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APPLICATION NOTE

Chemical Characterization of
Pharmaceutical Samples by
Confocal Raman Microscopy
and Correlative Techniques

Chemical Characterization of Pharmaceutical Samples by Confocal Raman Microscopy
and Correlative Techniques
Introduction
Development, production and quality
control in the pharmaceutical industry
requires efficient and reliable control
mechanisms to ensure the safety and therapeutic effect of the final products. These
products can vary widely in composition
and application. Several of their properties
can be difficult to study with conventional techniques due to the inability ofthese methods to chemically differentiatematerials with sufficient spatial resolution
and without damage or staining. Therefore analyzing methods that provide bothcomprehensive chemical characterizationand the flexibility to adjust the method tothe investigated specimen are preferred inpharmaceutical research.
Confocal Raman Microscopy (CRM) is awell-established and widely-used spectroscopic method for the investigation of
the chemical composition of a sample. In
pharmaceutical research, CRM can be used
to probe the distribution of components
within formulations, to characterize thehomogeneity of pharmaceutical samples,
to determine the state of drug substances and excipients and to characterize
contaminants and foreign particulates [1].
The information obtained by CRM is also
useful for drug substance design, for thedevelopment of solid and liquid formulations, as a tool for process analytics andfor patent infringement and counterfeit
analysis [2, 3, 4]. Being a non-destructive
method it is possible to combine CRM withother imaging techniques such as Atomic
Force Microscopy (AFM), Scanning Electron
Microscopy (SEM) or fluorescence analysis.
The Aim of the Study
Based on various samples the article will
demonstrate how CRM can be beneficiallyapplied in the pharmaceutical field. Withhigh-resolution, large-area Raman images,

topographic 3D Raman images, depth-profiles and correlative Raman-AFM images
the analyzing capabilities of CRM andits correlative techniques will be shown.
Furthermore an example of a statisticalquantitative evaluation of a spectral Raman dataset will be given.
Materials & Methods
Confocal Optical Microscopy
The primary benefit of confocal microscopy is the suppression of light from outside
the focal plane. This is realized firstly by apoint illumination in the focal plane andsecondly by a pinhole in the conjugate
plane of the detection beam path.
Due to the point illumination and detection, only information from a single point isdetermined at a time. In order to generate
an image the sample is scanned point-bypoint and line-by-line.
The advantages of confocal microscopy
over conventional wide-field microscopy
are an improved resolution in the lateralplane, a high axial discriminatory power, a
reduced background signal and the ability
to collect optical sections in series fromdifferent focal planes to generate depth
profiles or 3D images.
Confocal Raman Microscopy
By combining a research-grade confocal
optical microscope with a high-sensitivity
Raman spectrometer, the resolution of the
optical microscope can complement theanalytical power of Raman spectroscopy.
Thus it is not only possible to obtain Raman spectra from extremely small sample
volumes, but also to collect high-resolution
Raman images that show the distributionof chemical species and crystallographic
properties with sub-µm resolution. The
sample is scanned point-by-point and lineby-line, and at every image pixel a complete Raman spectrum is acquired. This
process is called hyperspectral imaging.

These multi-spectrum files are then analyzed to display and image the distributionof chemical sample properties.
Atomic Force Microscopy
Atomic Force Microscopy (AFM) provides
topographic high-resolution information
by recording the interaction forces between the surface and a sharp tip mounted
on a cantilever. In addition, local material
properties such as adhesion or stiffness
can be investigated.
Combining CRM with AFM the high spatial
and topographical resolution obtainedwith an AFM can be directly linked to themolecular information provided by confocal Raman spectroscopy.
Topographic Confocal Raman Imaging
Although confocal Raman imaging is considered to be a non-destructive method
it is common to create a smooth andeven sample surface in order to keep thesurface in the focal plane while measuring in confocal Raman imaging mode.
However, this intervention can lead to themisinterpretation of the analytical results.
To avoid any sample preparation topographic confocal Raman imaging (TrueSurface
Microscopy, WITec GmbH, Germany) can beapplied. It is especially useful for samples
with rough or inclined surfaces. The highly
precise sensor scans the topography of thesample. The topographic coordinates areused to trace the sample‘s surface in confocal Raman imaging mode to ensure that
the Raman laser is always kept in focus.
The result is a confocal Raman image thatcan be overlaid on the topographic image
and visualized three dimensionally.
Experimental Setup
A confocal Raman microscope (alpha300
R, WITec GmbH) was used to study thechemical composition of various pharmaceutical samples. The laser light is guided
to the microscope through an opticalfiber. It can be focused to a diffraction-limited spot and therefore acts as a point
light source. This light is focused onto thesample using a dichroic beam splitter thatreflects the exciting laser beam, but isfully transparent for the frequency-shifted
Raman light. The sample is scanned with apiezo-electric scanning table with capacitive feedback correction for high resolution.
The Raman scattered light is collectedwith the same objective and is focused
into the core of another optical fiber thatis connected to a spectrometer. The light isdispersed inside the spectrometer and thespectra are acquired with an ultra-sensiti-a)ve, back-illuminated CCD camera.
Results & Discussion
High-Resolution, Large-Area Confocal
Raman Imaging, Volume Scans and 3D
Visualizations
In the first example a pharmaceuticalemulsion was investigated. The active
pharmaceutical ingredient (API) was
dissolved in water. In figure 1a a large-area,
high-resolution Raman image of the emulsion is shown. The image scan range is 180
x 180 µm2 with 2048 x 2048 pixels. At each
image pixel a complete Raman spectrum

was acquired, therefore the large imageis the result of an evaluation of 4,194,304
Raman spectra. The integration time perspectrum was 2 ms and the raw data filesize is 12.5 GB. The consecutive zoom-in
images (figure 1b and 1c) of the same dataset illustrate the extremely high-resolutionof the large-area scan shown in figure 1a.
The Raman data were acquired, evaluated and processed with the Project FOUR
Software (WITec GmbH, Germany). In the
resulting color-coded images the waterand API-containing phase is presented inblue, whereas with green the oil-matrix is
displayed. In addition to the distribution ofb)c)Figure 1: a) Large-area, high-resolution confocal Raman image of a pharmaceutical emulsion. Scan range: 180 µm x 180 µm; 2048 x 2048 pixels =4,194,304 Raman spectra; raw data file size: 12.5 GB. Blue: active pharmaceutical ingredient; green: oil; red: silicon impurities. b) and c) consecutive
zoom-in images of the same dataset.

the known materials, silicon-based impurities could be visualized (red in the images).
Volume scans are a valuable tool for providing information about the dimensionsof objects or the distribution of a certain
compound throughout the sample. The
generation of volume scans and 3D images
always requires large data sizes. In orderto generate 3D images, confocal 2D Raman
images of parallel focal planes are acquired by scanning throughout the sample
in the z-direction. The 2D images are then
combined into a 3D image stack.
To investigate the volume of the impuritiesof the emulsion from figure 1a in moredetail, a 3D scan was performed. For that a
volume of 25 x 25 x 20 μm3 was analyzed
with 200 x 200 x 50 pixels. At each image
pixel a complete Raman spectra with 10
ms integration time per spectrum was
acquired. The image stack contains theinformation of a total of 2 million Raman
spectra and is based on a raw data file sizeof 6 GB (figure 2).

Figure 2: Confocal 3D Raman
volume image. The green oil ispartially removed in the image
to facilitate a better identification of the red impurities. Scan
range: 25 x 25 x 20 μm3, 200 x
200 x 50 pixels = 2,000,000
Raman spectra, integration
time per spectrum: 10 ms, data
file size: 6 GB.

a)

In the following an example emulsion wasstudied. Therefore carbon tetrachloride(CCl4) was mixed with an alkane, waterand oil. A high-resolution 3D Raman imageof the emulsion was acquired (figure 3).
It shows the three-dimensional distribution of the components and reveals CCl4
dissolved in the oil phase.

b)
Figure 3: Confocal, high-resolution Raman microscopy of an emulsion of CCl4, alkane, water andoil. a) Three-dimensional confocal color-coded Raman image of the emulsion; alkane: green, water:
blue, CCl4 + oil: yellow. Image parameters: 200 x 200 x 20 pixels; scan area: 100 x 100 x 10 µm3; integration time per spectrum: 0.06 s; excitation laser wavelength: 532 nm. b) corresponding Raman
spectra.

Topographic Raman Imaging
A pharmaceutical tablet with heightvariations of 300 µm on the surface
was investigated. Therefore topographic
confocal Raman imaging was applied [5,6]. Figure 4a shows the resulting heightprofile of the pharmaceutical tablet. The
color code displays the varying heights.
Following the sample’s topography duringconfocal Raman image generation keeps

the sample’s surface in focus over theentire scanned area without any Raman
signal decrease. The resulting confocal
Raman image reveals the distribution of
the sample’s components three dimensionally. Figure 4b shows the height profile
with the chemical information from theconfocal Raman measurement overlaid.
The drugs are labeled red and blue respectively, while the excipient is shown ingreen. In this way the generated 3D Raman
image provides the full information about
the chemical composition and additionallycombines topographic and spatial sample
characteristics. Figure 5 shows the resultsof the same method applied to study the
distribution of the protein conformationof a highly structured lyophilisate section(for more information please refer to theimage caption).

Figure 4: a) Height profile of a pharmaceutical tablet scanned with TrueSurface. The color code displays the varying heights. Topographic variation ismore than 300 µm. b) Topographic profile from a) overlaid with the confocal Raman image. The drugs are labeled red and blue, while the excipient isshown in green.

d)

b)

a)

c)

Figure 5: Investigation of the protein conformation of a highly structured lyophilisate section. (a) Lyophilisate image visualizing thehighly structured surface. (b) Surface topography profile of a lyophilisate section acquired with TrueSurface® Microscopy. (c) Plain confocal Raman image of the investigated area. (d) Overlay of the topography profile with the corresponding confocal Raman image. The
resulting three dimensional, color coded image indicates the native protein conformation in blue and the denatured protein conformation in red. Scale bars: 400 μm.

Raman Depth Profiling & AFM of a Drug
Delivery Coating
For the characterization of drug delivery
coatings, nondestructive confocal Raman
imaging provides the ability to analyze
the chemical composition and spatial
distribution of the material within thecoating. Due to the confocal principle eventhe thickness of these coatings can bemeasured. In figure 6a the spectral Raman
image of a drug-eluting coating on top ofa stent is shown. In this case the confocal
Raman microscope was used to perform adepth scan along the x-z axis through thecoating. As a result the chemical composition of the pharmaceutical sample aswell as the distribution of each individual chemical compound can be spatially
distinguished and displayed. In addition
to Raman imaging the microscope allows
AFM analysis. The obtained AFM image
shows the drug distribution on top of thepolymer substrate structure of the stent(figure 6b). The high-resolution AFM image
provides a precise topographic description
and provides additional information about
the surface properties [7].
Ultrafast Confocal Raman Imaging
With the Ultrafast Confocal Raman Imaging option the acquisition time for a single Raman spectrum can be as low as 760
microseconds and 1300 Raman spectra
can be acquired per minute. As a confocal
Raman image typically consists of tens of
thousands of spectra, the option reduces
the total acquisition time for a complete
image to only a few minutes. For example,
a complete hyperspectral image consistingof 250 x 250 pixels = 62,500 Raman spectra can be recorded in less than a minute.
The latest spectroscopic EMCCD detector
technology combined with the highthroughput optics of a confocal Raman
imaging system are the keys to this improvement, which can also be advantageouswhen performing measurements on delicate and precious samples requiring thelowest possible levels of excitation

Figure 6: a) Confocal Raman image (depth scan x-z) of a drug-eluting stent. The drug-eluting
coating (drug: green, polymer: red) on top can be distinguished from the substrate polymer layer(blue). B) High-resolution AFM surface topography of a drug-eluting stent surface showing thepolymer substrate structure with the embedded drug particles.

a)Figure 7: a) Raman image of toothpaste.
Scan range: 60 x 60 μm2, 200 x 200 pixels,
40,000 spectra, 760 microseconds/spectrum, 42 seconds/image. b) Zoom-in of
the marked area in Fig 5a, scan range 20 x
20 μm2, 200 x 200 spectra, 40,000 spectra,
acquisition time: 0.76 ms/spectrum,
40 s/image. c) Corresponding Raman
spectra.

b)c)power. Time-resolved investigations ofdynamic processes can also benefit fromthe ultrafast spectral acquisition times. A
standard, commercially available toothpaste was imaged using the Ultrafast
Confocal Raman Imaging option. The scan
range was 60 x 60 μm2 and 20 x 20 μm2
respectively at 200 x 200 pixels (40,000
Raman spectra). The acquisition time fora single spectrum was 760 microseconds,
resulting in 42 seconds for the complete
image. The Raman images in figure 7a and7b show the distribution of the toothpaste’s main compounds. Figure 7c shows thecorresponding spectra.

Statistical Analysis - Dexpanthenol Ointment
For further detailed analysis of the distribution of a sample’s chemical components
it is useful to apply statistical methods.
Cluster analysis is a typical example of astatistical evaluation method with which
spectral characteristics can be extracted,
classified and imaged. Furthermore histograms can serve as effective visualization
tools to quantitatively evaluate spectral
datasets.
In the following example two dexpanthenol ointments for different areas of topicalapplication (eye and skin) were analyzed.
Alkane, oil and water were identified as theprimary components of both ointmentsby confocal Raman microscopy (figure8a). However, the confocal Raman images
clearly show that the components occur indifferent concentrations in the ointments(figures 8b and 8c).
For further validation and a more detailed
quantitative examination a histogram
analysis was performed. The intensity ofthe detector counts was plotted against
the number of pixels. Hence, the frequencyof the appearance of a component (pixels)
relative to its intensity (detector counts)

Figure 8: a) Example Raman spectra of the main components of two dexpanthenol-containing ointments for different areas of topical application.
b) and c) corresponding confocal Raman images of the ointments (alkane red, oil green, water blue; 25 µm x 25 µm, 150 x 150 pixels = 22,500 spectra,
0.05 s integration time/spectrum, 532 nm excitation wavelength, 25 mW laser power).

Figure 9: Histogram analysis of the intensity distributions of the main components (alkane, oil,water) relative to the area of topical application (eye in purple; skin in cyan) of two dexpanthenol
ointments. The intensity of the detector counts (abscissa) is plotted against the number of pixels(ordinate).

is displayed. Figure 9 shows the resulting
histograms of the two dexpanthenol
ointments for the appearance of the main
components: alkane, oil and water.
The histogram analysis reveals that thecomponents’ mixture differs between
the ointments depending on their areasof topical application. The eye ointment
contains less oil, but on average morewater. With statistical analysis of spectral
datasets, pharmacists in research anddevelopment can gain insight into the chemical composition of a product and obtainsignificant information to improve therequired pharmaceutical characteristics.

Conclusion
In pharmaceutical development it is ofgreat importance to acquire information
on drug composition and distributionof chemical components. With confocal
Raman images the distribution of the chemical components in diverse drug systems
can be clearly visualized. Combining CRM
with other techniques such as topographic Raman imaging and AFM expands
its analyzing capabilities. Thus, a variety
of different pharmaceutical samples canbe investigated and the chemical information from spectral Raman analyses
can be linked to topographic data andfurther surface characteristics. CRM and its
correlative analyzing methods contributeto a comprehensive understanding of apharmaceutical product and facilitate its
development.
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Reviews. 2015;89.
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[3] Wormuth, K. Characterization of Therapeutic Coatings on Medical Devices. Vol.
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Sciences; 2010.
[4] Franzen, L.; Selzer, D.; Fluhr, J.W.; Schaefer, U.F.; Windbergs, M. Towards drug
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