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.

This Perspective explains how the International Conference on Harmonisation's Guidelines on Validation of Analytical Procedures for quantitative methods can be met by near-infrared (NIR) assays of intact pharmaceutical products. Each of the validation characteristics (accuracy, precision, specificity, detection limit, quantification limit, linearity, range, robustness and system suitability testing) is defined, examined for their relevance to quantitative methods and examples given on how they may be used to demonstrate that near-infrared assays are fit for purpose. Methods for preparing samples for calibration are given in detail. The intention is to provide information so that a pharmaceutical manufacturer could validate a method suitable for an application for a variation of a marketing authorisation for an existing product and use a NIR assay instead of the previous method. The perspective is illustrated in detail using a NIR reflectance assay of paracetamol in intact tablets. This proven assay gives results comparable to the British Pharmacopeia ultraviolet assay for paracetamol, the standard errors of calibration and prediction for the NIR method being 0.48% w/w and 0.71% w/w respectively. The method is also precise, the standard deviation and coefficient of variation for six NIR assays on the same day being 0.14% w/w and 0.16% w/w respectively, while measurements over six consecutive days gave 0.31% w/w and 0.36% w/w respectively.

A number of powdered drugs and pharmaceutical excipients were used to demonstrate the ability of near-infrared spectroscopy to measure median particle size (d50). Sieved fractions and bulk samples of aspirin, anhydrous caffeine, paracetamol, lactose monohydrate and microcrystalline cellulose were particle sized by forward angle laser light scattering (FALLS) and scanned by fibre-optic probe FT-NIR spectroscopy. Two-wavenumber multiple linear regression (MLR) calibrations were produced using: NIR reflectance; absorbance and Kubelka-Munk function data with each of median particle size, reciprocal median particle size and the logarithm of median particle size. Best calibrations were obtained using reflectance data versus the logarithm of median particle size (NIR predicted lnd50 versus ln(FALLS d50) for microcrystalline cellulose and lactose monohydrate sieve fraction calibrations: r = 0.99 in each case). Working calibrations for lactose monohydrate (median particle size range: 19.2-183 microns) and microcrystalline cellulose (median particle size range: 24-406 microns) were set-up using combinations of machine sieve-fractions and bulk samples. This approach was found to produce more robust calibrations than just the use of sieved fractions. The method has been compared with single wavenumber quadratic least squares regression using reflectance and mean-corrected reflectance data with median particle size. Correlation between NIR predicted and FALLS values was significantly better using the MLR method.