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Raman Spectroscopy

Author Olivier Savard PerkinElmer, Inc. Shelton, CT 06484 USA

IdentiCheck Raman Spectrometer for the Most Demanding Incoming Raw Material Testing


Due to increased pressure on pharmaceutical companies by both consumers and legislation to be able to show clear traceability of their products (including full identification of all raw materials used) new identification methods are required. Raman spectroscopy is a very attractive technique for pharmaceutical companies, because it provides a fast and easy way to run a large number of extra analyses with high reliability of results, while at the same time keeping tight control over the cost of analysis.1

Since most pharmaceutical companies utilize a wide variety of materials, the instrument used for material identification will need to have the capability to identify as many as possible. Material with similar chemical structure or composition (polymorphs, excipients, waxes, etc.), exhibiting low residual fluorescence, or with low scattering properties could be very challenging to analyze using a low performance Raman spectrometer. Furthermore, to avoid contamination of the materials, reduce exposure hazard to employees and to keep the time and cost of analysis to a minimum, most samples should be analyzed through their original packaging. However minimizing sample removal or sample preparation, makes the identification task even harder, while making the overall procedure for the company safer and economically more advantageous. This field application report shows the importance and advantages of using a high performance Raman spectrometer like the PerkinElmer® Raman IdentiCheckTM when analyzing a wide variety of samples in such demanding circumstances.

What is a considered a difficult sample in Raman spectroscopy?

Two materials with similar molecular structures could produce Raman spectrum without noticeable differences. To differentiate common pharmaceutical excipients such as calcium and magnesium stearate is a good example. Polymorphic compounds (which are the same chemical formula and structure but different crystalline structure) are another good example of materials that are difficult to differentiate. The differences in the crystalline structure of these polymorphs can affect the physicochemical parameters of the substance such as solubility, dissolution rate, density, hardness and shape. This in turn can impact on important pharmaceutical properties of these polymorphs such as bioavailability and stability of a drug as well as the formulation technology of the dosage form. Therefore it is very important to perform a full identification.2 As a final example of challenging materials we can mention those that exhibit fluorescence. The fluorescence produced by these materials could lead to a baseline slope and saturate the instrument detector. A good example is ranitide HCl which is discussed in more detail below.


Case 1. Samples with problems of Fluorescence Material exhibiting a low to medium level of fluorescence will cause a sloping baseline* in the lower wavenumber region (Figure 2, red spectrum, as recorded; blue spectrum after baseline correction). If a good signal to noise ratio is obtained, a baseline shift like this will not significantly change the information contained in the spectra, but could be harder to interpret and could lead to misleading results when compared with commercial libraries or fluorescencefree standards. Note: Materials were identified by comparing their spectra with a customer database. The correlation limit was set to 0.98 to be considered a good match (PASS criteria). The software controlling the IdentiCheck (SpectrumTM 10; Spectrum Insight or AssureIDTM) can be programmed to automatically apply a baseline correction to the spectra.


To demonstrate the importance of using a high performance Raman spectrometer for incoming raw material identification, samples commonly used in the pharmaceutical industry were analyzed. It is often considered a challenge to reliably identify such samples with a handheld Raman spectrometer. The samples provided are commonly used APIs and excipients that were provided by major pharmaceutical companies. The samples were analyzed through their plastic bag to replicate procedures followed by the pharmaceutical industry.

Figure 2. Amoxicillin trihydrate spectrum obtained with two five second scans before (red) and after (blue) automatic baseline correction.

For highly fluorescence materials such as minocycline HCl which show too much fluorescence for a standard acquisition, thirty seconds of photobleaching was used prior to the spectrum acquisition to remove some of the fluorescence effect (see Figure 3). Without photobleaching, fluorescence would saturate the detector and prevent any measurement.3

Figure 1. PerkinElmer Raman IdentiCheck. Figure 3. Baseline corrected minocycline HCl spectrum obtained with thirty seconds photobleaching and two five second scans.

* This effect should not be mistaken for the vignetting effect present on low quality, low resolution microspectrometers; Vignetting is a loss on light intensity at the periphery of the image compared to its center. It is a quite common effect in spectroscopy but especially significant in MEMS (Micro-Electro-Mechanical Systems) spectrometers. Low performance Raman instruments based on MEMS technology have regularly this baseline sloping effect. 2

Case 2. Providing a unique and unambiguous identification of materials Most Raman handheld devices use complex algorithms for sample identification to compensate for their lower performance. The high performance of a PerkinElmer Raman IdentiCheck provides high quality spectra in a short time. The high quality spectra, combined with the information rich Raman spectroscopy allows the use of a simple CoMPARETM algorithm for identification purposes.4 In this section, three replicas of each sample were obtained. Each spectrum was obtained with two five second scans. A spectrum of each sample was then identified using the CoMPARE algorithm. In this example, the correlation threshold for positive identification was set to 0.98. In these examples, materials exhibiting too much fluorescence to be reliably identified by Raman handheld devices were nevertheless recognized using the PerkinElmer Raman Identicheck.

Figure 6. Baseline corrected ranitide HCl spectrum obtained with two five seconds scans.

Case 3. Identification of excipients The high sensitivity and high resolution of the IdentiCheck allow the identification of materials that have similar Raman spectra. Magnesium stearate and calcium stearate are good examples of materials that are very alike both chemically and spectroscopically. Their Raman spectra contain the same peaks since they contain the same functional groups and similar structure and could be very hard to differentiate without a high performance Raman instrument. The only difference is a slight shift in peak position. Magnesium stearate from a different source (I and II) and calcium stearate were analyzed to show the capability of the IdentiCheck to differentiate them. A close-up to the 2850 cm-1 region (Figure 8) and 1450 cm-1 region (Figure 9) shows the differences between magnesium and calcium stearate. In these two regions of interest, a shift of less than 3 cm-1 can be observed (Figures 8 and 9). No changes (shift) were observed between the two samples of magnesium stearate.

Figure 4. Baseline corrected azithromycin spectrum obtained with two five second scans.

Figure 5. Baseline corrected doxycyline hydrate spectrum obtained with two five second scans.

Figure 7. Magnesium stearate (I and II) and calcium stearate full range spectra.


Case 4. Identification of waxes Three waxes (Ceteareth-15, Ceteareth-20 and Ceteareth-30), that only differ in the length of their backbone (15, 20 and 30 carbons), were analyzed to show that a high performance Raman instrument can easily differentiate between these three similar materials. In this case, the only observed spectral variations are the peak intensities. With its calibrated and reproducible signal intensity, the PerkinElmer Raman IdentiCheck is the perfect instrument to differentiate between these types of samples. Since their molecular structures are very similar, it is hard to find any differences between these spectra. Figure 10 shows a close-up of the region where most of the differences are to be found. There is no peak shift, but a change of peak ratio depending on the carbon chain length contained in the wax. These peak ratios are more noticeable in the region of 1125 cm-1 and 1300 cm-1.

Figure 8. Magnesium stearate (I and II) and calcium stearate differences in the 2875 cm-1 region.

Figure 9. Magnesium stearate (I and II) and calcium stearate differences in the 1450 cm-1 region.

Finally, the three samples were correctly identified using the CoMPARE algorithm (Table 1 and 2) Table 1. Compare results for Calcium Stearate. Name(ID) Calcium Stearate Magnesium Stearate Correlation 0.999275 0.954975 pass / Fail Pass Fail

Figure 10. Changes in peak ratio observed in the 1300 cm-1 due to different backbone length of Ceteareth-15 (red), Ceteareth-20 (blue) and Ceteareth-30 (green).


The high performance PerkinElmer Raman IdentiCheck allows fast and simple identification of incoming raw material due to its high signal/noise, high resolution at full range and high sensitivity. Materials that exhibit low to medium fluorescence can easily be identified by reducing the exposure time due to the high sensitivity and great signal/noise of the IdentiCheck. Sloping baselines due to fluorescence can automatically be corrected with the software to provide even more reproducible results. Use of the photobleaching technique is also available for samples that exhibit too much fluorescence for standard Raman measurement. Samples that have similar molecular structure such as magnesium stearate and calcium stearate or waxes that only differ in their backbone chain length, can easily be identified with the IdentiCheck.

Table 2. Compare results for magnesium Stearate. Name(ID) Magnesium Stearate Calcium Stearate Correlation 0.999246 0.953768 pass / Fail Pass Fail



1. PerkinElmer Application Note, The Raman IdentiCheck in the Pharmaceutical and Healthcare QC/QA Environments. 008238A_03 2. R. Alexander, PerkinElmer Application Note, Raman Analysis of a Polymorph Within a Polymorph (2007). 007998_01 3. A. Dennis, PerkinElmer Technical Note, Photo-Bleaching and Automatic Baseline Correction for Raman (2007). 007927_01 4. PerkinElmer Application Note, Verification of Material Using Spectrum Compare (2002). D-5663B

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IdentiCheck Raman Spectrometer for the Most Demanding Incoming Raw Material Testing

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