Article

Raman mapping to visualise the three-dimensional structure of pharmaceutical tablets

By Andrew Ewing (Pfizer), Don Clark (Pfizer), Fiona Clarke (Pfizer)

22 December 2022

Raman mapping is a powerful tool that can be used to reveal details about the size and spatial arrangement of components throughout a tablet matrix. Here, Andrew Ewing, Don Clark and Fiona Clarke from the Materials Characterisation Team at Pfizer present a 3D imaging approach using Raman mapping to investigate pharmaceutical tablets.

The use of vibrational spectroscopy, including raman mapping, to study pharmaceutical products has been widely applied across the industry for several decades.¹ Conventional vibrational spectroscopic approaches, namely Raman spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and near infrared (NIR) spectroscopy, are integral to providing chemical information about samples. The techniques reveal chemically specific information derived from vibrations within the molecules. These techniques can be utilised to understand polymorphs, intra- and inter-molecular interactions and solid form changes within pharmaceutical products. This knowledge can greatly impact formulation development and be used for troubleshooting applications.

Spectroscopic imaging and mapping offer label-free approaches to probe pharmaceutical tablets and visualise the identity of their components, spatial distributions, domain sizes and shapes”

The advent of spectroscopic, or chemical, mapping and imaging allows the spatial distribution of different components to be revealed by measuring the spectra within different areas of a sample. These spectroscopic imaging approaches have been employed in a range of pharmaceutical applications.^2-7 The terms spectroscopic imaging and mapping are often used interchangeably in the literature: mapping acquires discrete spectra from single points via raster scanning across a sample on a movable stage; whereas, imaging acquires spectra in two spatial dimensions using an array detector. Chemical images are generated by plotting the absorbance of specific spectral bands across the measured area. Spectroscopic imaging and mapping offer label-free approaches to probe pharmaceutical tablets and visualise the identity of their components, spatial distributions, domain sizes and shapes.

The term ‘chemical imaging’ typically refers to spectra acquired from a two-dimensional (2D) array of a sample. A potential caveat of these methods is the assumption that the data acquired is representative of the sample bulk. However, it should be acknowledged that this is not always the case. A hypothetical system comprising spherical and cubic components can be used as an example.⁸ The point at which the sample is sliced (ie, cross‑sectioned) will affect the visualised diameter of the spherical component. Therefore, it is possible that the calculated diameter of the sphere will be underestimated. On the other hand, the cubic domains can result in over estimations of their domain sizes if they are sliced across one, or more, of their faces.

A pharmaceutical tablet is a 3D sample that comprises a mixture of components in which some are arranged as a network of agglomerated particles….2D imaging and mapping approaches may not provide a true representation of these networks throughout a tablet matrix”

A 2D chemical image probes a single layer of the sample, which is not always representative of the whole sample, particularly for 3D objects. A pharmaceutical tablet is a 3D sample that comprises a mixture of components in which some are arranged as a network of agglomerated particles. Processing of a blend (eg, granulation) and subsequent tableting can cause the powdered ingredients of a tablet to agglomerate. Therefore, 2D imaging and mapping approaches may not provide a true representation of these networks throughout a tablet matrix. It is widely accepted that the distribution of components throughout a tablet is important to ensure that reliable quality medicines are produced. Revealing information about this distribution can help to understand the effects of parameters like processing conditions during manufacturing processes. It would also provide opportunities to profile tablets that can be used as a baseline against subsequent batches produced, or for troubleshooting issue samples.

This article summarises some recent developments from the Materials Characterisation Team at Pfizer (Sandwich, UK) that has demonstrated a 3D imaging approach using Raman mapping to investigate pharmaceutical tablets.

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This research has built upon 2D Raman mapping and overcome the limitations discussed above, by combining 2D images taken at regular voxel depths to construct a 3D image as a volumetric dataset (see Figure 1). This has facilitated the understanding of formulation development by revealing knowledge about the size and spatial arrangement of components throughout a tablet matrix, and forming links with product attributes and performance.

Figure 1. A schematic representation of the 3D chemical image reconstruction process.Reproduced from Ref. 11 with permission of John Wiley and Sons.

Three-dimensional Raman mapping of pharmaceutical tablets

We compared the capabilities of NIR and Raman mapping approaches to assess which technique gave the desired attributes for visualising components within tablets.⁹ A model pharmaceutical system was studied that comprised of three chemically and elementally different components: eletriptan hydrobromide, microcrystalline cellulose (MCC) and saccharin loaded in equal weight ratios. This allowed scanning electron microscopy (SEM) with energy dispersive X-ray (EDX) analysis to be used as a further imaging technique to support the chemical imaging results.

Comparison of chemical images acquired from NIR and Raman mapping showed that the domains for each component were larger and less well defined in the NIR chemical images”

The tablet samples were glued to chemical image fusion slides, which ensured that the same area was examined when acquiring data from the different techniques.¹⁰ Comparison of chemical images acquired from NIR and Raman mapping showed that the domains for each component were larger and less well defined in the NIR chemical images. One potential explanation for this is related to the raster step size of the two approaches, where 25µm was the highest achievable resolution when using the NIR mapping system. In contrast, a 10µm step size was used to collect the Raman maps. The larger spatial resolution in the NIR chemical maps could lead to pixels containing more than one component, thus overestimating their distribution, or components with particle sizes less than 25µm may be underestimated. This highlights one of the challenges of NIR chemical imaging for a sample containing a mixture of strong and weak NIR absorbers. The greater penetration depth of the NIR radiation can potentially lead to an overestimation of strongly absorbing NIR components, even when they are underneath the measured surface. However, it should be noted that the total scanning acquisition time for a 3mm × 3mm area of the tablet was about 3.5 hours for the Raman setup but only about 13 minutes for the NIR measurement. The longer acquisition times required for Raman mapping experiments make it unsuitable for all samples, particularly dynamic specimens or investigations that require rapid analysis of many samples.

Figure 2

Raman (left), NIR (centre) and EDX (right) maps, where blue = MCC, green = saccharin and red = eletriptan HBr.

Reproduced from Ref. 9 with permission of Sage Publishing.

Furthermore, when SEM-EDX images were compared to further inspect the tablet, it was observed that the Raman and EDX maps were more consistent with each in revealing the spatial distribution of components (see Figure 2). The most significant differences between the images were the size and shapes of the domains of the different components. Quantitative domain size and distribution statistics were generated from the acquired chemical images. In general, the Raman and EDX map statistics were more comparable to each other than the NIR chemical images. Interestingly the general domain sizes of the components differed to that of the input raw materials. This suggested that blending and compaction of the formulation changed the physical properties of the powder mixture. For example, the domain statistics from MCC indicated that it formed an agglomerated network, while saccharin fractured into smaller particles.

The study demonstrated some of the key differences in the capabilities of Raman and NIR chemical mapping for pharmaceutical analysis”

The study demonstrated some of the key differences in the capabilities of Raman and NIR chemical mapping for pharmaceutical analysis. The detailed qualitative and quantitative assessment of the chemical images revealed that different spatial distributions of components, domain sizes and shapes were identified within the same measured area. The Raman map resulted in a higher spatial resolution image with discrete domains of the individual components. In contrast, the NIR mapping image was dominated by large, pixelated domains of the strong NIR‑absorbing components, MCC and saccharin. This suggested that Raman mapping would be the preferred chemical imaging approach for providing information about the domain sizes and shapes of all components. Therefore, it was selected for subsequent studies to demonstrate the feasibility of 3D chemical imaging of pharmaceutical tablets.

Carruthers et al reported a novel approach that manually serial sectioned a model spherical bead system and pharmaceutical tablets, then recombined the series of 2D chemical images into 3D data cubes.¹¹ AmberLite™ beads embedded in a microcrystalline cellulose matrix were used to validate the proposed 3D imaging method. This model system was selected because the spherical beads were of known size, and objects of this shape are difficult to characterise using chemical mapping approaches. The obtained qualitative and quantitative data from the 3D visualisation method, conducted using FIJI 3D viewer, produced data within an acceptable error range.¹² The limitations and error derive from overestimation of the components’ distribution due to irregularly shaped boundaries but are inherently systemic of the method.

Figure 3

(a) 3D volumetric representation of the distribution of MCC (blue), saccharin (green) and eletriptan hydrobromide (red), (b) with MCC removed to see minor components, (c) shows a 3D orthoslice representation of the distribution of MCC (blue), saccharin (green) and eletriptan hydrobromide (red), and (d) shows a 3D scatterplot of the geometric centres of eletriptan hydrobromide and saccharin domains. Adapted and reproduced from Ref. 11 with permission of John Wiley and Sons.

In general, the domain shapes within pharmaceutical tablets are likely to be irregular and so are easier to characterise when using Raman mapping. This study further demonstrated the 3D Raman mapping method to assess the number, average volume and surface area of the components in a three-material tablet formulation. It was proposed that the quantitative values would be powerful as a comparative tool to reveal differences about the size and distribution of component domains between different samples. This could highlight: variances or similarities between samples from different batches; the effect of processing and compaction conditions; and aid identification of issue tablets. As shown in Figure 3, the reconstructed 3D data cube could be visualised as a volumetric representation or as an orthoslice. This demonstrates a few of the complementary representations of the data that provides information about distributions of components of interest.

A recently published article detailed the workflow of the data processing methods required to quantitatively examine 3D vibrational spectroscopic data for understanding the domain size and distributions of multicomponent systems.¹³ This paper summarised the application, from a pharmaceutical perspective, of the 3D Raman mapping approach as a tool for enhanced tablet manufacturing and drug product understanding. In addition to the size and shapes of the separate domains, a calculation of the relative position of components within the samples was also quantified, to inform on the contact surface area between the materials throughout the matrix. Such analysis can provide enhanced understanding of a tablet’s 3D microstructure, which can afford greater final product insight.

Future opportunities for vibrational spectroscopic chemical imaging

The major limitation of the 3D Raman mapping approach discussed above is the fact that high‑quality 2D maps require long acquisition times. Furthermore, physical serial-sectioning of the tablet requires it to be removed from the Raman system, sliced, then realigned to the same coordinate position before the next 2D map can be measured. Thus, novel rapid imaging approaches are of interest to further advance 3D chemical imaging capabilities.

Advancements in commercially available imaging techniques that utilise quantum cascade laser (QCL) technology have opened up new opportunities for infrared spectroscopic imaging”

Advancements in commercially available imaging techniques that utilise quantum cascade laser (QCL) technology have opened up new opportunities for infrared spectroscopic imaging.^14,15 The possibility to acquire spectral data from selected, discrete wavelengths significantly reduces the data acquisition time. A recent study assessed the application of a laser-direct infrared (LDIR) mapping system against other established imaging techniques, such as Raman mapping, NIR mapping and SEM-EDX.¹⁵ A model pharmaceutical system, produced in the laboratory and an authentic tablet containing the same active ingredient (eletriptan hydrobromide), were analysed using the different imaging approaches.

Comparison with other established spectroscopic imaging techniques showed that LDIR imaging provides high-spatial resolution distribution maps comparable to Raman and SEM-EDX data, as shown in Figure 4. Moreover, the acquisition time was orders of magnitude faster; just a few seconds. The rapid acquisition time of LDIR provides opportunities to obtain chemical images of an entire cross section of a tablet surface. It was further demonstrated that a whole cross section of a 10mm-diameter tablet was collected at 10μm spatial step size in about three minutes.

Figure 4

LDIR, Raman, NIR and SEM-EDX chemical images of the three-component model system, where blue = MCC, green = saccharin and red = hydrobromide salt active pharmaceutical ingredient (API). Each chemical image represents a 3mm × 3mm area of sample and the total data collection time for each technique is displayed below the respective chemical image. Reproduced from Ref. 15 with permission of the Royal Society of Chemistry.

This initial assessment suggested that the use of a QCL infrared imaging system can allow detailed domain morphology information to be acquired with rapid collection times. However, utilising this spectroscopic approach requires sample details to be known prior to analysis, and each component of interest must have unique spectral bands. This could potentially limit the capabilities of this technique for several applications, including reverse engineering and identification of unknowns. It is expected that QLC infrared imaging experimental setups will be applied after orthogonal vibrational spectroscopic imaging approaches have been used to study the samples. This would provide information about the full spectral range so that specific wavelengths can be selected for the QCL infrared experiments. To fully realise the potential of this emerging commercial imaging approach, the capabilities of QCL infrared for the analysis of more complex systems must be explored.

Conclusions: Raman mapping for analysis of pharmaceutical tablets

The introduction of a 3D chemical imaging method that combined 2D Raman mapping, serial cross sectioning, and visualisation of the stacked maps as a 3D data cube have been used to reveal quantitative domain size and distribution statistics within tablets”

Recent studies have further demonstrated that NIR and Raman mapping are powerful approaches for the analysis of pharmaceutical tablets. The introduction of a 3D chemical imaging method that combined 2D Raman mapping, serial cross sectioning, and visualisation of the stacked maps as a 3D data cube have been used to reveal quantitative domain size and distribution statistics within tablets. The 3D chemical imaging application has predominantly been used in reactive troubleshooting to identify and understand differences between tablet batches with varying performance.

Future steps in this field would be to incorporate 3D chemical imaging earlier in the drug development process. This would aid understanding about the effects of the physical properties of ingoing raw materials and the manufacturing parameters on the final tablet performance. Further developments in the commercialisation of QCL infrared techniques provide exciting opportunities for fast data acquisition times, although such techniques are still in their infancy in pharmaceutical research. Rapid analyses into the 3D microstructure of pharmaceutical tablets are expected to facilitate improved understanding of pharmaceutical products across the industry.

About the authors

Andrew Ewing is a Senior Scientist in the Material Characterisation Team at Pfizer (UK). He uses advanced microscopical and spectroscopic methods to deliver insights and understanding of a range of pharmaceutical materials and products.

Don Clark is the CSI (Chemistry and Spectroscopy Investigations) Manager in the Material Characterisation Team at Pfizer, based in Sandwich, UK. He is a vibrational spectroscopy SME and since the mid-1990s has been actively involved in chemical mapping and imaging applications.

Fiona Clarke is Director/Team Leader of the Material Characterisation Team, embedded into the Global Supply organisation and based at Pfizer in Sandwich, UK. Having completed her post doctorate in near‑infrared microscopy and image analysis, she has continued to drive this insightful technology for over 20 years to build further pharmaceutical process and product understanding.

References

Pivonka DE, Chalmers JM, Griffiths PR. Applications of vibrational spectroscopy in pharmaceutical research and development. Chichester: Wiley; 2007.
Šašić S, Clark DA. Defining a strategy for chemical imaging of industrial pharmaceutical samples on Raman line-mapping and global illumination instruments. Applied Spectroscopy. 2006;60(5):494-502.
Gendrin C, Roggo Y, Collet C. Content uniformity of pharmaceutical solid dosage forms by near infrared hyperspectral imaging: A feasibility study. Talanta. 2007;73(4):733-41.
Gowen A, O’donnell C, Cullen PJ, Bell S. Recent applications of chemical imaging to pharmaceutical process monitoring and quality control. European Journal of Pharmaceutics and Biopharmaceutics. 2008;69(1):10-22.
Sacré PY, De Bleye C, Chavez PF, et al. Data processing of vibrational chemical imaging for pharmaceutical applications. Journal of Pharmaceutical and Biomedical Analysis. 2014;101:123-40.
Ewing AV, Kazarian SG. Recent advances in the applications of vibrational spectroscopic imaging and mapping to pharmaceutical formulations. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2018;197:10-29.
Zeng Q, Wang L, Wu SJ, et al. Research progress on the application of spectral imaging technology in pharmaceutical tablet analysis. International Journal of Pharmaceutics. 2022;625:122100.
Clark D, Šašić S. Chemical images: Technical approaches and issues. Cytometry Part A. 2006;69A(8):815-24.
Carruthers H, Clark D, Clarke F, et al. Comparison of Raman and near-infrared chemical mapping for the analysis of pharmaceutical tablets. Applied Spectroscopy. 2021;75(2):178-88.
Clarke F, Jamieson M, Clark D, et al. Chemical image fusion. The synergy of FT-NIR and Raman mapping microscopy to enable a more complete visualization of pharmaceutical formulations. Analytical Chemistry. 2001;73(10):2213-20.
Carruthers H, Clark D, Clarke FC, et al. Three-dimensional imaging of pharmaceutical tablets using serial sectioning and Raman chemical mapping. Journal of Raman Spectroscopy. 2022;53(6):1115-25.
Schindelin J, Arganda-Carreras I, Frise E, et al. Fiji: an open-source platform for biological-image analysis. Nature Methods. 2012;9(7):676-82.
Carruthers H, Clark D, Clarke FC, et al. Data processing of three-dimensional vibrational spectroscopic chemical images for pharmaceutical applications. Journal of Spectral Imaging. 2022;11(a3):1-8.
Sacré PY, Mansouri MA, De Bleye C, et al. Evaluation of distributional homogeneity of pharmaceutical formulation using laser direct infrared imaging. International Journal of Pharmaceutics. 2022;612:121373.
Carruthers H, Clark D, Clarke FC, et al. Evaluation of laser direct infrared imaging for rapid analysis of pharmaceutical tablets. Analytical Methods. 2022;14(19):1862-71.

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Raman mapping to visualise the three-dimensional structure of pharmaceutical tablets

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