Quantitative analysis of solid dosage forms of Atenolol by Raman spectroscopy

OBJECTIVE

To develop a Raman spectroscopy-based analytical model for quantification of solid dosage forms of active pharmaceutical ingredient (API) of Atenolol.Significance: For the quantitative analysis of pharmaceutical drugs, Raman Spectroscopy is a reliable and fast detection method. As part of this study, Raman Spectroscopy is explored for the quantitative analysis of different concentrations of Atenolol.

METHODS

Various solid-dosage forms of Atenolol were prepared by mixing API with excipients to form different solid-dosage formulations of Atenolol. Multivariate data analysis techniques, such as Principal Component Analysis (PCA) and Partial least square regression (PLSR) were used for the qualitative and quantitative analysis, respectively.

RESULTS

As the concentration of the drug increased in formulation, the peak intensities of the distinctive Raman spectral characteristics associated with the API (Atenolol) gradually increased. Raman spectral data sets were classified using PCA due to their distinctive spectral characteristics. Additionally, a prediction model was built using PLSR analysis to assess the quantitative relationship between various API (Atenolol) concentrations and spectral features. With a goodness of fit value of 0.99, the root mean square errors of calibration (RMSEC) and prediction (RMSEP) were determined to be 1.0036 and 2.83 mg, respectively. The API content in the blind/unknown Atenolol formulation was determined as well using the PLSR model.

CONCLUSIONS

Based on these results, Raman spectroscopy may be used to quickly and accurately analyze pharmaceutical samples and for their quantitative determination.

Spectral encoder to extract the efficient features of Raman spectra for reliable and precise quantitative analysis

Raman spectroscopy has become a powerful analytical tool highly demanded in many applications such as microorganism sample analysis, food quality control, environmental science, and pharmaceutical analysis, owing to its non-invasiveness, simplicity, rapidity and ease of use. Among them, quantitative research using Raman spectroscopy is a crucial application field of spectral analysis. However, the entire process of quantitative modeling largely relies on the extraction of effective spectral features, particularly for measurements on complex samples or in environments with poor spectral signal quality. In this paper, we propose a method of utilizing a spectral encoder to extract effective spectral features, which can significantly enhance the reliability and precision of quantitative analysis. We built a latent encoded feature regression model; in the process of utilizing the autoencoder for reconstructing the spectrometer output, the latent feature obtained from the intermediate bottleneck layer is extracted. Then, these latent features are fed into a deep regression model for component concentration prediction. Through detailed ablation and comparative experiments, our proposed model demonstrates superior performance to common methods on single-component and multi-component mixture datasets, remarkably improving regression precision while without needing user-selected parameters and eliminating the interference of irrelevant and redundant information. Furthermore, in-depth analysis reveals that latent encoded feature possesses strong nonlinear feature representation capabilities, low computational costs, wide adaptability, and robustness against noise interference. This highlights its effectiveness in spectral regression tasks and indicates its potential in other application fields. Sufficient experimental results show that our proposed method provides a novel and effective feature extraction approach for spectral analysis, which is simple, suitable for various methods, and can meet the measurement needs of different real-world scenarios.

Raman Spectroscopy for the Quantitative Analysis of Solid Dosage Forms of the Active Pharmaceutical Ingredient of Febuxostat

Raman spectroscopy has been used to characterize and quantify the solid dosage forms of the commercially available drug febuxostat. For this purpose, different formulations consisting of the febuxostat (API) and excipients with different concentrations of the API are prepared and analyzed by Raman spectroscopy to identify different spectral features related to the febuxostat API and excipients. Multivariate data analysis tools such as principal component analysis (PCA) and partial least-squares regression (PLSR) analysis are used for qualitative and quantitative analyses. PCA has been found to be useful for the qualitative monitoring of various solid dosage forms. PLSR analysis has led to the successful prediction of API concentration in the unknown samples with a sensitivity and a selectivity of 98 and 99%, respectively. Moreover, the root-mean-square error (RMSE) of calibration and validation of the PLSR model has been found to be 2.9033 and 1.35, respectively. Notably, it is found to be very helpful for the comparison between the self-made formulations of febuxostat and commercially available febuxostat tablets (40 and 80 mg) of two different brands (Gouric and Zurig). These results showed that Raman spectroscopy can be a useful and reliable technique for identifying and quantifying the active pharmaceutical ingredient (API) in commercially available solid dosage forms.

Microfluidic SERS devices: brightening the future of bioanalysis

A new avenue has opened up for applications of surface-enhanced Raman spectroscopy (SERS) in the biomedical field, mainly due to the striking advantages offered by SERS tags. SERS tags provide indirect identification of analytes with rich and highly specific spectral fingerprint information, high sensitivity, and outstanding multiplexing potential, making them very useful in in vitro and in vivo assays. The recent and innovative advances in nanomaterial science, novel Raman reporters, and emerging bioconjugation protocols have helped develop ultra-bright SERS tags as powerful tools for multiplex SERS-based detection and diagnosis applications. Nevertheless, to translate SERS platforms to real-world problems, some challenges, especially for clinical applications, must be addressed. This review presents the current understanding of the factors influencing the quality of SERS tags and the strategies commonly employed to improve not only spectral quality but the specificity and reproducibility of the interaction of the analyte with the target ligand. It further explores some of the most common approaches which have emerged for coupling SERS with microfluidic technologies, for biomedical applications. The importance of understanding microfluidic production and characterisation to yield excellent device quality while ensuring high throughput production are emphasised and explored, after which, the challenges and approaches developed to fulfil the potential that SERS-based microfluidics have to offer are described.

Combining fiber optical tweezers and Raman spectroscopy for rapid identification of melanoma

Cutaneous melanoma is a skin tumor with a high degree of malignancy and fatality rate, the incidence of which has increased in recent years. Therefore, a rapid and sensitive diagnostic technique of melanoma cells is urgently needed. In this paper, we present a new approach using fiber optical tweezers to manipulate melanoma cells to measure their Raman spectra. Then, combined with Principal Component Analysis and Support Vector Machines (PCA-SVM) classification model, to achieve the classification of common mutant, wild-type and drug-resistant melanoma cells. A total of 150 Raman spectra of 30 cells were collected from mutant, wild-type and drug-resistant melanoma cell lines, and the classification accuracy was 92%, 94%, 97.5%, respectively. These results suggest that the study of tumor cells based on fiber optical tweezers and Raman spectroscopy is a promising method for early and rapid identification and diagnosis of tumor cells.

Generic Chemometric Models for Metabolite Concentration Prediction Based on Raman Spectra

Chemometric models for on-line process monitoring have become well established in pharmaceutical bioprocesses. The main drawback is the required calibration effort and the inflexibility regarding system or process changes. So, a recalibration is necessary whenever the process or the setup changes even slightly. With a large and diverse Raman dataset, however, it was possible to generate generic partial least squares regression models to reliably predict the concentrations of important metabolic compounds, such as glucose-, lactate-, and glutamine-indifferent CHO cell cultivations. The data for calibration were collected from various cell cultures from different sites in different companies using different Raman spectrophotometers. In testing, the developed “generic” models were capable of predicting the concentrations of said compounds from a dilution series in FMX-8 mod medium, as well as from an independent CHO cell culture. These spectra were taken with a completely different setup and with different Raman spectrometers, demonstrating the model flexibility. The prediction errors for the tests were mostly in an acceptable range (<10% relative error). This demonstrates that, under the right circumstances and by choosing the calibration data carefully, it is possible to create generic and reliable chemometric models that are transferrable from one process to another without recalibration.

Combining Pharmacokinetics and Vibrational Spectroscopy: MCR-ALS Hard-and-Soft Modelling of Drug Uptake In Vitro Using Tailored Kinetic Constraints

Raman microspectroscopy is a label-free technique which is very suited for the investigation of pharmacokinetics of cellular uptake, mechanisms of interaction, and efficacies of drugs in vitro. However, the complexity of the spectra makes the identification of spectral patterns associated with the drug and subsequent cellular responses difficult. Indeed, multivariate methods that relate spectral features to the inoculation time do not normally take into account the kinetics involved, and important theoretical information which could assist in the elucidation of the relevant spectral signatures is excluded. Here, we propose the integration of kinetic equations in the modelling of drug uptake and subsequent cellular responses using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and tailored kinetic constraints, based on a system of ordinary differential equations. Advantages of and challenges to the methodology were evaluated using simulated Raman spectral data sets and real Raman spectra acquired from A549 and Calu-1 human lung cells inoculated with doxorubicin, in vitro. The results suggest a dependency of the outcome on the system of equations used, and the importance of the temporal resolution of the data set to enable the use of complex equations. Nevertheless, the use of tailored kinetic constraints during MCR-ALS allowed a more comprehensive modelling of the system, enabling the elucidation of not only the time-dependent concentration profiles and spectral features of the drug binding and cellular responses, but also an accurate computation of the kinetic constants.

Advancing Raman spectroscopy from research to clinic: Translational potential and challenges

Raman spectroscopy has emerged as a non-invasive and versatile diagnostic technique due to its ability to provide molecule-specific information with ultrahigh sensitivity at near-physiological conditions. Despite exhibiting substantial potential, its translation from optical bench to clinical settings has been impacted by associated limitations. This perspective discusses recent clinical and biomedical applications of Raman spectroscopy and technological advancements that provide valuable insights and encouragement for resolving some of the most challenging hurdles.

Reusable and highly sensitive SERS immunoassay utilizing gold nanostars and a cellulose hydrogel-based platform

The development of robust and sensitive point-of-care testing platforms is necessary to improve patient care and outcomes. Surface-enhanced Raman scattering (SERS)-based immunosensors are especially suited for this purpose. Here, we present a highly sensitive and selective SERS immunoassay, demonstrating for example the detection of horseradish peroxidase (HRP), in a sandwich format. The strength of our biosensor lies in merging: (i) SERS-immunotags based on gold nanostars, allowing exceptional intense SERS from attached Raman probes, covalent attachment of anti-HRP antibodies by a simple chemical method providing exceptional antigen binding activity; (ii) the ease of preparation of the capture platform from a regenerated cellulose-based hydrogel, a transparent material, ideal for microfluidics applications, with low background fluorescence and Raman signal, particularly suited for preserving high activity of the covalently bound anti-HRP antibodies. The sandwich complexes formed were characterised by atomic force microscopy, and by scanning electron microscopy coupled with electron diffraction spectroscopy; and (iii) the robustness of the simple Classical Least Squares method for SERS data analysis, resulting in superior discrimination of SERS signals from the background and much better data fitting, compared to the commonly used peak integral method. Our SERS immunoassay greatly improves the detection limits of traditional enzyme-linked immunosorbent assay approaches, and its performance is better or comparable to those of existing SERS-based immunosensors. Our approach successfully overcomes the main challenges of application at point-of-care, including increasing reproducibility, sensitivity, and specificity, associated with an environmentally friendly and robust design. Also, the proposed design withstands several cycles of regeneration, a feature absent in paper-SERS immunoassays and this opens the way for sensitive multiplexing applications on a microfluidic platform.

Monitoring the biochemical changes occurring to human keratinocytes exposed to solar radiation by Raman spectroscopy

Solar radiation exposure is recognised to be a significant contributor to the development of skin cancer. Monitoring the simultaneous and consecutive mechanisms of interaction could provide a greater understanding of the process of photocarcinogenesis. This work presents an analysis of the biochemical and morphological changes occurring to immortalised human epithelial keratinocyte (HaCaT) cell cultures exposed to simulated solar radiation (SSR). Cell viability was monitored with the aid of the Alamar Blue assay, morphological examination was done with haematoxylin and eosin staining (H&E) and changes to the biochemical constituents (nucleic acids and proteins) as a result of the radiation insult were demonstrated through a combination of Raman microspectroscopy and multivariate analysis of spectral patterns. The spectral results suggest that SSR induces changes to the conformational structure of DNA as an immediate result of the radiation, whereas alteration in the protein signature is mostly seen as a later response.

Quantitative analysis of human blood serum using vibrational spectroscopy

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State of the art of quantitative Vibrational Spectroscopic analysis of human blood serum is reviewed.

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Technical considerations for infrared absorption and Raman analysis are discussed.

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Quantitative analyses of Endogenous and Exogenous constituents are presented.

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The potential for clinical translation of spectroscopic serology is argued.

Analysis of bodily fluids using vibrational spectroscopy has attracted increasing attention in recent years. In particular, infrared spectroscopic screening of blood products, particularly blood serum, for disease diagnostics has been advanced considerably, attracting commercial interests. However, analyses requiring quantification of endogenous constituents or exogenous agents in blood are less well advanced. Recent advances towards this end are reviewed, focussing on infrared and Raman spectroscopic analyses of human blood serum. The importance of spectroscopic analysis in the native aqueous environment is highlighted, and the relative merits of infrared absorption versus Raman spectroscopy are considered, in this context. It is argued that Raman spectroscopic analysis is more suitable to quantitative analysis in liquid samples, and superior performance for quantification of high and low molecular weight components, is demonstrated. Applications for quantitation of viral loads, and therapeutic drug monitoring are also discussed.

Biomolecular and bioanalytical applications of infrared spectroscopy - A review

Infrared (IR; or mid-infrared, MIR; 4000-400 cm^-1; 2500-25,000 nm) spectroscopy has become one of the most powerful and versatile tools at the disposal of modern bioscience. Because of its high molecular specificity, applicability to wide variety of samples, rapid measurement and non-invasivity, IR spectroscopy forms a potent approach to elucidate qualitative and quantitative information from various kinds of biological material. For these reasons, it became an established bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of the recent accomplishments in the field of biomolecular and bioanalytical IR spectroscopy. That progress is presented on a wider background, with fundamental characteristics, the basic principles of the technique outlined, and its scientific capability directly compared with other methods being used in similar fields (e.g. near-infrared, Raman, fluorescence). The article aims to present a complete examination of the topic, as it touches the background phenomena, instrumentation, spectra processing and data analytical methods, spectra interpretation and related information. To suit this goal, the article includes a tutorial information essential to obtain a thorough perspective of bio-related applications of the reviewed methodologies. The importance of the fundamental factors to the final performance and applicability of IR spectroscopy in various areas of bioscience is explained. This information is interpreted in critical way, with aim to gain deep understanding why IR spectroscopy finds extraordinarily intensive use in this remarkably diverse and dynamic field of research and utility. The major focus is placed on the diversity of the applications in which IR biospectroscopy has been established so far and those onto which it is expanding nowadays. This includes qualitative and quantitative analytical spectroscopy, spectral imaging, medical diagnosis, monitoring of biophysical processes, and studies of physicochemical properties and dynamics of biomolecules. The application potential of IR spectroscopy in light of the current accomplishments and the future prospects is critically evaluated and its significance in the progress of bioscience is comprehensively presented.

Raman Spectroscopy for Rapid Evaluation of Surgical Margins during Breast Cancer Lumpectomy

Failure to precisely distinguish malignant from healthy tissue has severe implications for breast cancer surgical outcomes. Clinical prognoses depend on precisely distinguishing healthy from malignant tissue during surgery. Laser Raman spectroscopy (LRS) has been previously shown to differentiate benign from malignant tissue in real time. However, the cost, assembly effort, and technical expertise needed for construction and implementation of the technique have prohibited widespread adoption. Recently, Raman spectrometers have been developed for non-medical uses and have become commercially available and affordable. Here we demonstrate that this current generation of Raman spectrometers can readily identify cancer in breast surgical specimens. We evaluated two commercially available, portable, near-infrared Raman systems operating at excitation wavelengths of either 785 nm or 1064 nm, collecting a total of 164 Raman spectra from cancerous, benign, and transitional regions of resected breast tissue from six patients undergoing mastectomy. The spectra were classified using standard multivariate statistical techniques. We identified a minimal set of spectral bands sufficient to reliably distinguish between healthy and malignant tissue using either the 1064 nm or 785 nm system. Our results indicate that current generation Raman spectrometers can be used as a rapid diagnostic technique distinguishing benign from malignant tissue during surgery.

Qualitative and quantitative analysis of therapeutic solutions using Raman and infrared spectroscopy

Anticancer drugs are prescribed and administrated to an increasing number of patients on a daily basis. As a consequence, a number of concerns have been raised about the patient health and safety in the case that the drugs administered are not at the required concentration or even worse not the correct ones. Quality control of therapeutic solutions has therefore been extensively implemented in hospital environments, in order to avoid any failure in the intense workflow faced by administering pharmacists. In the present study, infrared (IR) and Raman spectroscopy have been employed for the analysis of 3 commercially available therapeutic solutions TEVA®, MYLAN®, CERUBIDINE®, respectively containing doxorubicin, epirubicin and daunorubicin. They perfectly illustrate the analytical difficulties encountered, as these 3 chemotherapeutic drugs are isomers, hardly distinguishable with conventional approaches such as UV/VIS spectrometry. Any analytical failure to identify these molecules can lead to delays in patient treatment. While Partial Least Squares Regression analysis demonstrates that both Raman and IR can deliver satisfactory quantitative analysis in the clinical range, with respective Root Mean Square Error of Cross Validation (RMSECV) between 0.0127 - 0.0220 g·L^-1 and 0.0573 - 0.0759 g·L^-1, the identification rate between the 2 techniques differs substantially. Indeed, Principal Component Analysis - Factorial Discriminant Analysis (PCA-FDA) highlights that, depending on the data preprocessing applied to Raman spectra, the discrimination between the 3 drugs is decreased, with in some cases specificity and sensitivity below 50%. However, IR analysis displays encouraging results with an overall specificity and sensitivity between 99 and 100%, suggesting that reliable validation of the therapeutic solution for administration to patients can be achieved. IR and Raman spectroscopy could assist and support quality control of chemotherapeutic solutions prepared in personalised concentrations for each patient. The effective and reliable characterisation of therapeutic solutions could have a lot to offer to improve current practices in a near future.

ATR-IR coupled to partial least squares regression (PLSR) for monitoring an encapsulated active molecule in complex semi-solid formulations

Attenuated Total Reflectance-Infrared (ATR-IR) spectroscopy holds great promise for industrial applications as a quality control tool for complex galenic formulations. Although the technique is often promoted for the molecular information it delivers in a label free and cost effective fashion, other advantages can emerge compared to the gold standard analytical tools such as liquid chromatography coupled to mass spectrometry. The present study demonstrates how ATR-IR measurements enable accurate quantitative analysis of an active cosmetic ingredient such as Omegalight® encapsulated in a complex alginate based nano-capsule. The study demonstrates how precise concentrations can be obtained without the requirement for fastidious extraction and separation protocols prior to ATR-IR analysis. However, data mining remains a crucial aspect with particular emphasis on the preprocessing of the data that will be subjected to Partial Least Squares Regression (PLSR) analysis. Therefore, different pre-processing methods have been evaluated to investigate the relationship between corrections applied and PLSR outcomes (i.e. precision, ratio of performance to deviation (RPD) and accuracy of the analysis). Ultimately, it has been found that, against all expectations, some of the preprocessing methods do not necessarily lead to improvements in the end result, while Extended Multiplicative Scattering Correction (EMSC) is the only one which delivers satisfying results, as defined by a Root Mean Square Error (RMSEV) of 0.07% (w/w) and a RPD greater than 30 when performing analysis over the range 0.4-8.2% (w/w). Despite the presence of large amounts of additives such as glycerol and preservatives in the formulation, implementing Leave One Out Cross Validation (LOOCV) further validates the method with a RPD of 18 and relative errors for the predicted concentrations below the 5% (w/w) threshold, hence demonstrating that ATR-IR has analytical capabilities for applications in the cosmetic industry.

Fast and Quantitative Analysis of Ediphenphos Residue in Rice Using Surface-Enhanced Raman Spectroscopy

Detection of residual farm chemicals in agricultural crops is a hot topic in the field of food safety. In this study, ediphenphos residue in rice was detected using surface-enhanced Raman spectroscopy (SERS) on a portable Raman spectrometer. A simple pretreatment method for rice samples was developed, and uniform gold nanorods were used for SERS measurement. Characteristic signals can still be detected when ediphenphos concentration in rice extraction solution was higher than or equal to 0.1 mg/L. Quantitative analysis of ediphenphos was conducted by regression models developed using partial least-squares regression, random forest and kernel principal component analysis, and root-mean-square error of cross validation, coefficient of determination and relative predicted deviation of optimal model were 0.022 mg/L, 0.9967 and 297.45, which indicated the proposed method can predict ediphenphos concentration with high precision. To validate the feasibility of practical application further, rice samples spiked with 10, 5, 1, 0.5, and 0.1 μg/g ediphenphos residue were analyzed using the above method. The predicted recovery was in the range of 93.4% to 102%, and the predicted error was small for residue of each concentration. These results demonstrated that the presented method could be used for accurate and quantitative detection of ediphenphos residue in rice.

PRACTICAL APPLICATION

This study developed a surface-enhanced Raman spectroscopy (SERS) method for detection of ediphenphos in rice coupled with simple extraction protocol and gold nanorods on a portable Raman spectrometer. SERS is a rapid and accurate method which can be applied in agricultural grain safety inspection.

In vitro label-free screening of chemotherapeutic drugs using Raman microspectroscopy: Towards a new paradigm of spectralomics

This overview groups some of the recent studies highlighting the potential application of Raman microspectroscopy as an analytical technique in preclinical development to predict drug mechanism of action and in clinical application as a companion diagnostic and in personalised therapy due to its capacity to predict cellular resistance and therefore to optimise chemotherapeutic treatment efficacy. Notably, the anthracyclines, doxorubicin and actinomycin D, elicit similar spectroscopic signatures of subcellular interaction characteristic of the mode of action of intercalation. Although cisplatin and vincristine show markedly different signatures, at low exposure doses, their signatures at higher doses show marked similarities to those elicited by the intercalating anthracyclines, confirming that anticancer agents can have different modes of action with different spectroscopic signatures, depending on the dose. The study demonstrates that Raman microspectroscopy can elucidate subcellular transport and accumulation pathways of chemotherapeutic agents, characterise and fingerprint their mode of action, and potentially identify cell-resistant strains. The consistency of the spectroscopic signatures for drugs of similar modes of action, in different cell lines, suggests that this fingerprint can be considered a "spectralome" of the drug-cell interaction suggesting a new paradigm of representing spectroscopic responses.

An in vitro study of the interaction of the chemotherapeutic drug Actinomycin D with lung cancer cell lines using Raman micro-spectroscopy

The applications of Raman microspectroscopy have been extended in recent years into the field of clinical medicine, and specifically in cancer research, as a non-invasive diagnostic method in vivo and ex vivo, and the field of pharmaceutical development as a label-free predictive technique for new drug mechanisms of action in vitro. To further illustrate its potential for such applications, it is important to establish its capability to fingerprint drug mechanisms of action and different cellular reactions. In this study, cytotoxicity assays were employed to establish the toxicity profiles for 48 and 72 hours exposure of lung cancer cell lines, A549 and Calu-1, after exposure to Actinomycin D (ACT) and Raman micro-spectroscopy was used to track its mechanism of action at subcellular level and subsequent cellular responses. Multivariate data analysis was used to elucidate the spectroscopic signatures associated with ACT chemical binding and cellular resistances. Results show that the ACT uptake and mechanism of action are similar in the 2 cell lines, while A549 cells exhibits spectral signatures of resistance to apoptosis related to its higher chemoresistance to the anticancer drug ACT. The observations are discussed in comparison to previous studies of the similar anthracyclic chemotherapeutic agent Doxorubicin. A, Preprocessed Raman spectrum of ACT stock solution dissolved in sterile water and mean spectrum with SD of (B) nucleolus, (C) nucleus and (D) cytoplasm of A549 cell lines after 48 hours exposure to the corresponding IC₅₀ .

Laser Tweezers Raman Microspectroscopy of Single Cells and Biological Particles

Laser tweezers Raman spectroscopy (LTRS) is a variation of micro-Raman spectroscopy that is used to analyze single cells and biological particles suspended in an aqueous environment. The Raman spectrum of the cell/particle reflects its intrinsic biochemical composition and molecular structures. The technique utilizes a laser trap generated by a tightly focused Gaussian laser beam to physically manipulate individual cells and immobilize them in the laser focal volume. The same laser that is used for optical trapping also simultaneously excites Raman signals from the trapped cell, which are detected using a spectrometer and a confocal detection setup. LTRS offers unique capabilities not commonly found in other optical cytometry methods, such as label-free chemical analysis, multi-parametric chemical detection with a single excitation laser, and a non-photobleaching signal that can be used to quantitate and monitor dynamic chemical changes. This chapter provides guidelines on the design of a single beam LTRS microscope and methods for building and aligning the system. Operating procedures for trapping particles and acquiring spectra and a summary of data analysis techniques are provided.

Quantitative analysis of curcumin-loaded alginate nanocarriers in hydrogels using Raman and attenuated total reflection infrared spectroscopy

Core-shell nanocarriers are increasingly being adapted in cosmetic and dermatological fields, aiming to provide an increased penetration of the active pharmaceutical or cosmetic ingredients (API and ACI) through the skin. In the final form, the nanocarriers (NC) are usually prepared in hydrogels, conferring desired viscous properties for topical application. Combined with the high chemical complexity of the encapsulating system itself, involving numerous ingredients to form a stable core and quantifying the NC and/or the encapsulated active without labor-intensive and destructive methods remains challenging. In this respect, the specific molecular fingerprint obtained from vibrational spectroscopy analysis could unambiguously overcome current obstacles in the development of fast and cost-effective quality control tools for NC-based products. The present study demonstrates the feasibility to deliver accurate quantification of the concentrations of curcumin (ACI)-loaded alginate nanocarriers in hydrogel matrices, coupling partial least square regression (PLSR) to infrared (IR) absorption and Raman spectroscopic analyses. With respective root mean square errors of 0.1469 ± 0.0175% w/w and 0.4462 ± 0.0631% w/w, both approaches offer acceptable precision. Further investigation of the PLSR results allowed to highlight the different selectivity of each approach, indicating only IR analysis delivers direct monitoring of the NC through the quantification of the Labrafac®, the main NC ingredient. Raman analyses are rather dominated by the contribution of the ACI which opens numerous perspectives to quantify the active molecules without interferences from the complex core-shell encapsulating systems thus positioning the technique as a powerful analytical tool for industrial screening of cosmetic and pharmaceutical products. Graphical abstract Quantitative analysis of encapuslated active molecules in hydrogel-based samples by means of infrared and Raman spectroscopy.

Spectral pre and post processing for infrared and Raman spectroscopy of biological tissues and cells

This review presents the current understanding of the factors influencing the quality of spectra recorded and the pre-processing steps commonly employed to improve on spectral quality, as well as some of the most common techniques for classification and analysis of the spectral data for biomedical applications.

Toward SERS-based point-of-care approaches for therapeutic drug monitoring: the case of methotrexate

To date, in spite of their toxicity, the plasmatic concentration of most chemotherapeutic drugs is difficult to monitor in oncological patients, because their quantitative determination is expensive and time consuming. This contribution reports a first attempt for the direct quantitative determination of a chemotherapeutic drug in human serum samples by means of Surface Enhanced Raman Spectroscopy (SERS). In this study, SERS substrates constituted by Au nanoparticles deposited on paper by a simple dipping method have been used for rapid (few minutes) analysis of diluted human serum spiked with different concentrations of methotrexate, MTX. The drug concentrations were chosen in a range designed to cover typical therapeutic plasmatic values (from nanomolar to millimolar) in oncological patients, and the pertinent calibration was obtained by Partial Least-Squares Regression (PLSR). Stability selection was employed to evaluate the capability of the PLSR model to accurately predict and extract spectral variations correlated to MTX concentration. Such a quantitative determination is crucial for frequent, and hence adherent, therapeutic drug monitoring, TDM, of chemiotherapic drugs, given their heavy side effects. Its low cost, rapid response and the possibility of obtaining spectra with simple and compact instruments, make SERS particularly apt for implementing effective TDM. The promising results obtained in the analytical validation indicate which steps are to be taken on the way toward a clinical validation with real samples from oncological patients, for MTX as well as for other chemotherapeutic drugs.

Raman micro spectroscopy for in vitro drug screening: subcellular localisation and interactions of doxorubicin

Raman spectroscopy is used for the localization and tracking of chemotherapeutic drug, doxorubicin, in the intracellular environment of lung cancer cell line. Results show the potential of the technique to monitor the mechanisms of action and response on a molecular level, with subcellular resolution.

Spectropathology for the next generation: Quo vadis?

Vibrational spectroscopy for biomedical applications has shown great promise although its translation into clinical practice has, as yet, been relatively slow. This Editorial assesses the challenges facing the field and the potential way forward.