Characterization of chloramphenicol palmitate drug polymorphs by Raman mapping with multivariate image segmentation using a spatial directed agglomeration clustering method

Chemical imaging analysis holds great potential in probing the chemical heterogeneity of samples with high spatial resolution and molecular specificity. This paper demonstrates the implementation of Raman mapping for microscopic characterization of tablets containing chloramphenicol palmitate polymorphs with the aid of a new multivariate image segmentation approach based on spatial directed agglomeration clustering. This approach performs the agglomeration clustering by stepwise merging the pixels possessing both spatial closeness and spectral similarity into clusters that define the image segmentation. The incorporation of spatial closeness into the clustering process enables the approach to improve the robustness and avoid poorly defined image segmentation arising from clusters with highly separated pixels. Additionally, the stepwise merging of clusters offers an F-statistic-based procedure to automatically ascertain the number of image segments. Raman mapping analysis of tablets containing two polymorphs of chloramphenicol palmitate followed by multivariate image segmentation reveals that the proposed technique offers the identification of each polymorph and a quantitative visualization of the spatial distribution of the polymorphs identified. This technique holds promise in rapid, noninvasive, and quantitative polymorph analysis for pharmaceutical production processes.     

Defining a strategy for chemical imaging of industrial pharmaceutical samples on Raman line-mapping and global illumination instruments

The performance of line-mapping and global illumination Raman systems for two pharmaceutical tablets and a powder blend are assessed in this study. The chemical images were obtained from the placebo, real tablets, and powder blend by using x20, x50, and x100 objectives, as well as via the (pseudo) confocal set-up. The chemical images were produced via univariate wavenumbers and as re-folded principal component (PC) scores (known as score images). In most cases it was easy to image two or three major components of the tablets directly, while the minor components were only imaged via PC scores. The active pharmaceutical ingredients (APIs) were located relatively easily even if present in quite low concentrations (less than 1%) owing to the high Raman scattering coefficients of these materials. The strength of the Raman signal of the API makes it almost ubiquitous in the chemical images of real tablets. Thorough discussion is given on the strategies used to produce chemical images, the prospects of making composite images of all components present in the tablets, and the effects of packing density with relation to the diffusion of the excitation laser light inside the sample. The strengths and weaknesses of the Raman imaging techniques used are emphasized and suggestions are given regarding which instrument is preferable with respect to the goal of the experiment and material under study. For example, mapping technology is preferred for analyzing minor components, while the global illumination approach is recommended for imaging of spatially isolated strong Raman scatterers.     

Characterization of complex polysorbate formulations by means of shape-selective mass spectrometry

Complex synthetic formulations based on polysorbates can be challenging to characterize. They may be composed of many similar products including those of the same molecular weight, which cannot be readily separated by separation science approaches. Carbon number variation and ethylene oxide distribution add to the complexity. The properties of these formulations will be dependent on the chemical structure and relative concentration of formulation components. Here we describe the use of two experimental approaches based on mass spectrometry to provide enhanced characterization of these formulations. The first utilizes an atmospheric pressure solids analysis probe to rapidly determine the percentage content of individual esters in a formulation. These are shown to be in good agreement with product specification sheets. In a second approach, mobility separation has been integrated into a MALDI-MS/MS experiment to categorize major, minor, and trace ingredients. Components of identical molecular mass in the polysorbate formulations have been separated by ion mobility and then fragmented for additional characterization. The rapidity and level of structural detail provided by these experiments offers a significant opportunity to develop practical screening methods for complex formulations.     

An in-depth analysis of Raman and near-infrared chemical images of common pharmaceutical tablets

This study reports on the application of Raman and near-infrared (NIR) imaging techniques for determining the spatial distribution of all (five) components in a common type of pharmaceutical tablet manufactured in two different ways. Multivariate chemical images were produced as principal component (PC) scores, while univariate images were produced by using the most unique spectra selected by the orthogonal projection approach (OPA), a searching algorithm. Multivariate Raman images were obtained for all five components in both tablets, while only two or three components could be imaged with the NIR instrument. Very interesting PC results are reported that in effect cast doubt on the effectiveness of the established criteria for determining signal-related PCs in the Raman data. PCA has been found to be indispensable for imaging the minor components using the Raman data. Significant similarity between the multivariate and univariate chemical images has been noted despite there being considerable spectral overlap within the Raman and, especially, within the NIR mapping data sets. Gray-scale images are carefully thresholded, which allowed for quantitative comparison of the obtained binarized images. A thorough discussion is given on the problems and approximations needed for producing composite images.     

Quantitative image analysis of broadband CARS hyperspectral images of polymer blends

We demonstrate that broadband coherent anti-Stokes Raman scattering (CARS) microscopy can be very useful for fast acquisition of quantitative chemical images of multilayer polymer blends. This is challenging because the raw CARS signal results from the coherent interference of resonant Raman and nonresonant background and its intensity is not linearly proportional to the concentration of molecules of interest. Here we have developed a sequence of data-processing steps to retrieve background-free and noise-reduced Raman spectra over the whole frequency range including both the fingerprint and C-H regions. Using a classical least-squares approach, we are able to decompose a Raman hyperspectral image of a tertiary polymer blend into quantitative chemical images of individual components. We use this method to acquire 3-D sectioned quantitative chemical images of a multilayer polymer blend of polystyrene, styrene-ethylene/propylene copolymer, and polypropylene that have overlapping spectral peaks.     

A practical algorithm to remove cosmic spikes in Raman imaging data for pharmaceutical applications

Raman dispersive microscopic imaging techniques are finding ever-increasing applications in pharmaceutical research for their ability to provide spatial and spectral information about the sample. Spectral data acquired from dispersive Raman instruments utilizing charge-coupled device detectors are characterized by occasional high intensity spikes arising from cosmic ray events. These random cosmic spikes are superimposed on chemically meaningful spectra. Due to their high intensity and potential influence on variance structures, it is often crucial to filter cosmic spikes from data prior to the use of multivariate algorithms to extract chemical information from the image cube. Some extremely challenging cosmic spikes are found to seriously interfere with multivariate data analysis for our application, e.g., spikes with bandwidth greater than the bandwidth from species of interest, spikes in neighboring image pixels occurring at the same spectral channels, spikes right on top of the band of interest, etc. A practical algorithm is proposed for semiautomated cosmic spike removal. The algorithm is computationally efficient, conceptually simple, and easy to implement. It is an alternative to methods using repetitive measurements by taking advantage of the spatial characteristic of imaging techniques and existing knowledge from the formulation. The algorithm has been shown to generate recovered spectra with negligible spectral distortion. The utility of the algorithm will be illustrated by the analysis of Raman images of pharmaceutical samples.     

Integrating X-ray fluorescence and infrared imaging microspectroscopies for comprehensive characterization of an acetaminophen model pharmaceutical

The integration of full spectral images using the complementary microspectroscopic imaging techniques X-ray fluorescence and Fourier transform infrared is demonstrated. This effort surpasses previous work in that a single chemometric software package is used to elicit chemical information from the integrated spectroscopic images. Integrating these two complementary spectroscopic methods provides both elemental and molecular spatial distribution within a specimen. The critical aspect in this work is using full spectral maps from each pixel within the image and subsequent processing with chemometric tools to provide integrated chemical information. This integration enables a powerful approach to more comprehensive materials characterization. Issues addressed include sample registration and beam penetration depth and how each affects post-processing. An inorganic salt and an acetaminophen pharmaceutical model mixture demonstrate the power of integrating these techniques with chemometric software.     

Characterizing the structure of pharmaceutical granules obtained by wet granulation with varying amounts of water via Raman chemical imaging

A pharmaceutical formulation containing metformin hydrochloride (MET), hydroxypropyl cellulose (HPC), and microcrystalline cellulose (MCC) was wet granulated with varying amounts of water and the structure of the obtained granules was characterized by Raman chemical mapping. Univariate Raman mapping was found to be satisfactory for producing the images of the two components of interest (HPC and MCC). In addition to the images, the average Raman spectra from the maps as well as the micro-Raman spectra from the hot pixels were analyzed. HPC is found to strongly respond to the addition of water, with its domain dissipating and Raman bands becoming weaker as the water addition increases. MCC is also responsive to water, reacting similarly to HPC but to a much smaller extent and only for the largest amounts of water. Granules made with increasing water content also have improved tabletting properties and flow.     

Noninvasive authentication of pharmaceutical products through packaging using spatially offset Raman spectroscopy

We demonstrate the use of spatially offset Raman spectroscopy (SORS) in the identification of counterfeit pharmaceutical tablets and capsules through different types of packaging. The technique offers a substantially higher sensitivity than that available from conventional backscattering Raman spectroscopy. The approach is particularly beneficial in situations where the conventional Raman backscattering method is hampered or fails because of excessive surface Raman or fluorescence signals emanating from the packaging, capsule shell, or tablet coating contaminating the much weaker subsurface Raman signals of the active pharmaceutical ingredients and excipients held in the product. It is demonstrated that such interfering signals can be effectively suppressed by SORS.     

Chemical imaging of iron oxides and oxyhydroxides using near infrared Raman imaging microscopy

Abstract

A new method of identifying and mapping the distribution of both iron oxides and oxyhydroxides using near infrared Raman imaging microscopy NIRIM is reported. This technique offers an important alternative to conventional spectroscopic techniques that provide spatially averaged data. The NIRIM instrument used for these studies combines fibre bundle image compression hardware and multivariate signal processing software to identify and map different iron minerals and corrosion products. The NIRIM images clearly distinguish hematite, magnetite, wustite, goethite, and lepidocrocite microstructures. The first chemical maps of naturally occurring iron minerals and corroded steel surfaces obtained using NIRIM spectral images, classified with the aid of a library of pure compound spectra, are presented.     

Quantitative transmission Raman spectroscopy of pharmaceutical tablets and capsules

Quantitative analysis of pharmaceutical formulations using the new approach of transmission Raman spectroscopy has been investigated. For comparison, measurements were also made in conventional backscatter mode. The experimental setup consisted of a Raman probe-based spectrometer with 785 nm excitation for measurements in backscatter mode. In transmission mode the same system was used to detect the Raman scattered light, while an external diode laser of the same type was used as excitation source. Quantitative partial least squares models were developed for both measurement modes. The results for tablets show that the prediction error for an independent test set was lower for the transmission measurements with a relative root mean square error of about 2.2% as compared with 2.9% for the backscatter mode. Furthermore, the models were simpler in the transmission case, for which only a single partial least squares (PLS) component was required to explain the variation. The main reason for the improvement using the transmission mode is a more representative sampling of the tablets compared with the backscatter mode. Capsules containing mixtures of pharmaceutical powders were also assessed by transmission only. The quantitative results for the capsules' contents were good, with a prediction error of 3.6% w/w for an independent test set. The advantage of transmission Raman over backscatter Raman spectroscopy has been demonstrated for quantitative analysis of pharmaceutical formulations, and the prospects for reliable, lean calibrations for pharmaceutical analysis is discussed.     

Dependence of signal on depth in transmission Raman spectroscopy

Recently, transmission Raman spectroscopy has been shown to be a valuable tool in the volumetric quantification of pharmaceutical formulations. In this work a Monte Carlo simulation and experimental study are performed to elucidate the dependence of the Raman signal on depth from the viewpoint of probing pharmaceutical tablets and powders in this experimental configuration. The transmission Raman signal is shown to exhibit a moderate bias toward the center of the tablets and this can be considerably reduced by using a recently developed Raman signal-enhancing concept, the "photon diode." The enhancing element not only reduces the bias but also increases the overall Raman signal intensity and consequently improves the signal-to-noise ratio of the measured spectrum. Overall, its implementation with appropriately chosen reflectivity results in a more uniform volumetric sampling across the half of the tablet where the photon diode is used (or across the tablet's entire depth if two photon diodes are used on each side of tablet) and enhanced overall sensitivity. These findings are substantiated experimentally on a segmented tablet by inserting a poly(ethelyne terephthalate) (PET) film doped with TiO(2) at different depths and monitoring its contribution to the overall transmission Raman signal from the segmented tablet. The numerical simulations also indicate considerable sensitivity of the overall Raman signal to the absorption of the sample, which is in line with large migration distances traversed by photons in these measurements. The presence of sample absorption was shown numerically to reduce the signal enhancement effect while the overall depth-dependence profile remained broadly unchanged. The absorption was also shown to produce a depth profile with the photon diode similar to that without it, although with a reduced absolute intensity of Raman signals and diminished enhancement effect.     

Finite element formulation for a digital image correlation method

A finite element formulation for a digital image correlation method is presented that will determine directly the complete, two-dimensional displacement field during the image correlation process on digital images. The entire interested image area is discretized into finite elements that are involved in the common image correlation process by use of our algorithms. This image correlation method with finite element formulation has an advantage over subset-based image correlation methods because it satisfies the requirements of displacement continuity and derivative continuity among elements on images. Numerical studies and a real experiment are used to verify the proposed formulation. Results have shown that the image correlation with the finite element formulation is computationally efficient, accurate, and robust.     

Chemical imaging with a confocal scanning Fourier-transform-Raman microscope

Traditional approaches in confocal microscopy have focused on techniques to generate volumetric intensity or phase images of an object. In these different imaging modes the scattered optical-field properties depend on local refractive index and absorption, properties not unique to a given material. We report here on a confocal microscope that uses Raman scattered light to generate volumetric chemical images of a material. We designed and built a prototype instrument, called a confocal scanning laser Raman microscope, that combines a confocal scanning laser microscope with a Fourier-transform-Raman spectrometer. The high depth and lateral spatial resolution of the confocal optics design define a volume element from which the Raman scattered light is collected, and the spectrometer analyzes its spectral content. The sample is scanned through the microscope probe volume, and a chemical image isgenerated based on the content of the Raman spectrum extracted from each scan position in the sample. The results inclu e instrument characterization measurements and examples of confocal chemical imaging.     

Direct Raman imaging techniques for study of the subcellular distribution of a drug

Direct Raman imaging techniques are demonstrated to study the drug distribution in living cells. The advantage of Raman imaging is that no external markers are required, which simplifies the sample preparation and minimally disturbs the drug mechanism during imaging. The major challenge in Raman imaging is the weak Raman signal. In this study, we present a Raman image model to describe the degradation of Raman signals by imaging processes. Using this model, we demonstrate special-purpose image-processing algorithms to restore the Raman images. The processing techniques are then applied to visualize the anticancer agent paclitaxel in living MDA-435 breast cancer cells. Raman images were obtained from a cancer cell before, during, and after drug treatment. The paclitaxel distribution illustrated in these images is explained by means of the binding characteristics of the paclitaxel and its molecular target-the microtubules. This result demonstrates that direct Raman imaging is a promising tool to study the distribution of a drug in living cells.     

Quantitative evaluation of the sensitivity of library-based Raman spectral correlation methods

Library-based Raman spectral correlation methods are widely used in surveillance applications in multiple areas including the pharmaceutical industry, where Raman spectroscopy is commonly used in verification screening of incoming raw materials. While these spectral correlation methods are rapid and require little or no sample preparation, their sensitivity to the presence of contaminants has not been adequately evaluated. This is particularly important when dealing with pharmaceutical excipients, which are susceptible to economically motivated adulteration by substances having similar physical/chemical/spectroscopic properties. We report a novel approach to evaluating the sensitivity of library-based Raman spectral correlation methods to contaminants in binary systems using a hit-quality index model. We examine three excipient/contaminant systems, glycerin/diethylene glycol, propylene glycol/diethylene glycol, and lactose/melamine and find that the sensitivity to contaminant for each system is 18%, 32%, and 4%, respectively. These levels are well-correlated to the minimum contaminant composition that can be detected by both verification and identification methods. Our studies indicate that the most important factor that determines the sensitivity of a spectral correlation measurement to the presence of contaminant is the relative Raman scattering cross section of the contaminant.     

Quantitative analysis of piroxicam polymorphs pharmaceutical mixtures by hyperspectral imaging and chemometrics

It has been recognized that crystal polymorphism is an important factor related to the physicochemical and biological properties of drug substances and formulations. In this work, the piroxicam polymorphic forms 1 and 2 were studied using near-infrared chemical imaging (NIR-CI) technology to map the distribution of both species in pharmaceutical formulations. In this direction, the partial least squares (PLS) method was used to construct calibration models of concentrations per pixel of the sample. The RMSEP results for both models of the polymorphic forms remained below 4% (w/w). It was also possible to distinguish local and global information of the constituents through this method. These results seem to be a suitable tool for quality process control and final product quality assurance.     

Multivariate statistical analysis of concatenated time-of-flight secondary ion mass spectrometry spectral images. Complete description of the sample with one analysis

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) instruments are capable of saving an entire mass spectrum at each pixel of an image, allowing for retrospective analysis of masses that were not selected for analysis during data collection. These TOF-SIMS spectral images contain a wealth of information, but few tools are available to assist the analyst in visualizing the entire raw data set and as a result, most of the data are not analyzed. Automated, nonbiased, multivariate statistical analysis (MVSA) techniques are useful for converting the massive amount of data into a smaller number of chemical components (spectra and images) that are needed to fully describe the TOF-SIMS measurement. Many samples require two back-to-back TOF-SIMS measurements in order to fully characterize the sample, one measurement of the fraction of positively charged secondary ions (positive ion fraction) and one measurement of the fraction of negatively charged secondary ions (negative ion fraction). Each measurement then needs to be individually evaluated. In this paper, we report the first MVSA analysis of a concatenated TOF-SIMS data set comprising positive ion and negative ion spectral images collected on the same region of a sample. MVSA of concatenated data sets provides results that are intuitive and fully describe the sample. The analytical insight provided by MVSA of the concatenated data set was not obtained when either polarity data set was analyzed separately.     

Bulk Raman analysis of pharmaceutical tablets

We compare and contrast two Raman collection geometries, backscattering and transmission, to identify their potential for monitoring the bulk chemical composition of turbid media. The experiments performed on pharmaceutical tablets confirm the expected strong bias of the backscattering Raman collection towards surface layers of the probed sample. However, this bias is largely absent with the transmission geometry, exhibiting gross insensitivity to the depth of impurities within the sample. The results are supported by Monte-Carlo simulations. The applicability of transmission geometry to tablets without any thinning is possible because of long migration times of Raman photons in non-absorbing powder media. The absolute measured intensity of the Raman signal was only 12 times lower in transmission geometry compared with backscattering geometry for a standard paracetamol tablet with a thickness of 3.9 mm. This makes detection relatively straightforward, and detectable Raman signals were observed even after propagation through three paracetamol tablets. Given its properties and instrumental simplicity, the transmission method is particularly well suited to the on-line analysis of bulk content of tablets in pharmaceutical applications.