Measurement of Component Distribution in “Soft Chew” Formulations by ATR FTIR Imaging Ronald Rubinovitz and William Wihlborg Thermo Fisher Scientific, Lanham, Maryland

Overview Purpose: Use FTIR microscopy to determine the distribution of key components in “soft chew” formulations

Methods: FTIR microscopy enhanced with array detector and imaging ATR technique. Maps created using univariate and multivariate analysis from measured spectra.

Results: Imaging of key ingredients made possible with minimal measurement time and the elimination of “sample carry over”.

Introduction In this study, the benefits of attenuated total reflectance (ATR) imaging microscopy are applied to “soft chew” formulations in order to obtain distribution information related to their key components. This increasingly popular formulation type presents various sampling challenges for micro FTIR measurements by alternate sampling modes. Imaging in transmission mode is challenging since samples are difficult to cut thin enough and simply pressing them flat destroys the distribution information within the sample. Measuring these samples by reflectance mode tends to result in spectra of poor quality. The ATR measurement of a sample cross section offers a viable alternative since sample thickness is not an issue. However, as these sample formulations tend to be sticky and contain oil, the occurrence of “sample carry over” make single point ATR mapping problematic. Also, maps acquired by ATR typically require longer measurement times due to the time required to raise and lower the sample stage at each measurement point, thus dramatically reducing the potential speed that array detectors would normally make possible. However, the use of an imaging ATR accessory which makes contact with the sample just once while still permitting measurements across the sample surface removes these issues. In this manner, the utilization of an array detector enables the collection of thousands of spectra in relatively short time periods. Finally, germanium ATR microscope measurements offer the benefit of a four times magnification due to presence of germanium (refractive index=n=4) instead of air (n=1) at the sample interface, resulting in enhanced spatial resolution compared to non-ATR measurements. The distributions of active and other key components within these products are revealed in chemical maps. Results will show that strong spectral features are readily imaged by univariate methods, such as peak height, while weaker spectral features are detected and mapped by multivariate methods such as multivariate curve resolution.

Methods Spectra were measured using a Thermo Scientific™ iN™10 MX infrared imaging microscope (Figure 1), configured with both a single point MCT-A and a linear array MCT-A detector. Each sample cross section was cut to a size of approximately 5 x 5 x 2 mm (l x w x h) and was placed on the sample post of an imaging ATR microscope accessory (Figure 2) and raised to make contact with the germanium ATR crystal for measurement. Unless otherwise indicated, spectra were collected in “ultra-fast” mode where a single scan per step at 16 cm-1 resolution was collected at each map point and the spatial resolution was 6.25 microns. Maps of about 625 x 625 microns consisting of approximately 11,000 spectra were measured in approximately 1.5 minutes. Principal component analysis, multivariate curve resolution (MCR), and the creation of spectral maps were carried out using Thermo Scientific™ OMNIC™ Picta™ software.

This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others.

FIGURE 2. Thermo Scientific Imaging ATR accessory

FIGURE 1. Thermo Scientific iN10 MX Infrared Imaging microscope.

FIGURE 5. Comparison of maps of active component measured using an array (A) and single point detector (B)

FIGURE 7. Comparison of MCR components to IR library spectra.

Results

Antacid Product Component Distribution

Comparison of map spectra to library spectra of pure materials are shown in Figure 3. Maps of the active material (calcium carbonate), and two of the main non-active components, oil and corn syrup are shown in Figure 4, using peak heights at 872, 1746, and 1020 cm-1, respectively. It is clear that the active component is found primarily in the corn syrup regions. In Figure 5, the quality of the map is verified by comparing two maps measured with array and single point detectors, respectively. Each map shows the intensity of the calcium carbonate peak at 872 cm-1 and contains approximately 2000 spectra. The array map collected in just 18 seconds shows the same features of the single point detector map collected at 8 cm-1 resolution and 16 scans per spectrum that required about two hours to collect.

FIGURE 3. Map spectra compared to spectra of IR library

18 seconds 122 min

A B

FIGURE 4. Distribution of main components of antacid product Joint Health Supplement Component Distribution

Due to the low concentration of this product’s active, a multivariate curve resolution (MCR) analysis was performed which readily extracted the spectra of glucosamine and, as expected, oil and corn syrup. The resulting maps are shown in Figure 6. Comparisons of the MCR components of interest and the spectra of key components are shown in Figure 7. The minor presence of glucosamine in the measured spectra in demonstrated in Figure 8, where a map spectrum of mostly corn syrup is subtracted from a map spectrum of glucosamine and corn syrup, resulting in spectral features that compare well to the reference spectrum of glucosamine. Principal component reconstructed spectra were used for the subtraction.

FIGURE 6. Maps of components obtained with MCR Analysis.

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FIGURE 8. Spectral subtraction confirming the presence of glucosamine as found by MCR analysis.

Conclusion The use of an array detector and the elimination of the need to raise and lower the microscope stage at each measurement point allowed the acquisition of maps composed of thousands of spectra in just a few minutes at high spatial resolution. Also, maps were collected without sample “carry over” expected from typical ATR measurements of sticky and oily samples. Maps of sample components with relatively intense feature were easily created by straight-forward peak-height methods, while significantly weaker features were readily mapped by using MCR spectral processing. The combination of these techniques yielded maps illustrating the distribution of key components within these products.

Oil

Active

Corn Syrup

Oil

Active

Corn Syrup Oil

Active

Corn Syrup