Pharmaceutical applications of vibrational chemical imaging and chemometrics: a review

Critical evaluation of hyperspectral imaging technology for detection and quantification of microplastics in soil

In this study, we critically evaluated the performance of an emerging technology, hyperspectral imaging (HSI), for detecting microplastics (MPs) in soil. We examined the technology's robustness against varying environmental conditions in five groups of experiments. Our findings show that near-infrared (NIR) hyperspectral imaging (HSI) effectively detects microplastics (MPs) in soil, though detection efficacy is influenced by factors such as MP concentration, color, and soil moisture. We found a generally linear relationship between the levels of MPs in various soils and their spectral responses in the NIR HSI imaging spectrum. However, effectiveness is reduced for certain MPs, like polyethylene, in kaolinite clay. Furthermore, we showed that soil moisture considerably influenced the detection of MPs, leading to nonlinearities in quantification and adding complexities to spectral analysis. The varied responses of MPs of different sizes and colors to NIR HSI present further challenges in detection and quantification. The research suggests pre-grouping of MPs based on size before analysis and proposes further investigation into the interaction between soil moisture and MP detectability to enhance HSI's application in MP monitoring and quantification. To our knowledge, this study is the first to comprehensively evaluate this technology for detecting and quantifying microplastics.

Suitability of Fourier transform infrared microscopy for the diagnosis of cystic echinococcosis in human tissue sections

Cystic echinococcosis (CE) is a global health concern caused by cestodes, posing diagnostic challenges due to nonspecific symptoms and inconclusive radiographic results. Diagnosis relies on histopathological evaluation of affected tissue, demanding comprehensive tools. In this retrospective case study, Fourier transform infrared microscopy was explored for detecting and identifying CE through biochemical changes in human tissue sections. Tissue samples from 11 confirmed CE patients were analyzed. Archived FFPE blocks were cut and stained, and then CE-positive unstained sections were examined using Fourier transform infrared microscopy post-deparaffinization. Results revealed the method's ability to distinguish echinococcus elements from human tissue, irrespective of organ type. This research showcases the potential of mid-infrared microscopy as a valuable diagnostic tool for CE, offering promise in enhancing diagnostic precision in the face of the disease's complexities.

Hyperspectral retinal imaging biomarkers of ocular and systemic diseases

Hyperspectral imaging is a frontier in the field of medical imaging technology. It enables the simultaneous collection of spectroscopic and spatial data. Structural and physiological information encoded in these data can be used to identify and localise typically elusive biomarkers. Studies of retinal hyperspectral imaging have provided novel insights into disease pathophysiology and new ways of non-invasive diagnosis and monitoring of retinal and systemic diseases. This review provides a concise overview of recent advances in retinal hyperspectral imaging.

Quantitative study of ternary polycrystalline mixtures of prulifloxacin based on Raman spectra and Raman imaging maps

Prulifloxacin, a broad-spectrum quinolone antibiotic, exhibits three distinct crystal forms, each with different bioavailability and therapeutic properties. It is imperative to assess and control the proportion of each crystal form during the production of raw materials and preparations. Therefore, it is necessary to establish an analytical method that can determine the content of each crystal form in the ternary polycrystalline mixtures. In this study, prulifloxacin crystal forms were analyzed and quantitatively measured using Raman spectroscopy. First, three pure crystal forms of prulifloxacin were prepared under different crystallization conditions and mixed into ternary mixtures at the designed proportions. Subsequently, the ternary mixed crystal samples were analyzed using a Raman microscope.Then run a partial least squares regression analysis to establish a PLS quantitative model using the average spectra data, and a non-negative least squares analysis to establish an area percentage quantitative model using Raman imaging data.The method validation results showed that the two models successfully predicted the proportion of each crystal form within the prulifloxacin polycrystalline mixtures, with a prediction accuracy of less than ± 10 %. Raman spectroscopy was thus established as an effective method for crystal form analysis and quantitative measurement of prulifloxacin.

Detection of Oxacillin/Cefoxitin Resistance in Staphylococcus aureus Present in Recurrent Tonsillitis

Background: Recurrent tonsillitis is one of the most common diseases in childhood, caused many times by ß-lactam-resistant S. aureus. The objective of this study was to investigate an alternative method to identify resistance to oxacillin/cefoxitin in S. aureus from hospitalized children with recurrent tonsillitis. Methods: The samples of S. aureus came from patients with recurrent tonsillitis and were used in 16S rRNA sequencing and an antibiogram test for identification and verifying resistance, after which HSI methodology were applied for separation of S. aureus resistances. Results: The S. aureus isolated showed sensitivity to oxacillin/cefoxitin and the diagnostic images show a visual description of the resistance different groups formed, that may be related to sensitivity and resistance to oxacillin/cefoxitin, characterizing the MRSA S. aureus. Conclusions: Samples that showed phenotypic resistance to oxacillin/cefoxitin were clearly separated from samples that did not show this resistance. A PLS-DA model predicted the presence of resistance to oxacillin/cefoxitin in S. aureus samples and it was possible to observe the pixels classified as MRSA. The HSI was able to successfully discriminate samples in replicas that were sensitive and resistant, based on the calibration model it received.

Novel aspects of Raman spectroscopy in skin research

The analytical technology of Raman spectroscopy has an almost 100‐year history. During this period, many modifications and developments happened in the method like discovery of laser, improvements in optical elements and sensitivity of spectrometer and also more advanced light detection systems. Many types of the innovative techniques appeared (e.g. Transmittance Raman spectroscopy, Coherent Raman Scattering microscopy, Surface‐Enhanced Raman scattering and Confocal Raman spectroscopy/microscopy). This review article gives a short description about these different Raman techniques and their possible applications. Then, a short statistical part is coming about the appearance of Raman spectroscopy in the scientific literature from the beginnings to these days. The third part of the paper shows the main application options of the technique (especially confocal Raman spectroscopy) in skin research, including skin composition analysis, drug penetration monitoring and analysis, diagnostic utilizations in dermatology and cosmeto‐scientific applications. At the end, the possible role of artificial intelligence in Raman data analysis and the regulatory aspect of these techniques in dermatology are briefly summarized. For the future of Raman Spectroscopy, increasing clinical relevance and in vivo applications can be predicted with spreading of non‐destructive methods and appearance with the most advanced instruments with rapid analysis time.

Prediction of the Quality of Thermally Sprayed Copper Coatings on Laser-Structured CFRP Surfaces Using Hyperspectral Imaging

With the progressive replacement of metallic parts by high-performance fiber-reinforced plastic (FRP) components, typical properties of metals are required to be placed on the material’s surface. A metallic coating applied to the FRP surface by thermal spraying, for instance, can fulfill these requirements, including electrical conductivity. In this work, laser pre-treatments are utilized for increasing the bond strength of metallic coatings. However, due to the high-precision material removal using pulsed laser radiation, the production-related heterogeneous fiber distribution in FRP leads to variations in the structuring result and consequently to different qualities of the subsequent coating. In this study, hyperspectral imaging (HSI) technologies in conjunction with deep learning were applied to carbon fiber-reinforced plastics (CFRP) structured by nanosecond pulsed laser. HSI-based prediction models could be developed, which allow for reliable prediction, with an accuracy of around 80%, of which laser-treated areas will successfully be coated and which will not. By using this objective and automatic evaluation, it is possible to avoid large amounts of rejects before further processing the parts and also to optimize the adhesion of coatings. Spatially resolved data enables local reworking during the laser process, making it feasible for the manufacturing process to achieve zero waste.

A feasibility study on improving the non-invasive detection accuracy of bottled Shuanghuanglian oral liquid using near infrared spectroscopy

The ultimate goal of the study is to present a strategy to improve the accuracy of near-infrared spectroscopy detection of Shuanghuanglian oral liquid in glass bottles without damaging the primary packaging. we adopted the multi-position spectral modeling (MPSM) method to correct the spectral variation caused by the difference of bottle and measuring position, so as to improve the measurement accuracy and find the best site combination for measuring Shuanghuanglian oral liquid. Baicalin, total flavonoids and soluble solid contents were considered as the quality indicators of the oral liquid, and partial least squares (PLS) models were employed for the single-position and multi-position spectra, respectively. The root mean square error of the validation set (RMSEP) of the optimum multi-position models are 0.7412 mg/mL for baicalin, 1.1259 mg/mL for total flavonoids and 0.9491% for soluble solids contents. Compared with the traditional single-position spectral modeling method (SPSM method), MPSM method improved the prediction accuracy of baicalin, total flavonoids and soluble solid contents by 26.84%, 31.97% and 58.14% respectively. The results showed that the MPSM method can improve the measurement accuracy of bottled oral liquid and is an effective method to eliminate the uncertainty of measurement conditions.

Method development and validation of a near-infrared spectroscopic method for in-line API quantification during fluidized bed granulation

Near-infrared spectroscopy (NIRS) is an excellent process analytical technology (PAT) tool for active pharmaceutical ingredient (API) quantification during fluidized granulation. Therefore, a portable near-infrared spectrometer combined with a new innovative method of extended iterative optimization technique (EIOT) was used to in-line monitor the API content uniformity during fluidized bed granulation. The principal component analysis (PCA) and partial least squares regression (PLSR) were also used to characterize and predict API concentration with changes from 75% to 125% of the label claim to prove the superiority of EIOT. The API content prediction accuracy of the EIOT method was verified through offline High Performance Liquid Chromatography (HPLC) measurement. Also, the spatial distribution of API in granules was visualized by Raman imaging technology. The results showed that the established NIRS method was suitable for the prediction of API content in fluidized bed granulation, which provides a new idea for the determination of API content during granulation.

Evaluation of laser direct infrared imaging for rapid analysis of pharmaceutical tablets

Vibrational spectroscopic chemical imaging is an important tool in the pharmaceutical industry for characterising the spatial distribution of components within final drug products. The applicability of these techniques is currently limited by the long data acquisition times required to obtain high-definition chemical images of a sample surface. Advancements in quantum cascade laser (QCL) technology have provided an exciting new opportunity for infrared (IR) imaging. Instead of collecting a full IR spectrum at each point, it is possible to focus on distinct spectral bands to reduce imaging data collection time. This study explores a laser direct infrared (LDIR) chemical imaging approach that couples QCL technology with rapid scanning optics to provide high-definition chemical images at an order of magnitude faster than traditional imaging techniques. The capabilities of LDIR chemical imaging were evaluated for pharmaceutical formulations and compared with other established spectroscopic chemical imaging techniques including Raman, near-infrared (NIR) and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) spectroscopy with regards to data acquisition time and image quality. The study showed that LDIR imaging provided high-definition component distribution maps comparable to Raman and SEM-EDX at orders of magnitude faster in terms of time. The ability to obtain high-definition chemical images of the whole tablet surface in relatively fast time frames indicates LDIR imaging could be a promising tool in the pharmaceutical industry to rapidly characterise the size and distribution of components within tablets and could help enhance drug product manufacturing understanding.

Non-Local Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspectral image (HSI) restoration, which includes the tasks of denoising, compressed HSI reconstruction and inpainting. Unfortunately, while its restoration performance benefits from more spectral bands, its runtime also substantially increases. In this paper, we claim that the HSI lies in a global spectral low-rank subspace, and the spectral subspaces of each full band patch group should lie in this global low-rank subspace. This motivates us to propose a unified paradigm combining the spatial and spectral properties for HSI restoration. The proposed paradigm enjoys performance superiority from the non-local spatial denoising and light computation complexity from the low-rank orthogonal basis exploration. An efficient alternating minimization algorithm with rank adaptation is developed. It is done by first solving a fidelity term-related problem for the update of a latent input image, and then learning a low-dimensional orthogonal basis and the related reduced image from the latent input image. Subsequently, non-local low-rank denoising is developed to refine the reduced image and orthogonal basis iteratively. Finally, the experiments on HSI denoising, compressed reconstruction, and inpainting tasks, with both simulated and real datasets, demonstrate its superiority with respect to state-of-the-art HSI restoration methods.

Analysis of Over-Granulated Particles using Near-Infrared Chemical Imaging and Attenuated Total Reflectance-Infrared Techniques

To elucidate the previously described mechanism of segregation caused by over-granulation, we analyzed over-granulated particles using the techniques of near-infrared chemical imaging (NIR-CI) and attenuated total reflectance infrared (ATR-IR). The same area of over-granulated particles was measured using both techniques. The distributions of the active ingredient, ethenzamide, and other additives in the over-granulated particles were compared. As ATR-IR chemical imaging easily identifies components and has higher spatial resolution than NIR-CI, it permitted a clearer observation of the distribution of ingredients, particularly in fine cornstarch particles. Using both techniques, segregation of components were observed as previously reported. Although lactose was barely observed in the ethenzamide-enriched regions, ethenzamide and cornstarch were observed in lactose-enriched regions. This suggests that only lactose aggregated and segregated from the other compounds during the process of granulation. Hydrophilic lactose aggregation is supposedly caused by the behavior of water during granulation. In conclusion, ATR-IR chemical imaging is an excellent analytical technique for obtaining the detailed distribution of components. Furthermore, fusion of ATR-IR chemical imaging and NIR-CI is a useful tool for understanding drug manufacturing processes and may be applicable to pharmaceutical manufacturing and quality control.

Evaluation of the Miscibility of Novel Cocoa Butter Equivalents by Raman Mapping and Multivariate Curve Resolution-Alternating Least Squares

Cocoa butter (CB) is an ingredient traditionally used in the manufacturing of chocolates, but its availability is decreasing due to its scarcity and high cost. For this reason, other vegetable oils, known as cocoa butter equivalents (CBE), are used to replace CB partially or wholly. In the present work, two Peruvian vegetable oils, coconut oil (CNO) and sacha inchi oil (SIO), are proposed as novel CBEs. Confocal Raman microscopy (CRM) was used for the chemical differentiation and polymorphism of these oils with CB based on their Raman spectra. To analyze their miscibility, two types of blends were prepared: CB with CNO, and CB with SIO. Both were prepared at 5 different concentrations (5%, 15%, 25%, 35%, and 45%). Raman mapping was used to obtain the chemical maps of the blends and analyze their miscibility through distribution maps, histograms and relative standard deviation (RSD). These values were obtained with multivariate curve resolution-alternating least squares. The results show that both vegetable oils are miscible with CB at high concentrations: 45% for CNO and 35% for SIO. At low concentrations, their miscibility decreases. This shows that it is possible to consider these vegetable oils as novel CBEs in the manufacturing of chocolates.

Raman Imaging as a powerful tool to elucidate chemical processes in a matrix: Medicated chewing gums with nicotine

Extruded medicated chewing gum is a convenient but complex drug delivery system. Description of gum ingredient distribution and interactions in literature is sparse, but fundamental in product characterization and stability prediction. Although Raman spectroscopy has been used for such characterization of numerous dosage forms, its applicability to medicated chewing gum has not been studied until now. The objective was to investigate the applicability of confocal Raman imaging on chewing gum for identification and distribution of excipients and the model drug nicotine, including changes occurring during shelf life. A sample preparation protocol was composed to present an even surface of a gum cross section without altering the gum matrix texture. High-resolution Raman maps were obtained by Non Negative Least Squares (NNLS) analysis for a reference gum and gums stored for 6 months at mild (25 °C/60% RH) and accelerated (40 °C/75% RH) conditions. Additional Empty Modelling™ analysis confirmed the results of NNLS. The NNLS analysis located nicotine and the following excipients: gum base, calcium carbonate, sorbitol, xylitol, sodium carbonate, sodium bicarbonate and talc in distinct domains of the reference sample. Changes of the sample stored at accelerated conditions was discovered as sodium carbonate was not observed in this sample. Additionally, stereo light microscopy showed changes in product appearance and high-performance liquid chromatography confirmed formation of the oxidation product nicotine-1'-N-oxide in this sample. The gum formulation and its ingredients displayed characteristic Raman spectra, proving Raman imaging as a useful method for characterizing medicated chewing gums, including changes occurring during stability testing.

Application of reverse engineering in the field of pharmaceutical tablets using Raman mapping and chemometrics

Raman micro-spectroscopy technique offers a combination of relatively high spatial resolution with identification of components or mixtures of components in different sample areas, e.g. on the surface or the cross-section of a sample. This study is focused on the analysis of the tablets from pharmaceutical development with different technological parameters: (1) the manufacturing technology, (2) the particle size of the input API (active pharmaceutical ingredient) and (3) the quantitative composition of the individual excipients. These three mentioned parameters represent the most frequently solved problems in the field of reverse engineering in pharmacy. The investigation aims to distinguish tablets with the above-described technological parameters with limited subjective steps by Raman microscopy. Furthermore, non-subjective methods of Raman data analysis using advanced statistical analysis have been proposed, namely Principal Component Analysis, Soft Independent Modelling of Class Analogy and Linear Discriminant Analysis. The methods successfully distinguished and identified even very small differences in the analysed tablets within our study and provided objective statistic evaluation of Raman maps. The information on component and particle size distribution including their small differences, which is the critical parameter in the development of the original and generic products, was obtained due to combination of these methods. Even though each of these chemometric methods evaluates the data set from a different perspective, their mutual application on the problem of Raman maps evaluation confirmed and specified results on level that would be unattainable with the use of only one them.

Application of mid-infrared microscopic imaging for the diagnosis and classification of human lymphomas

Mid-infrared (MIR) microscopic imaging of indolent and aggressive lymphomas was performed including formalin-fixed and paraffin-embedded samples of six follicular lymphomas and 12 diffuse large B-cell-lymphomas as well as reactive lymph nodes to investigate benefits and challenges for lymphoma diagnosis. MIR images were compared to defined pathological characteristics such as indolent versus aggressive versus reactive, germinal centre versus activated cell-of-origin (COO) subtypes, or a low versus a high proliferative index and level of PD-L1 expression. We demonstrated that MIR microscopic imaging can differentiate between reactive lymph nodes, indolent and aggressive lymphoma samples. Also, it has potential to be used in the subtyping of lymphomas, as shown with the differentiation between COO subtypes, the level of proliferation and PD-L1 expression. MIR microscopic imaging is a promising tool for diagnosis and subtyping of lymphoma and further evaluation is needed to fully explore the advantages and disadvantages of this method for pathological diagnosis.

In Vitro and In Vivo Multispectral Photoacoustic Imaging for the Evaluation of Chromophore Concentration

Multispectral photoacoustic imaging is a powerful noninvasive medical imaging technique that provides access to functional information. In this study, a set of methods is proposed and validated, with experimental multispectral photoacoustic images used to estimate the concentration of chromophores. The unmixing techniques used in this paper consist of two steps: (1) automatic extraction of the reference spectrum of each pure chromophore; and (2) abundance calculation of each pure chromophore from the estimated reference spectra. The compared strategies bring positivity and sum-to-one constraints, from the hyperspectral remote sensing field to multispectral photoacoustic, to evaluate chromophore concentration. Particularly, the study extracts the endmembers and compares the algorithms from the hyperspectral remote sensing domain and a dedicated algorithm for segmentation of multispectral photoacoustic data to this end. First, these strategies are tested with dilution and mixing of chromophores on colored 4% agar phantom data. Then, some preliminary in vivo experiments are performed. These consist of estimations of the oxygen saturation rate (sO2) in mouse tumors. This article proposes then a proof-of-concept of the interest to bring hyperspectral remote sensing algorithms to multispectral photoacoustic imaging for the estimation of chromophore concentration.

Non-invasive detection technologies of solid foreign matter and their applications to lyophilized pharmaceutical products: A review

Good Manufacturing Practice Regulations, under the Food and Drug Administration (FDA), stipulate that all pharmaceutical products must be free of any contaminants, including, namely, any foreign solid objects. Lyophilization is a common manufacturing method that consists of several steps where foreign materials may enter the product. The presence of unintended particles in freeze drying, which will herein be referred to under the term 'Lyophilization', is of great concern to the authorities responsible for drug safety and effectiveness. In the pharmaceutical industry, presently, the inspection of lyophilized products for foreign matter particulates relies on visual inspection where only the outer surface of the lyophilized cake is visible. This review is motivated by the need for new control strategies for foreign matter (FM) detection in lyophilized products; more specifically, it assesses the reliability of non-destructive technologies for FM detection in dried samples. Emerging technologies applied in other industries, such as various types of spectroscopies and imaging (e.g. chemical, X-ray, ultrasound, thermal and terahertz), are evaluated based on compatibility with the intended application, with identification of the possible technical challenges.

Potential of Raman spectroscopy in facilitating pharmaceutical formulations development - An AI perspective

Drug development is time-consuming and inherently possesses a high failure rate. Pharmaceutical formulation development is the bridge that links a new chemical entity (NCE) to pre-clinical and clinical trials, and has a high impact on the efficacy and safety of the final drug product. Further, the time required for this process is escalating as formulation techniques are becoming more complicated due to the rising demands for drug products with better efficacy and patient compliance, as well as the inherent difficulties of addressing the unfavorable properties of NCEs such as low water solubility. The advent of artificial intelligence (AI) provides possibilities to accelerate the drug development process. In this review, we first examine applications of AI methods in different types of pharmaceutical formulations and formulation techniques. Moreover, as availability of data is the engine for the advancement of AI, we then suggest a potential way (i.e. applying Raman spectroscopy) for faster high-quality data gathering from formulations. Raman techniques have the capability of analyzing the composition and distribution of components and the physicochemical properties thereof within formulations, which are prominent factors governing drug dissolution profiles and subsequently bioavailability. Thus, useful information can be obtained bridging formulation development to the final product quality.

Comparison of Raman and Near-Infrared Chemical Mapping for the Analysis of Pharmaceutical Tablets

Raman and near-infrared (NIR) chemical mapping are widely used methods in the pharmaceutical industry to understand the distribution of components within a drug product. Recent advancements in instrumentation have enabled the rapid acquisition of high-resolution images. The comparison of these techniques for the analysis of pharmaceutical tablets has not recently been explored and thus the relative performance of each technique is not currently well defined. Here, the differences in the chemical images obtained by each method are assessed and compared with scanning electron microscopy with energy dispersive X-ray microanalysis (SEM-EDX), as an alternative surface imaging technique to understand the ability of each technique to acquire a chemical image representative of the sample surface. It was found that the Raman data showed the best agreement with the spatial distribution of components observed in the SEM-EDX images. Quantitative and qualitative comparison of the Raman and NIR images revealed a very different spatial distribution of components with regards to domain size and shape. The Raman image exhibited sharper and better discriminated domains of each component, whereas the NIR image was heavily dominated by large pixelated domains. This study demonstrated the superiority of using Raman chemical mapping compared with NIR chemical mapping to produce a chemical image representative of the sample surface using routinely available instrumentation to obtain a better approximation of domain size and shape. This is fundamental for understanding knowledge gaps in current manufacturing processes; particularly relating the relationship between components in the formulation, processing condition, and final characteristics. By providing a means to more accurately visualize the components within a tablet matrix, these areas can all be further understood.

Forensic analysis of anabolic steroids tablets composition using attenuated total reflection Fourier transform infrared microspectroscopy (µATR-FTIR) mapping

The use of falsified and unregistered drugs is a worldwide public health problem. Because these global market products usually do not follow the Good Manufacturing Practices required by health legislation, its composition may be completely different from the original or may contain relevant concentrations of impurities and toxic contaminants. Since anabolic steroids are among the main irregular therapeutic classes seized in Brazil, here we propose a new methodology for analyzing these products, in tablets form, using Attenuated Total Reflection Fourier Transform Infrared Microspectroscopy (µATR-FTIR) mapping. Spectra were acquired from solid tablets by attenuated total reflection, through point mapping methodology. In data processing, a characteristic absorption band for each Active Pharmaceutical Ingredient (API) was integrated and plotted to create its distribution map. This technique was applied in an unprecedented way for the forensic analysis of anabolic steroids and proved to be effective in distinguishing falsified products based on the detection of their APIs. It was possible to detect APIs in 26 out of 30 samples, five of which were classified as falsified only through µATR-FTIR analysis. We were able to create distribution maps of the detected substances associating the microspectroscopic results with characteristic band integration method, which can be used to detect substances and to study samples' homogeneity. We concluded that this methodology is promising for the analysis of anabolic steroid tablets, and can be used in a complementary way with techniques already consolidated in forensic laboratory routine for a better classification of questioned samples between authentic and falsified ones.

In Vivo Spectral Distortions of Infrared Luminescent Nanothermometers Compromise Their Reliability

Luminescence nanothermometry has emerged over the past decade as an exciting field of research due to its potential applications where conventional methods have demonstrated to be ineffective. Preclinical research has been one of the areas that have benefited the most from the innovations proposed in the field. Nevertheless, certain questions concerning the reliability of the technique under in vivo conditions have been continuously overlooked by most of the scientific community. In this proof-of-concept, hyperspectral in vivo imaging is used to explain how unverified assumptions about the thermal dependence of the optical transmittance of biological tissues in the so-called biological windows can lead to erroneous measurements of temperature. Furthermore, the natural steps that should be taken in the future for a reliable in vivo luminescence nanothermometry are discussed together with a perspective view of the field after the findings here reported.

Terahertz Time of Flight Spectroscopy as a Coating Thickness Reference Method for Partial Least Squares Near Infrared Spectroscopy Models

Near infrared spectroscopy (NIRS) is often used during the tablet coating process to assess coating thickness. As the coating process proceeds, the increase and decrease in NIRS signal from both the coating formulation and tablet core has been related to coating thickness. Partial least-squares models are often generated relating NIRS spectra to reference coating thickness measurements for in-line and/or at-line monitoring of the coating process. This study investigated the effect of the reference coating thickness measurements on the accuracy of the model. The two primary reference techniques used were weight gain-based coating thickness and terahertz-based coating thickness. Most NIRS coating thickness models currently use weight gain-based reference values; however, terahertz-time-of-flight spectroscopy (THz-TOF) offers a more direct reference coating thickness measurement. Results showed that the accuracy of the NIRS coating thickness model significantly improved when terahertz-based coating thickness measurements were used as reference when compared to weight gain-based coating thickness measurements. Therefore, the application of THz-TOF as a reference method is further demonstrated.

Characterization of Zinc Carboxylates in an Oil Paint Test Panel

Zinc (carboxylate) soaps, formed by reactions between zinc oxide (ZnO) and fatty acids in a drying oil, are known to cause deterioration in the paint layers of modern and contemporary oil paintings. This study investigates zinc carboxylates that developed in an oil painting test panel designed to mimic the aging and degradation encountered in actual works of art. Following accelerated and natural aging, protrusions were noted on the surface of the test panel. A large protrusion with erupted gel features was extracted from the test panel, mounted in top view, and then cut to reveal the sample's cross section. The gel features, which resulted from the unreacted oil binder's separation from the paint matrix, facilitated zinc carboxylate formation. Using reflectance μ-FTIR and SEM-EDX analysis, the morphologies and spatial distributions of zinc carboxylates within the gel regions of the protrusion were studied. A concentration gradient of zinc within the gel material was observed in the cross-sectional view, indicating patterns of zinc carboxylate formation and migration.

A novel multivariate curve resolution-alternating least squares (MCR-ALS) methodology for application in hyperspectral Raman imaging analysis

Multivariate curve resolution-alternating least squares (MCR-ALS) applied to hyperspectral Raman imaging is extensively used to spatially and spectrally resolve the individual, pure chemical species within complex, heterogeneous samples. A critical aspect of performing MCR-ALS with hyperspectral Raman imaging is the selection of the number of chemical components within the experimental data. Several methods have previously been proposed to determine the number of chemical components, but it remains a challenging task that if done incorrectly, can lead to the loss of chemical information. In this work, we show that the choice of 'optimal' number of factors in the MCR-ALS model may vary depending on the relative contribution of the targeted species to the overall spectral intensity. In a data set consisting of 27 hyperspectral Raman images of TiO2 polymorphs, it was observed that the more dominant species were best resolved with a parsimonious model. However, species with intensities near the noise level often needed more factors to be resolved than was predicted by standard methods. Based on the observations in this data set, we propose a new method that employs approximate reference spectra for determining optimal model complexity for identifying minor constituents with MCR-ALS.

Characterization of acoustic emission analysis in applications for inhalation device performance assessment

Acoustic Emission (AE) measurement technology has gained wide appreciation in material sciences and process monitoring. In inhalation research, AE has been used for adherence indicating applications in clinical studies. Promising results from feasibility studies using AE combined with multivariate data analysis (AE-MVDA) in the analysis of devices for inhalation have prompted a broader study reported in this paper. This work presents the novel application of AE-MVDA for assessment of the combined inhalation device and formulation performance. The purpose is to evaluate the benefits that this technology can provide to inhalation product development programs. The work was carried out using two different dry powder inhaler device model systems while investigating different performance features. The devices were filled with dry powder formulations with both placebo and with active pharmaceutical ingredient (API). The acquired AE data was analyzed using multivariate data analysis tools such as Principal component analysis (PCA) and orthogonal projections to latent structures (OPLS). The AE profiles were indicative for device and formulation performance. Normal and deviating performances were readily picked up in the AE data. Moreover, performance trends between doses withdrawn from the inhalers were also observable. Lastly, differences in the AE profile between the formulations could be detected. The overall conclusion from the AE-MVDA measurement approach evaluation is that it has the potential to add value as a cost-effective, non-invasive quality and performance monitoring technology both in development and in production of inhaled medicines.

Brillouin Light Scattering: Development of a Near Century-Old Technique for Characterizing the Mechanical Properties of Materials

Brillouin light scattering (BLS), a technique theoretically described nearly a century back by the French physicist Léon Brillouin in 1922, is a light-scattering method for determining the mechanical properties of materials. This inelastic scattering method is described by the Bragg diffraction of light from a propagating fluctuation in the local dielectric. These fluctuations arise spontaneously from thermally populated sound waves intrinsic to all materials, and thus BLS may be broadly applied to transparent samples of any phase. This review begins with a brief historical overview of the development of BLS, from its theoretical prediction to the current state of the art, and notes specific technological advancements that enabled the development of BLS. Despite the broad utility of BLS, no commercial spectrometer is currently available for purchase, but rather individual components are assembled to suit a specific application. Central to any BLS spectrometer is the interferometer, and its performance characteristics-scanning or non-scanning, multi-passing, and stabilization-are critical considerations for spectrometer design. Consistent with any light-scattering method, the frequency shift is a key observable in BLS, and we summarize the connection of this measurement to evaluate the mechanical properties of materials. With emphasis toward pharmaceutical materials analysis, we introduce the traditional BLS approach for single-crystal elasticity, and this is followed by a discussion of more recent developments in powder BLS. We conclude our review with a perspective on future developments in BLS that may enable BLS as a novel addition to the current catalog of process analytical technologies.

Reduction of the influence of film thickness on diffuse reflectance spectroscopy measurement of the tongue

Diffuse reflectance spectroscopy of the tongue contains rich physiological and biochemical information of human status. As it involves contact measurement of the tongue, preventing cross infection during measurement is an important problem to be solved. The use of sterile isolation films is a convenient and efficient way. However, these films can affect the spectral measurement results at the same time. In this paper, to study the influence of films on spectral analysis, a new modeling strategy with good robustness is proposed. The model is established by the use of spectra obtained with different thicknesses of films; thus it is insensitive to the film thickness. The experiment was conducted by gathering spectra of 35 volunteers' tongue using films of different thicknesses. First, the partial least squares method was used to reveal the relationship between the spectral data and the thickness of films. Second, the support vector machine established a classification model between the spectral data and subjects to study the influence of the film. The results showed that the model established by the new modeling strategy could minimize the error caused by variation of the film thickness.

[Applications of Raman Spectroscopy on Quality Control of Hospital Formulations]

Hospital formulation has several advantages, including the flexibility of customization as per the disease state or the patients' precise requirements. However, compared with commercial formulations, hospital formulations are usually not under the same level of quality check. In the present study, we tested mixed powder formulations prepared in a hospital pharmacy using Raman spectroscopy to investigate the feasibility of applying Raman spectroscopy as a quality-control tool of hospital formulations. For this purpose, we first established a numerical evaluation method to determine the uniformity of a powder mixture using Raman chemical imaging data with atropine sulfate/lactose mixture samples and revealed that the mixing uniformity correlated to the experience level of the pharmacist. Next, we developed a content quantification method in a one-dose packaged powder formulation by measuring the Raman spectra from the outside of the package. Because this method allows for quantification of the components inside the package in a non-destructive and non-contact manner, it can be applied for content confirmation after one-dose packaging. Using this method, the content uniformity of the mixed powder formulation in the one-dose package was compared between the formulations prepared by the pharmacists and those prepared by a pharmacy robot. Our study indicates the possibility of applying Raman spectroscopy as a quality-control tool of hospital formulations. Studies on further applications of Raman spectroscopy in the field of clinical pharmacology are expected.

Comparison of different chemometric methods to extract chemical and physical information from Raman images of homogeneous and heterogeneous semi-solid pharmaceutical formulations

In formulations of nanostructured lipid carriers, lipid solid dispersions and self-emulsifying drug delivery systems, it is common that a solid or semi-solid lipid excipient is mixed with a liquid solvent or liquid lipid. Even when the excipients are visually miscible upon melting, they might have microscopic non-homogeneities which could lead to instability over time and future phase separation. Raman mapping associated with chemometric methods can be useful to evaluate spatial distribution of compounds, however it has not been extensively applied to the formulations mentioned above. The aim of this work was to compare the outcomes of three different chemometric methods - principal components analysis (PCA), multivariate curve resolution with alternating least squares (MCR-ALS) and independent components analysis (ICA) - to study two systems of very different degrees of microscopic miscibility: cetyl palmitate + Transcutol^© (heterogeneous) and polyethylene glycol 6000 (PEG 6000) + Tween 80^© (homogeneous). These two samples were chosen due to large differences in spatial distribution of the compounds over the pixels which could require different approaches for data treatment. The three methods were compared regarding recovered concentrations (or scores), signals (or loadings) and the need for matrix augmentation to obtain reliable results. Results showed that PCA loadings were the mathematical differences of the spectra of pure compounds for both samples, and therefore only 'contrast images' could be generated. MCR and ICA provided signals that could be related to the chemical components, however MCR presented rotational ambiguities even for the very heterogeneous sample, a situation in which ICA performed better as a blind search method. For the homogeneous sample, both methods showed rank deficiency and therefore the use of a matrix augmentation was necessary. ICA and PCA allowed identifying physical modifications in the homogeneous semi-solid PEG 6000/Tween 80^® sample over the time, probably due to the folding/unfolding of the crystalline chains of PEG 6000. Therefore, this work discusses the ability of the three chemometrics methods to extract information from Raman spectra in order to characterize the chemical, spatial and even physical aspects of semi-solid pharmaceutical formulations, which could be of much use for stability studies of different drug delivery systems.

Hyperspectral Imaging Using Laser Excitation for Fast Raman and Fluorescence Hyperspectral Imaging for Sorting and Quality Control Applications

A hyperspectral measurement system for the fast and large area measurement of Raman and fluorescence signals was developed, characterized and tested. This laser hyperspectral imaging system (Laser-HSI) can be used for sorting tasks and for continuous quality monitoring. The system uses a 532 nm Nd:YAG laser and a standard pushbroom HSI camera. Depending on the lens selected, it is possible to cover large areas (e.g., field of view (FOV) = 386 mm) or to achieve high spatial resolutions (e.g., 0.02 mm). The developed Laser-HSI was used for four exemplary experiments: (a) the measurement and classification of a mixture of sulphur and naphthalene; (b) the measurement of carotenoid distribution in a carrot slice; (c) the classification of black polymer particles; and, (d) the localization of impurities on a lead zirconate titanate (PZT) piezoelectric actuator. It could be shown that the measurement data obtained were in good agreement with reference measurements taken with a high-resolution Raman microscope. Furthermore, the suitability of the measurements for classification using machine learning algorithms was also demonstrated. The developed Laser-HSI could be used in the future for complex quality control or sorting tasks where conventional HSI systems fail.

Clinical infrared microscopic imaging: An overview

New developments in Mid-infrared microscopic imaging instrumentation and data analysis have turned this method into a conventional technique. This imaging method offers a global analysis of samples, with a resolution close to the cellular level enabling the acquisition of local molecular expression profiles. It is possible to get chemo-morphological information about the tissue status, which represents an essential benefit for future analytical interpretation of pathological changes of tissue. In this review, we give an overview of Mid-infrared microscopic imaging and its applications in clinical research.

Recent advances in the applications of vibrational spectroscopic imaging and mapping to pharmaceutical formulations

Vibrational spectroscopic imaging and mapping approaches have continued in their development and applications for the analysis of pharmaceutical formulations. Obtaining spatially resolved chemical information about the distribution of different components within pharmaceutical formulations is integral for improving the understanding and quality of final drug products. This review aims to summarise some key advances of these technologies over recent years, primarily since 2010. An overview of FTIR, NIR, terahertz spectroscopic imaging and Raman mapping will be presented to give a perspective of the current state-of-the-art of these techniques for studying pharmaceutical samples. This will include their application to reveal spatial information of components that reveals molecular insight of polymorphic or structural changes, behaviour of formulations during dissolution experiments, uniformity of materials and detection of counterfeit products. Furthermore, new advancements will be presented that demonstrate the continuing novel applications of spectroscopic imaging and mapping, namely in FTIR spectroscopy, for studies of microfluidic devices. Whilst much of the recently developed work has been reported by academic groups, examples of the potential impacts of utilising these imaging and mapping technologies to support industrial applications have also been reviewed.

Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) with Raman Imaging Applied to Lunar Meteorites

Lunar meteorites provide a more random sampling of the surface of the Moon than do the returned lunar samples, and they provide valuable information to help estimate the chemical composition of the lunar crust, the lunar mantle, and the bulk Moon. As of July 2014, ∼96 lunar meteorites had been documented and ten of these are unbrecciated mare basalts. Using Raman imaging with multivariate curve resolution-alternating least squares (MCR-ALS), we investigated portions of polished thin sections of paired, unbrecciated, mare-basalt lunar meteorites that had been collected from the LaPaz Icefield (LAP) of Antarctica-LAP 02205 and LAP 04841. Polarized light microscopy displays that both meteorites are heterogeneous and consist of polydispersed sized and shaped particles of varying chemical composition. For two distinct probed areas within each meteorite, the individual chemical species and associated chemical maps were elucidated using MCR-ALS applied to Raman hyperspectral images. For LAP 02205, spatially and spectrally resolved clinopyroxene, ilmenite, substrate-adhesive epoxy, and diamond polish were observed within the probed areas. Similarly, for LAP 04841, spatially resolved chemical images with corresponding resolved Raman spectra of clinopyroxene, troilite, a high-temperature polymorph of anorthite, substrate-adhesive epoxy, and diamond polish were generated. In both LAP 02205 and LAP 04841, substrate-adhesive epoxy and diamond polish were more readily observed within fractures/veinlet features. Spectrally diverse clinopyroxenes were resolved in LAP 04841. Factors that allow these resolved clinopyroxenes to be differentiated include crystal orientation, spatially distinct chemical zoning of pyroxene crystals, and/or chemical and molecular composition. The minerals identified using this analytical methodology-clinopyroxene, anorthite, ilmenite, and troilite-are consistent with the results of previous studies of the two meteorites using electron microprobe analysis. To our knowledge, this is the first report of MCR-ALS with Raman imaging used for the investigation of both lunar and other types of meteorites. We have demonstrated the use of multivariate analysis methods, namely MCR-ALS, with Raman imaging to investigate heterogeneous lunar meteorites. Our analytical methodology can be used to elucidate the chemical, molecular, and structural characteristics of phases in a host of complex, heterogeneous geological, geochemical, and extraterrestrial materials.

Raman chemical imaging for spectroscopic screening and direct quantification of falsified drugs

Falsified drugs are a threat to the health of patients. The analytical control of such products contributes to the fight against this global issue. Raman chemical imaging is a method that relies on consecutive measurements at the surface of a sample, combining spectroscopy, microscopy and chemometrics. This article explores the capabilities of this analytical technique proposing an innovative methodology with spectroscopic screening for the identification of chemical compounds and the direct quantification of the active substance (without prior calibration). Two chemometric methods were used: Multivariate Curve Analysis - Alternate Least Squares for the qualitative analysis and Direct Classical Least Squares for the quantitative analysis. The methodology was optimized with samples prepared in the laboratory and validation parameters were studied. The methodology was then applied to real (authentic and falsified) samples of Viagra^® and Plavix^®. Despite the presence of fluorescence emission in some samples, the methodology succeeded in the detection of active pharmaceutical ingredients, and in the discrimination of three salts of clopidogrel (in generic formulations of Plavix^®). The quantitative deviation from the reference method ranged from -15% to +24% of the active substance content. This deviation may be considered to be acceptable since it is sufficient for assessing the risk to the health of patients and for quickly alerting the health authorities.

UV imaging of multiple unit pellet system (MUPS) tablets: A case study of acetylsalicylic acid stability

The applicability of multispectral ultraviolet (UV) imaging in combination with multivariate image analysis was investigated to monitor API degradation within multiple unit pellet system (MUPS) tablets during storage. For this purpose, acetylsalicylic acid (ASA) layered pellets were coated with Eudragit® RL PO and compressed to MUPS tablets. These tablets were stored under four different conditions with different levels of relative humidity (0 and 75%) and temperature (21 and 40°C) and analysed at seven storage time points (0, 15, 40, 140, 165, 265, and 330d). The UV imaging results for estimation of the salicylic acid (SA) concentration as degradation product of ASA in the tablets were compared to the SA concentration measured by high performance liquid chromatography with a partial least squares regression resulting in an RMSEP of 4.86% and an R² of 0.9812. The estimation of the SA concentration based on mean UV reflectance spectra was possible even through the coating of the API pellets and at low concentration levels. In addition, the distribution of the SA concentration on the tablet surfaces for different storage time periods was visualized. UV imaging as fast and non-destructive method appears to offer significant potential for monitoring of API degradation during stability studies.