Chemical imaging of pharmaceutical granules by Raman global illumination and near-infrared mapping platforms

High-throughput optimisations for 3D chemical imaging of pharmaceutical solid oral dosage forms

Chemical imaging of pharmaceutical solid oral dosage forms is a key technique for quality assurance and issue diagnosis. This technique can be further augmented using 3D chemical imaging via serial sections and image stacking. However, the additional collection time this entails means that 3D imaging is utilised for a very niche set of applications. Previous attempts have been made to optimize the process but have often compromised the quality of the resulting chemical images to achieve the gains in process time. In this study, several optimisation strategies are employed to increase the efficiency of 3D chemical image collection without sacrificing the quality of the final chemical images. The use of automated microscope macros and a kinematic mounting system allowed for rapid sample processing and efficient utilisation of equipment time. The automated macros allow the Raman microscope to collect mapping data continuously from multiple samples without the need for operator intervention steps. The kinematic mounting system allows rapid and accurate sample transfer and positioning between instruments. These optimisations resulted in a three times speed increase in collection time while keeping the same signal-to-noise ratio of the resulting chemical images. These optimisations will allow the rapid collection of statistically robust 3D chemical image data within a set time frame that is more amenable to an industrial workflow.

Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.

Application of Computer Microtomography and Hyperspectral Imaging to Assess the Homogeneity of the Distribution of Active Ingredients in Functional Food

Functional foods represent one of the most intensively investigated and widely promoted areas in the food and nutrition sciences’ market today. The purpose of this work is to determine the possibility of using computed microtomography to assess the homogeneity of distribution of active pharmaceutical ingredients (vitamins K and D and calcium) throughout chocolate. Algorithms for analyzing of microtomographic images were proposed to quantify the distribution of active pharmaceutical ingredients (API) in chocolate: the Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging. The use of the methods of analysis and processing of microtomographic images allows for a quantitative assessment of the homogeneity of the distribution of components throughout the sample, without a 3D reconstruction process. In computer microtomography analysis, it is possible to assess the distribution of those components whose density differs by at least a unit in the accepted scale of gray levels of images and for grain sizes not smaller than the voxel size. The proposed image analysis algorithms, Gray Level Co-Occurrence Matrix, quadtree decomposition and hyperspectral imaging, allow for the assessment of distribution of active ingredients in chocolate.

Recent Advances in Spontaneous Raman Spectroscopic Imaging: Instrumentation and Applications

BACKGROUND

Spectroscopic imaging based on the spontaneous Raman scattering effects can provide unique fingerprint information in relation to the vibration bands of molecules. Due to its advantages of high chemical specificity, non-invasive detection capability, low sensitivity to water, and no special sample pretreatment, Raman Spectroscopic Imaging (RSI) has become an invaluable tool in the field of biomedicine and medicinal chemistry.

METHODS

There are three methods to implement RSI, including point scanning, line scanning and wide-field RSI. Point-scanning can achieve two-and three-dimensional imaging of target samples. High spectral resolution, full spectral range and confocal features render this technique highly attractive. However, point scanning based RSI is a time-consuming process that can take several hours to map a small area. Line scanning RSI is an extension of point scanning method, with an imaging speed being 300-600 times faster. In the wide-field RSI, the laser illuminates the entire region of interest directly and all the images then collected for analysis. In general, it enables more accurate chemical imaging at faster speeds.

RESULTS

This review focuses on the recent advances in RSI, with particular emphasis on the latest developments on instrumentation and the related applications in biomedicine and medicinal chemistry. Finally, we prospect the development trend of RSI as well as its potential to translation from bench to bedside.

CONCLUSION

RSI is a powerful technique that provides unique chemical information, with a great potential in the fields of biomedicine and medicinal chemistry.

Kernel principal component analysis residual diagnosis (KPCARD): An automated method for cosmic ray artifact removal in Raman spectra

A new, fully automated, rapid method, referred to as kernel principal component analysis residual diagnosis (KPCARD), is proposed for removing cosmic ray artifacts (CRAs) in Raman spectra, and in particular for large Raman imaging datasets. KPCARD identifies CRAs via a statistical analysis of the residuals obtained at each wavenumber in the spectra. The method utilizes the stochastic nature of CRAs; therefore, the most significant components in principal component analysis (PCA) of large numbers of Raman spectra should not contain any CRAs. The process worked by first implementing kernel PCA (kPCA) on all the Raman mapping data and second accurately estimating the inter- and intra-spectrum noise to generate two threshold values. CRA identification was then achieved by using the threshold values to evaluate the residuals for each spectrum and assess if a CRA was present. CRA correction was achieved by spectral replacement where, the nearest neighbor (NN) spectrum, most spectroscopically similar to the CRA contaminated spectrum and principal components (PCs) obtained by kPCA were both used to generate a robust, best curve fit to the CRA contaminated spectrum. This best fit spectrum then replaced the CRA contaminated spectrum in the dataset. KPCARD efficacy was demonstrated by using simulated data and real Raman spectra collected from solid-state materials. The results showed that KPCARD was fast (<1 min per 8400 spectra), accurate, precise, and suitable for the automated correction of very large (>1 million) Raman datasets.

PAT: From Western solid dosage forms to Chinese materia medica preparations using NIR-CI

Near-infrared chemical imaging (NIR-CI) is an emerging technology that combines traditional near-infrared spectroscopy with chemical imaging. Therefore, NIR-CI can extract spectral information from pharmaceutical products and simultaneously visualize the spatial distribution of chemical components. The rapid and non-destructive features of NIR-CI make it an attractive process analytical technology (PAT) for identifying and monitoring critical control parameters during the pharmaceutical manufacturing process. This review mainly focuses on the pharmaceutical applications of NIR-CI in each unit operation during the manufacturing processes, from the Western solid dosage forms to the Chinese materia medica preparations. Finally, future applications of chemical imaging in the pharmaceutical industry are discussed.

Wide-field Raman imaging of dental lesions

Detection of dental caries at the onset remains as a great challenge in dentistry. Raman spectroscopy could be successfully applied towards detecting caries since it is sensitive to the amount of Raman active mineral crystals, the most abundant component of enamel. Effective diagnosis requires full examination of a tooth surface via Raman mapping. Point-scan Raman mapping is not clinically relevant (feasible) due to lengthy data acquisition time. In this work, a wide-field Raman imaging system was assembled based on a high-sensitivity 2D CCD camera for imaging the mineralization status of teeth with lesions. Wide-field images indicated some lesions to be hypomineralized and others to be hypermineralized. The observations of wide-field Raman imaging were in agreement with point-scan Raman mapping. Therefore, sound enamel and lesions can be discriminated by Raman imaging of the mineral content. In conclusion, wide-field Raman imaging is a potentially useful tool for visualization of dental lesions in the clinic.

Wide area coverage Raman spectroscopy for reliable quantitative analysis and its applications

This review summarizes recent studies to improve sample representation in Raman measurement by covering a large area of a sample in spectral collection. Three different schemes have been mainly investigated to fulfill the goal: (1) averaging of Raman spectra collected at many different locations on a sample, (2) rotation of a sample during spectral collection and (3) simultaneous wide area illumination (WAI) for spectral collection. The use of a wide area illumination scheme, simultaneously illuminating a laser over a large area for spectral acquisition without any further assistance such as sample rotation, has increased in diverse fields. Applications employing the WAI scheme in pharmaceutical, polymer/chemical/petrochemical and other areas are described in this review.

Raman imaging

The past decade has seen an enormous increase in the number and breadth of imaging techniques developed for analysis in many industries, including pharmaceuticals, food, and especially biomedicine. Rather than accept single-dimensional forms of information, users now demand multidimensional assessment of samples. High specificity and the need for little or no sample preparation make Raman imaging a highly attractive analytical technique and provide motivation for continuing advances in its supporting technology and utilization. This review discusses the current tools employed in Raman imaging, the recent advances, and the major applications in this ever-growing analytical field.

Confocal micro-X-ray fluorescence analysis as a new tool for the non-destructive study of the elemental distributions in pharmaceutical tablets

Chemical imaging studies of pharmaceutical tablets are currently an important emerging field in the pharmaceutical industry. Finding the distribution of the different compounds inside the tablet is an important issue for production quality control but also for counterfeit detection. Most of the currently used techniques are limited to the study of the surface of the compacts, whereas the study of the bulk requires a time-consuming sample preparation. In this paper, we present the use of 3D micro-X-ray fluorescence analysis (3D μXRF) for the non-destructive study of pharmaceutical tablets. Based on two different examples, it was shown that it was possible to measure the distribution of several inorganic elements (Zn, Fe, Ti, Mn, Cu) from the surface to a depth of several hundred microns under the surface. The X-ray absorption, depending on both matrix composition and energy, is one of the most critical factors of this analytical method while performing depth profiling or mapping. Therefore, an original method to correct the absorption, in order to accurately measure the true elemental distribution, was proposed. Moreover, by using the presence of titanium dioxide in a pharmaceutical coating, we proved that this technique is also suited to the non-destructive measurement of coating thickness.

Monitoring of API particle size during solid dosage form manufacturing process by chemical imaging and particle sizing

Agglomeration of API during a solid dosage form manufacturing process is followed from the bulk API, through the initial blend with the excipients to the ribbons by a combination of chemical imaging and particle sizing experiments. Particle size of the ingoing API was characterized using a Sympatec HELOS laser diffractometer. Chemical images of the API were obtained from the blends, granules, and ribbons using near-infrared (NIR) and Raman mapping instruments. All the chemical images are obtained in the univariate fashion through the API-characteristic wavenumbers. Light microscopy and laser diffraction were used to assess presence of large agglomerates in the bulk API. NIR chemical images of the sparsely distributed blend particles confirmed that the large agglomerates were not dispersed during the blending. Also, it was found that normal microscopy may be efficient at detecting those API agglomerates due to their distinct appearance (whiteness and size). The agglomerates were not detected in the NIR chemical images of the granules and the ribbons. This was more reliably confirmed by Raman chemical images in which small API domains were clearly identified which was not attainable by NIR mapping.

Lean Raman imaging for rapid assessment of homogeneity in pharmaceutical formulations

Solid dispersion formulations and drug in polymer matrices are increasingly being used by the pharmaceutical industry to enhance the solubility, or bio-availability, of active pharmaceutical ingredients (APIs). The degree of solubility or bio-availability enhancement, as well as properties such as chemical stability and physical characteristics, will be dependent on the homogeneity of the drug in polymer matrix. The use of Raman spectroscopy to assess homogeneity has traditionally been limited by the time required to acquire images from a statistically representative sample area. This may be overcome by employing a more rapid one-dimensional Raman line-mapping approach and using a statistical analysis to extract the critical information. This approach has been termed "lean" Raman imaging and allows a large area of sample to be probed in a relatively short space of time. This paper discusses the use of "lean" Raman imaging to assess two performance-indicating parameters of a drug in polymer formulation, sedimentation of the API within a capsule formulation and phase separation of the individual components. The development of a screening method, using Raman line mapping to allow rapid measurement of sedimentation of the API, is discussed. This method requires less than half an hour per capsule for data collection and processing. In addition, the development of a "lean" Raman mapping technique, using single line scans to assess drug and polymer domain sizes, is detailed. This technique employs a simple peak ratio approach coupled with statistical analysis to provide a measure of the degree of drug and polymer segregation without the need for acquisition of high pixel density images or multivariate analysis. The Raman mapping data is compared with both the dissolution profiles and processing parameters of the samples tested and a strong correlation is shown between formulation homogeneity and dissolution behavior.

Pharmaceutical applications of vibrational chemical imaging and chemometrics: a review

The emergence of chemical imaging (CI) has gifted spectroscopy an additional dimension. Chemical imaging systems complement chemical identification by acquiring spatially located spectra that enable visualization of chemical compound distributions. Such techniques are highly relevant to pharmaceutics in that the distribution of excipients and active pharmaceutical ingredient informs not only a product's behavior during manufacture but also its physical attributes (dissolution properties, stability, etc.). The rapid image acquisition made possible by the emergence of focal plane array detectors, combined with publication of the Food and Drug Administration guidelines for process analytical technology in 2001, has heightened interest in the pharmaceutical applications of CI, notably as a tool for enhancing drug quality and understanding process. Papers on the pharmaceutical applications of CI have been appearing in steadily increasing numbers since 2000. The aim of the present paper is to give an overview of infrared, near-infrared and Raman imaging in pharmaceutics. Sections 2 and 3 deal with the theory, device set-ups, mode of acquisition and processing techniques used to extract information of interest. Section 4 addresses the pharmaceutical applications.