, were the basis for this study. The evaluation of the depth of sample contributing to the measured reflected radiation (information depth) was achieved using varying thicknesses of cellulose placed on top of a substrate. Analyzing the change in the absorption profile of the substrate showed the relationship between thickness and absorption to be exponential. The information depth was evaluated using the point where the substrate signal was reduced by 50%, termed the DP50 value. The DP50 value ranged from 39 to 61 μm at ∼1675 nm, but was found to have an exponential relationship with wavelength. Longer wavelengths had less penetration into the sample; at 2380 nm the DP50 was ∼27 μm but this increased to ∼180 μm at 1100 nm. The sample size was determined using the information depth and an approximate model for the contributing sample volume. Sample size was found to be within the range of 0.03–418 μg of sample per NIR spectrum depending on the wavelength used.
The pharmaceutical industry uses successfully both FT-NIR and Raman microscopy to produce chemical images of solid dosage forms, typically in troubleshooting roles. However, due to the chemical composition of the formulations, it is not always possible to describe the entire chemical formulation by using a single spectroscopic method. As Raman and NIR spectroscopies are complementary in nature, their combined usage offers the opportunity to describe heterogeneous mixtures in more detail. A novel sample referencing approach has been developed that allows data to be acquired from exactly the same area of the sample using both Raman and FT-NIR microscopies. The optimum images for the components are then overlaid, which gives rise to a combined chemical image that visually describes the entire formulation. We have named this approach chemical image fusion (CIF). CIF has been applied to two examples. The first shows how a simple formulation was used to validate the CIF approach. In the second, CIF allowed an entire formulation to be visualized and the cause of tabletting problems determined. CIF provides increased confidence in the results generated by each individual technique and offers a more powerful method for the evaluation of pharmaceutical formulations.
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