Development of a univariate calibration model for pharmaceutical analysis based on NIR spectra

Near-infrared spectroscopy (NIRS) has been widely used in the pharmaceutical field because of its ability to provide quality information about drugs in near-real time. In practice, however, the NIRS technique requires construction of multivariate models in order to correct collinearity and the typically poor selectivity of NIR spectra. In this work, a new methodology for constructing simple NIR calibration models has been developed, based on the spectrum for the target analyte (usually the active principle ingredient, API), which is compared with that of the sample in order to calculate a correlation coefficient. To this end, calibration samples are prepared spanning an adequate concentration range for the API and their spectra are recorded. The model thus obtained by relating the correlation coefficient to the sample concentration is subjected to least-squares regression. The API concentration in validation samples is predicted by interpolating their correlation coefficients in the straight calibration line previously obtained. The proposed method affords quantitation of API in pharmaceuticals undergoing physical changes during their production process (e.g. granulates, and coated and non-coated tablets). The results obtained with the proposed methodology, based on correlation coefficients, were compared with the predictions of PLS1 calibration models, with which a different model is required for each type of sample. Error values lower than 1-2% were obtained in the analysis of three types of sample using the same model; these errors are similar to those obtained by applying three PLS models for granules, and non-coated and coated samples. Based on the outcome, our methodology is a straightforward choice for constructing calibration models affording expeditious prediction of new samples with varying physical properties. This makes it an effective alternative to multivariate calibration, which requires use of a different model for each type of sample, depending on its physical presentation.     

Challenging Near InfraRed Spectroscopy discriminating ability for counterfeit pharmaceuticals detection

This study was initiated by the laboratories and control department of the French Health Products Safety Agency (AFSSAPS) as part of the fight against the public health problem of rising counterfeit and imitation medicines. To test the discriminating ability of Near InfraRed Spectroscopy (NIRS), worse cases scenarios were first considered for the discrimination of various pharmaceutical final products containing the same Active Pharmaceutical Ingredient (API) with different excipients, such as generics of proprietary medicinal products (PMP). Two generic databases were explored: low active strength hard capsules of Fluoxetine and high strength tablets of Ciprofloxacin. Then 4 other cases involving suspicious samples, counterfeits and imitations products were treated. In all these cases, spectral differences between samples were studied, giving access to API or excipient contents information, and eventually allowing manufacturing site identification.A chemometric background is developed to explain the optimisation methodology, consisting in the choices of appropriate pretreatments, algorithms for data exploratory analyses (unsupervised Principal Component Analysis), and data classification (supervised cluster analysis, and Soft Independent Modelling of Class Analogy). Results demonstrate the high performance of NIRS, highlighting slight differences in formulations, such as 2.5% (w/w) in API strength, 1.0% (w/w) in excipient and even coating variations (<1%, w/w) with identical contents, approaching the theoretical limits of NIRS sensitivity. All the different generic formulations were correctly discriminated and foreign PMP, constituted of formulations slightly different from the calibration ones, were also all discriminated. This publication addresses the ability of NIRS to detect counterfeits and imitations and presents the NIRS as an ideal tool to master the global threat of counterfeit drugs.     

Characterization and identification of suspected counterfeit miltefosine capsules

Recently, it was revealed that generic miltefosine capsules for the treatment of visceral leishmaniasis, a fatal parasitic disease, were possibly counterfeit products. Here we report on the methods to characterize and identify miltefosine in pharmaceutical products and the procedures that were used to assess the quality of these suspected counterfeit products. Characterization and identification of miltefosine were done with liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), Fourier transform infrared (FT-IR) spectroscopy and near-infrared (NIR) spectroscopy. Moreover, a simple, rapid and inexpensive colorimetric test was developed and evaluated for the detection of miltefosine in pharmaceutical products that can be used in the field. The complementary analytical techniques presented here were able to determine qualitatively or (semi-)quantitatively the presence or absence of miltefosine in pharmaceutical preparations and could identify suspected counterfeit miltefosine capsules. This finding of a suspected counterfeit drug intended to treat a neglected disease in a resource-poor country emphasizes the urgent need to develop more simple inexpensive assays to evaluate drug quality for use in the field.     

多变量统计分类技术——磺胺甲基异口恶唑质量评价的研究

本文研究了近红外漫反射光谱法进行磺胺甲基异恶唑粉末药品质量评价的可能性，用多变量统计分类技术（系统聚类分析，逐步聚类分析，主成分分析和逐步判别分析），从磺胺甲基异恶唑末药品的一阶导数光谱，成功地鉴别了真药，劣药和假药，结果令人满意。     

Identification of the 'wrong' active pharmaceutical ingredient in a counterfeit Halfan drug product using accurate mass electrospray ionisation mass spectrometry,accurate mass tandem mass spectrometry and liquid chromatography/mass spectrometry

Methodology is presented for identifying an unknown active (pharmaceutical) ingredient (AI) in a counterfeit drug product. A range of mass spectrometric techniques, i.e., accurate mass mass spectrometry, tandem mass spectrometry (MS/MS) and liquid chromatography/mass spectrometry (LC/MS), has been employed to determine the AI in a counterfeit Halfan suspension, an antimalarial drug. In particular, use of LockSpray accurate mass MS/MS allowed identification of parts of the molecule from fragments, hence limiting the number of possible elemental compositions for the nominal mass of 278 found for the AI in the counterfeit product. The analysis of the isotope pattern observed for the protonated molecule further reduced the number of possible elemental compositions. A literature search for readily commercially available compounds of molecular formula C(12)H(14)N(4)O(2)S suggested that the AI was either sulfamethazine or sulfisomidine. An LC/MS separation of those two compounds and reference MS/MS spectra obtained for sulfamethazine and sulfisomidine led to the conclusion that the AI in the counterfeit Halfan suspension is sulfamethazine, which is an antibacterial agent.     

The FTIR spectrum of prostate cancer cells allows the classification of anticancer drugs according to their mode of action

The number of anticancer agents that fail in the clinic far outweighs those considered effective, suggesting that the selection procedure for progression of drug molecules into the clinic requires improvement. Traditionally, new drugs are evaluated for their potential to kill cancer cell lines. This approach is obviously not sufficient, and molecules with new modes of action are required. We suggest here that the infrared spectrum of cells exposed to anticancer drugs could offer an opportunity to obtain a fingerprint of the metabolic changes induced by the drugs. Because the infrared spectrum of cells yields a precise image of all the chemical bonds present in the sample, different drug targets are likely to yield different infrared fingerprints characteristic of the 'mode of action' of the therapeutic agent under investigation. In turn, drug-induced metabolic disorders should be amenable to classification in the same way that bacteria gender, species, and strains can be classified. We examined here a human prostate cancer PC-3 cell line exposed to 7 well described antimitotics. In a first step the IC(50) values were determined. For FTIR imaging, PC-3 cells were exposed to the IC(50) concentration of each drug for 48 h. About one hundred images of 4096 IR spectra at 8 cm(-1) spectral resolution were acquired. We show with a Student t-test that the different molecules tested induced different infrared spectral modifications. Furthermore, drugs known to induce similar types of metabolic disturbances appear to cluster when spectrum shapes are analyzed. Finally, supervised statistical methods allowed the building of an efficient and discriminant model. When the discriminant model was applied to a full infrared image a good sorting was generally obtained and misclassified spectra generally belonged to a small number of specific cells. Taken all together these data suggest that FTIR could be used for the classification of drug action.     

Evaluation of the potential of Raman microspectroscopy for prediction of chemotherapeutic response to cisplatin in lung adenocarcinoma

The study of the interaction of anticancer drugs with mammalian cells in vitro is important to elucidate the mechanisms of action of the drug on its biological targets. In this context, Raman spectroscopy is a potential candidate for high throughput, non-invasive analysis. To explore this potential, the interaction of cis-diamminedichloroplatinum(II) (cisplatin) with a human lung adenocarcinoma cell line (A549) was investigated using Raman microspectroscopy. The results were correlated with parallel measurements from the MTT cytotoxicity assay, which yielded an IC(50) value of 1.2 ± 0.2 μM. To further confirm the spectral results, Raman spectra were also acquired from DNA extracted from A549 cells exposed to cisplatin and from unexposed controls. Partial least squares (PLS) multivariate regression and PLS Jackknifing were employed to highlight spectral regions which varied in a statistically significant manner with exposure to cisplatin and with the resultant changes in cellular physiology measured by the MTT assay. The results demonstrate the potential of the cellular Raman spectrum to non-invasively elucidate spectral changes that have their origin either in the biochemical interaction of external agents with the cell or its physiological response, allowing the prediction of the cellular response and the identification of the origin of the chemotherapeutic response at a molecular level in the cell.     

Application of Mass Spectrometry and Chromatography–Mass Spectrometry in Drug Analysis

The review is devoted to the use of mass spectrometry and chromatography–mass spectrometry in various areas of pharmaceutical chemistry. The role of the above techniques in the structural identification of impurities in drug preparations and in the determination of the biotransformation behavior of pharmaceuticals in human and animal bodies is shown. The inactivation of drugs under the action of external factors (oxidation by atmospheric oxygen and the effects of moisture, heat, and light) is illustrated. The use of various ionization techniques and the spectra of metastable ions for determining the structures of components of biologically active substances are exemplified.     

Evaluation of a spectral searching algorithm for the comparison of Raman band positions

Raman spectroscopic identification of unknown materials involves often the comparison of the spectrum of the unknown spectrum with previously recorded reference spectra or data from literature. However, when spectra with many Raman bands or spectra of mixtures are involved, searching can be quite complex. Different chemometrical approaches have been proposed, but these have some drawbacks. Therefore, in this paper a novel approach is proposed, which is based on a multivariate comparison of Raman band positions. Different similarity measures can be used and are evaluated with spectra of test samples that were recorded on different spectrometers, using different laser wavelengths. Moreover, this study evaluates the performances of this algorithm for identifying different compounds in mixtures, by using an iterative approach.     

Testing the performance of pure spectrum resolution from Raman hyperspectral images of differently manufactured pharmaceutical tablets

Chemical imaging is a rapidly emerging analytical method in pharmaceutical technology. Due to the numerous chemometric solutions available, characterization of pharmaceutical samples with unknown components present has also become possible. This study compares the performance of current state-of-the-art curve resolution methods (multivariate curve resolution-alternating least squares, positive matrix factorization, simplex identification via split augmented Lagrangian and self-modelling mixture analysis) in the estimation of pure component spectra from Raman maps of differently manufactured pharmaceutical tablets. The batches of different technologies differ in the homogeneity level of the active ingredient, thus, the curve resolution methods are tested under different conditions. An empirical approach is shown to determine the number of components present in a sample. The chemometric algorithms are compared regarding the number of detected components, the quality of the resolved spectra and the accuracy of scores (spectral concentrations) compared to those calculated with classical least squares, using the true pure component (reference) spectra. It is demonstrated that using appropriate multivariate methods, Raman chemical imaging can be a useful tool in the non-invasive characterization of unknown (e.g. illegal or counterfeit) pharmaceutical products.     

Counterfeit drugs: analytical techniques for their identification

In recent years, the number of counterfeit drugs has increased dramatically, including not only “lifestyle” products but also vital medicines. Besides the threat to public health, the financial and reputational damage to pharmaceutical companies is substantial. The lack of robust information on the prevalence of fake drugs is an obstacle in the fight against drug counterfeiting. It is generally accepted that approximately 10% of drugs worldwide could be counterfeit, but it is also well known that this number covers very different situations depending on the country, the places where the drugs are purchased, and the definition of what constitutes a counterfeit drug. The chemical analysis of drugs suspected to be fake is a crucial step as counterfeiters are becoming increasingly sophisticated, rendering visual inspection insufficient to distinguish the genuine products from the counterfeit ones. This article critically reviews the recent analytical methods employed to control the quality of drug formulations, using as an example artemisinin derivatives, medicines particularly targeted by counterfeiters. Indeed, a broad panel of techniques have been reported for their analysis, ranging from simple and cheap in-field ones (colorimetry and thin-layer chromatography) to more advanced laboratory methods (mass spectrometry, nuclear magnetic resonance, and vibrational spectroscopies) through chromatographic methods, which remain the most widely used. The conclusion section of the article highlights the questions to be posed before selecting the most appropriate analytical approach.     

Transfer of silica gel TLC screening methods for clarithromycin,azithromycin, and amodiaquine + artesunate to HPTLC–densitometry with detection by reagentless thermochemical activation of fluorescence quenching

ABSTRACT

A previously published model process was used for the transfer of silica gel thin-layer chromatography (TLC) screening methods for clarithromycin, azithromycin, and amodiaquine?+?artesunate pharmaceutical formulations published in the Global Pharma Health Fund E.V. Minilab manual for the identification of counterfeit drugs to high-performance TLC–densitometry quantitative methods that can be used in support of regulatory compliance actions. In these new methods, detection of clarithromycin, azithromycin, and artesunate was achieved by thermochemical activation involving simple reagent-free heating of the layer to produce derivatives of the drugs that quench fluorescence under 254?nm ultraviolet light. Additional drugs with TLC screening methods published in the Minilab manual and/or Compendium of Unofficial Methods for Rapid Screening of Pharmaceuticals by Thin Layer Chromatography that do not naturally quench fluorescence were studied and also found to be detectable by thermochemical activation on silica gel layers. The conditions of the thermochemical activation were studied, and in situ spectra of drug zones before and after heating were obtained. Heat activation of fluorescence quenching seems to be a widely applicable detection method that is safer and more convenient than the use of chemical spray, dip, or vapor phase reagents.     

Measurement of lactate in whole human blood with near-infrared transmission spectroscopy

We have evaluated the potential of near-infrared spectroscopy (NIRS) as a technique for rapid analysis of lactate in whole blood. To test the NIRS technique, a comparison was made with a standard clinical method using whole blood samples taken from five exercising human subjects at three different stage of exercise. To expand lactate concentration within the physiological range, standard additions method was used to generate 45 unique data points. Spectra were collected over the 2050-2400 nm spectral range with a 1 mm optical path length quartz cell. Reference lactate concentrations in the samples were determined by enzymatic measurements. Estimates and calibration of the lactate concentration with NIRS was made using partial least squares (PLS) regression analysis and leave-N-out cross validation on second derivative spectra. Separate calibrations were determined from each of the subject samples and cumulative PRESS was used to determine the number of PLS factors in the final model. The results from the PLS model presented are generated from the five individual calibration coefficient vectors and provided a correlation coefficient of 0.978 and a standard error of cross validation of 0.65 mmol l⁻¹ between the enzymatic assay and the NIRS technique. To study the parameters that impact the spectra baseline and the correlation between the calculated model and the data, referenced measurements of lactate against baseline spectrum were made for each individual. A correlation coefficient of 0.992 and a standard error of cross validation of 0.21 mmol l⁻¹ were found. The results suggest that NIRS may provide a valuable tool to assess physiological status for both research and clinical needs.     

Standardization of a multi-wavelength UV detector for liquid chromatography-based toxicological analysis.

The performance of a multi-wavelength UV detector for automated drug identification following liquid chromatographic separation was evaluated. The ability of selected wavelength ratios to distinguish two closely related drugs was considered at different concentrations. Calibration of the detector based on wavelength ratios was then utilized to standardize two different detectors and to evaluate instrument-to-instrument variation of a series of detectors. Reproducibility of the second-derivative zero intercept for these drug spectra was also evaluated. Standardization of detector performance by reference to these two parameters permitted the transfer of UV spectral libraries stored on one instrument to another without compromising the reliability of qualitative data.     

Tracking infrared signatures of drugs in cancer cells by Fourier transform microspectroscopy

Aimed at developing accurate, reliable and cost-saving analytical techniques for drugs screening we evaluated the potential of Fourier Transform (FT) InfraRed (IR) microspectroscopy (microFTIR) as a quantitative pre-diagnostic approach for the rapid identification of IR signatures of drugs targeting specific molecular pathways causing Chronic Myeloid Leukemia (CML). To obtain reproducible FTIR absorbance spectra at the necessary spatial resolution we optimized sample preparation and acquisition parameters on a single channel Mercury-Cadmium-Telluride (MCT) detector in the spectral interval of frequencies from 4000 to 800 cm(-1). Single K562 cells were illuminated by Synchrotron Radiation (SR) and a number of ~15 K562 cells spread in monolayer were illuminated by a conventional IR source (Globar), respectively. Combining IR spectral data with the results of complementary biochemical investigations carried out in samples by different analytical methods we identified and cross-validated IR signatures of drugs targeting the oncogenic protein BCR/ABL and its associated abnormal tyrosine kinase activity in K562 cell line. Unsupervised pattern recognition performed by Hierarchical Cluster Analysis (HCA) clustered the spectra of single K562 cells in two distinct groups roughly corresponding to living and to apoptotic cells, respectively. The corresponding IR spectral profiles were assumed to represent drug-resistant and drug-sensitive cells. Significant variations with increasing percentages of apoptotic cells were observed after the treatment of K562 cells with drugs that directly or indirectly target BCR/ABL. In conclusion, we suggest that microFTIR associated with multivariate data analysis may be useful to assess drug compounds in ex vivo cancer cell models and possibly peripheral blast cells from CML patients.     

Revealing the Effect of Heat Treatment on the Spectral Pattern of Unifloral Honeys Using Aquaphotomics

In this study we aimed to investigate the effect of heat treatment on the spectral pattern of honey using near infrared spectroscopy (NIRS). For the research, sunflower, bastard indigo, and acacia honeys were collected from entrusted beekeepers. The honeys were not subject to any treatment before. Samples were treated at 40 °C, 60 °C, 80 °C, and 100 °C for 60, 120, 180, and 240 min. This resulted in 17 levels, including the untreated control samples. The 5-hydroxymethylfurfural (HMF) content of the honeys was determined using the Winkler method. NIRS spectra were recorded using a handheld instrument. Data analysis was performed using ANOVA for the HMF content and multivariate analysis for the NIRS data. For the latter, PCA, PCA-LDA, and PLSR models were built (using the 1300–1600 nm spectral range) and the wavelengths presenting the greatest change induced by the perturbations of temperature and time intervals were collected systematically, based on the difference spectra and the weights of the models. The most contributing wavelengths were used to visualize the spectral pattern changes on the aquagrams in the specific water matrix coordinates. Our results showed that the heat treatment highly contributed to the formation of free or less bonded water, however, the changes in the spectral pattern highly depended on the crystallization phase and the honey type.     

Compilation of an ESI-MS Library of β-Lactam Antibiotics for Rapid Identification of Drugs

β-Lactam antibiotics are among the most frequently used in clinical therapy. Thirty-three cephalosporin and eleven penicillin antibiotics frequently used in China have been used to create an ESI-MS library. A single-quadrupole mass analyzer was used for rapid identification. The product ions of these 44 β-lactam antibiotics were assigned to establish the fragmentation patterns and a standard ESI-MS library was established. Along with the specificity that product ion spectral information provides, the library provides another means to help identify β-lactam antibiotics. This is an important complement to the retention time from LC separations, and a valuable tool for confirming the identity of counterfeit drugs.     

Investigation into classification/sourcing of suspect counterfeit Heptodin™ tablets by near infrared chemical imaging

Near infrared chemical imaging (NIR-CI) analysis was performed on 55 counterfeit Heptodin™ tablets obtained from a market survey and an additional 11 authentic Heptodin™ tablets for comparison. The aim of the study was to investigate whether NIR-CI can be used to detect the counterfeit tablets and to classify/source them so as to understand the possible number of origins to aid investigators and authorities to shut down counterfeiting operations. NIR-CI combined with multivariate analysis is particularly suited to compare chemical and physical properties of samples, since it is a quick and non-destructive method of analysis. Counterfeit tablets were easily distinguished from the authentic ones. Principal component analysis (PCA) and k-means clustering were performed on the data set. The results from both analyses grouped the counterfeit tablets in 13 main groups. The main groups found with both methods were quite consistent. Out of the 55 tablets only 18% contained the correct active pharmaceutical ingredient (API), i.e., the anti-viral drug lamivudine. The remaining 82% of counterfeit tablets contained talc and starch as main excipients. The API containing tablets classified into three main groups, based mainly on the amount of lamivudine present in the tablet. The group which had close to the correct amount of lamivudine sub-classified into three groups. From the analysis carried out, it is likely that the counterfeit tablets originate from as many as 15 different sources.     

Detection and chemical profiling of medicine counterfeits by Raman spectroscopy and chemometrics

Raman spectroscopy combined with chemometrics has recently become a widespread technique for the analysis of pharmaceutical solid forms. The application presented in this paper is the investigation of counterfeit medicines. This increasingly serious issue involves networks that are an integral part of industrialized organized crime. Efficient analytical tools are consequently required to fight against it. Quick and reliable authentication means are needed to allow the deployment of measures from the company and the authorities. For this purpose a method in two steps has been implemented here. The first step enables the identification of pharmaceutical tablets and capsules and the detection of their counterfeits. A nonlinear classification method, the Support Vector Machines (SVM), is computed together with a correlation with the database and the detection of Active Pharmaceutical Ingredient (API) peaks in the suspect product. If a counterfeit is detected, the second step allows its chemical profiling among former counterfeits in a forensic intelligence perspective. For this second step a classification based on Principal Component Analysis (PCA) and correlation distance measurements is applied to the Raman spectra of the counterfeits.     

The development and inter-laboratory verification of LC-MS libraries for organic chemicals of environmental concern

The development, verification, and comparison study between LC-MS libraries for two manufacturers’ instruments and a verified protocol are discussed. Compounds in the libraries are among those considered by the U.S. EPA Office of Water as threats to drinking water including pesticides, drugs of abuse, and pharmaceuticals. The LC-MS library protocol was verified through an inter-laboratory study that involved Federal, State, and private laboratories. The results demonstrated that the libraries are transferable between the same manufacturer's product line, and have applicability between manufacturers. Although ion abundance ratios within mass spectra were shown to be different between the manufacturers’ instruments, the NIST search engine match probability was at 96% or greater for 64 out of 67 compounds evaluated.