D. Custers

ATR-FTIR spectroscopy and chemometrics: An interesting tool to discriminate and characterize counterfeit medicines.

Counterfeit medicines pose a huge threat to public health worldwide. High amounts of counterfeit pharmaceuticals enter the European market and therefore detection of these products is essential. Attenuated Total Reflection Fourier-Transform infrared spectroscopy (ATR-FTIR) might be useful for the screening of counterfeit medicines since it is easy to use and little sample preparation is required. Furthermore, this approach might be helpful to customs to obtain a first evaluation of suspected samples. This study proposes a combination of ATR-FTIR and chemometrics to discriminate and classify counterfeit medicines. A sample set, containing 209 samples in total, was analyzed using ATR-FTIR and the obtained spectra were used as fingerprints in the chemometric data-analysis which included Principal Component Analysis (PCA), k-Nearest Neighbours (k-NN), Classification and Regression Trees (CART) and Soft Independent Modelling of Class Analogy (SIMCA). First it was verified whether the mentioned techniques are capable to distinguish samples containing different active pharmaceutical ingredients (APIs). PCA showed a clear tendency of discrimination based on the API present; k-NN, CART and SIMCA were capable to create suitable prediction models based on the presence of different APIs. However k-NN performs the least while SIMCA performs the best. Secondly, it was tested whether these three models could be expanded to discriminate between genuine and counterfeit samples as well. k-NN was not able to make the desired discrimination and therefore it was not useful. CART performed better but also this model was less suited. SIMCA, on the other hand, resulted in a model with a 100% correct discrimination between genuine and counterfeit drugs. This study shows that chemometric analysis of ATR-FTIR fingerprints is a valuable tool to discriminate genuine from counterfeit samples and to classify counterfeit medicines.

Detection of sibutramine in adulterated dietary supplements using attenuated total reflectance-infrared spectroscopy

Sibutramine is one of the most occurring adulterants encountered in dietary supplements with slimming as indication. These adulterated dietary supplements often contain a herbal matrix. When customs intercept these kind of supplements it is almost impossible to discriminate between the legal products and the adulterated ones, due to misleading packaging. Therefore in most cases these products are confiscated and send to laboratories for analysis. This results inherently in the confiscation of legal, non-adulterated products. Therefore there is a need for easy to use equipment and techniques to perform an initial screening of samples. Attenuated total reflectance-infrared (ATR-IR) spectroscopy was evaluated for the detection of sibutramine in adulterated dietary supplements. Data interpretation was performed using different basic chemometric techniques. It was found that the use of ATR-IR combined with the k-Nearest Neighbours (k-NN) was able to detect all adulterated dietary supplements in an external test set and this with a minimum of false positive results. This means that a small amount of legal products will still be confiscated and analyzed in a laboratory to be found negative, but no adulterated samples will pass the initial ATR-IR screening.

Headspace–gas chromatographic fingerprints to discriminate and classify counterfeit medicines

Counterfeit medicines are a global threat to public health. These pharmaceuticals are not subjected to quality control and therefore their safety, quality and efficacy cannot be guaranteed. Today, the safety evaluation of counterfeit medicines is mainly based on the identification and quantification of the active substances present. However, the analysis of potential toxic secondary components, like residual solvents, becomes more important. Assessment of residual solvent content and chemometric analysis of fingerprints might be useful in the discrimination between genuine and counterfeit pharmaceuticals. Moreover, the fingerprint approach might also contribute in the evaluation of the health risks different types of counterfeit medicines pose. In this study a number of genuine and counterfeit Viagra(®) and Cialis(®) samples were analyzed for residual solvent content using headspace-GC-MS. The obtained chromatograms were used as fingerprints and analyzed using different chemometric techniques: Principal Component Analysis, Projection Pursuit, Classification and Regression Trees and Soft Independent Modelling of Class Analogy. It was tested whether these techniques can distinguish genuine pharmaceuticals from counterfeit ones and if distinct types of counterfeits could be differentiated based on health risks. This chemometric analysis showed that for both data sets PCA clearly discriminated between genuine and counterfeit drugs, and SIMCA generated the best predictive models. This technique not only resulted in a 100% correct classification rate for the discrimination between genuine and counterfeit medicines, the classification of the counterfeit samples was also superior compared to CART. This study shows that chemometric analysis of headspace-GC impurity fingerprints allows to distinguish between genuine and counterfeit medicines and to differentiate between groups of counterfeit products based on the public health risks they pose.

Chromatographic fingerprinting as a strategy to identify regulated plants in illegal herbal supplements

Erectile dysfunction (ED) is a sexual disorder characterized by the inability to achieve or maintain a sufficiently rigid erection. Despite the availability of non-invasive oral treatment options, many patients turn to herbal alternatives. Furthermore, herbal supplements are increasingly gaining popularity in industrialized countries and, as a consequence, quality control is a highly important issue. Unfortunately, this is not a simple task since plants are often crushed and mixed with other plants, which complicates their identification by usage of classical approaches such as microscopy. The aim of this study was to explore the potential use of chromatographic fingerprinting to identify plants present in herbal preparations intended for the treatment of ED. To achieve this goal, a HPLC-PDA and a HPLC-MS method were developed, using a full factorial experimental design in order to acquire characteristic fingerprints of three plants which are potentially beneficial for treating ED: Epimedium spp., Pausinystalia yohimbe and Tribulus terrestris. The full factorial design demonstrated that for all three plant references a C8 column (250mm×4.6mm; 5µm particle size) is best suited; methanol and an ammonium formate buffer (pH 3) were found to be the best constituents for the mobile phase. The suitability of this strategy was demonstrated by analysing several self-made triturations in three different botanical matrices, which mimic the influential effects that could be expected when analysing herbal supplements. To conclude, this study demonstrates that chromatographic fingerprinting could provide a useful means to identify plants in a complex herbal mixture.

Physical profiling and IR spectroscopy: simple and effective methods to discriminate between genuine and counterfeit samples of Viagra® and Cialis®

Counterfeit medicines are a global threat to public health. High amounts enter the European market, enforcing the need for simple techniques to help customs detect these pharmaceuticals. This study focused on physical profiling and IR spectroscopy to obtain a prime discrimination between genuine and illegal Viagra® and Cialis® medicines. Five post-tableting characteristics were explored: colour, mass, long length, short length, and thickness. Hypothesis testing showed that most illegal samples (between 60 and 100%) significantly differ from the genuine medicines, in particular for mass and long length. Classification and Regression Trees (CART) analysis resulted in a good discrimination between genuine and illegal medicines (98.93% correct classification rate for Viagra®, 99.42% for Cialis®). Moreover, CART confirmed the observation that mass and long length are the key physical characteristics which determine the observed discrimination. IR analysis was performed on tablets without blister and on tablets in intact blister. These data were analyzed using Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Squares - Discriminant Analysis (PLS-DA). Supervised techniques needed to be applied since Principal Component Analysis (PCA) was not able to generate the desired discrimination. Our study shows that a perfect discrimination between genuine and illegal medicines can be made by both SIMCA and PLS-DA without removing the tablets from the blister. This approach has the advantage of keeping the blister intact. Our study demonstrates that these user friendly techniques are reliable methods to aid customs to obtain a prime distinction between genuine and illegal samples on the spot. Copyright

A strategy for the identification of plants in illegal pharmaceutical preparations and food supplements using chromatographic fingerprints

Abstract The detection of regulated and forbidden herbs in pharmaceutical preparations and nutritional supplements is a growing problem for laboratories charged with the analysis of illegal pharmaceutical preparations and counterfeit medicines. This article presents a feasibility study of the use of chromatographic fingerprints for the detection of plants in pharmaceutical preparations. Fingerprints were developed for three non-regulated common herbal products—Rhamnus purshiana, Passiflora incarnata L. and Crataegus monogyna—and this was done by combining three different types of detection: diode-array detection, evaporative light scattering detection and mass spectrometry. It is shown that these plants could be detected in respective triturations of the dry extracts with lactose and three different herbal matrices as well as in commercial preparations purchased on the open market. FigureDetection of Passiflora incarnata in three commercial preparations using chromatographic fingerprints

Chemometrics and the identification of counterfeit medicines—A review

This review article provides readers with a number of actual case studies dealing with verifying the authenticity of selected medicines supported by different chemometric approaches. In particular, a general data processing workflow is discussed with the major emphasis on the most frequently selected instrumental techniques to characterize drug samples and the chemometric methods being used to explore and/or model the analytical data. However, further discussion is limited to a situation in which the collected data describes two groups of drug samples - authentic ones and counterfeits.

Chromatographic impurity fingerprinting of genuine and counterfeit Cialis® as a means to compare the discriminating ability of PDA and MS detection.

Public health is threatened worldwide by counterfeit medicines. Their quality, safety and efficacy cannot be guaranteed since no quality control is performed during and/or after the manufacturing process. Characterization of these products is a very important topic. During this study a High Performance Liquid Chromatography-Photodiode Array (HPLC-PDA) and a High Performance Liquid Chromatography - Mass Spectrometry (HPLC-MS) method were developed to analyse both genuine and counterfeit samples of Cialis®. The obtained PDA and MS fingerprints were explored and modelled using unsupervised Principal Component Analysis (PCA) and supervised Partial Least Squares and its discriminant variant (PLS, PLS-DA) as well the classification methods including Soft Independent Modelling of Class Analogy (SIMCA) and the k Nearest Neighbour classifier (kNN). Both MS1 and MS2 data and data measured at 254 nm and 270 nm were used with the aim to test the potential complementarity of PDA and MS detection. First, it was checked if both groups of fingerprints can support differentiation between genuine and counterfeit medicines. Then, it was verified if the obtained multivariate models could be improved by combining information present in MS and PDA fingerprints. Survey of the models obtained for the 254 nm data, 270 nm data and 254_270 nm data combination showed that a tendency of discrimination could be observed with PLS. For the 270 nm data and 254_270 nm data combination a perfect discrimination between genuine and counterfeit medicines is obtained with PLS-DA and SIMCA. This shows that 270 nm alone performs equally well compared to 254_270 nm. For the MS1 and MS1_MS2 data perfect models were obtained using PLS-DA and kNN, indicating that the MS2 data do not provide any extra useful information to acquire the aimed distinction. When combining MS1 and 270 nm perfect models were gained by PLS-DA and SIMCA, which is very similar to the results obtained for PDA alone. These results show that both detectors have a potential to reveal chemical differences between genuine and counterfeit medicines and thus enable the construction of diagnostic models with excellent recognition. However, if a larger sample set, including more possible sources of variation, is analysed more sophisticated techniques such as MS might be necessary.

Identification of (Antioxidative) Plants in Herbal Pharmaceutical Preparations and Dietary Supplements

The standard procedures for the identification, authentication, and quality control of medicinal plants and herbs are nowadays limited to pure herbal products. No guidelines or procedures, describing the detection or identification of a targeted plant or herb in pharmaceutical preparations or dietary supplements, can be found. In these products the targeted plant is often present together with other components of herbal or synthetic origin. This chapter describes a strategy for the fast development of a chromatographic fingerprint approach that allows the identification of a targeted plant in herbal preparations and dietary supplements. The strategy consists of a standard chromatographic gradient that is tested for the targeted plant with different extraction solvents and different mobile phases. From the results obtained, the optimal fingerprint is selected. Subsequently the samples are analyzed according to the selected methodological parameters, and the obtained fingerprints can be compared with the one obtained for the pure herbal product or a standard preparation. Calculation of the dissimilarity between these fingerprints will result in a probability of presence of the targeted plant. Optionally mass spectrometry can be used to improve specificity, to confirm identification, or to identify molecules with a potential medicinal or antioxidant activity.

Clustering and diagnostic modelling of slimming aids based on chromatographic and mass spectrometric fingerprints

Herbal medicines and food supplements intended as slimming aids are increasingly gaining popularity worldwide, especially for treating obesity. In this study, an ultra-performance liquid chromatography coupled to photodiode array detection (UPLC-PDA) and an ultra-performance liquid chromatography mass spectrometry (UPLC-MS) method were developed to analyze 92 slimming aids (confiscated by customs), aimed at acquiring highly informative fingerprints. Three types of fingerprints were acquired (PDA, Total Ion Chromatograms (TIC), and MS fingerprints) which were used in the chemometric data analysis. Both unsupervised (i.e., Hierarchical Cluster Analysis (HCA)) and supervised techniques (i.e., Classification and Regression Tree (CART) and Partial Least Squares - Discriminant Analysis (PLS-DA)) were applied. The aim was to perform an in-depth study of the samples, thereby exploring potential patterns present in the data. HCA was able to generate a clustering which was mainly defined by chemical compounds detected in the samples, i.e., sibutramine, phenolphthalein and amfepramone. PLS-DA generated the best diagnostic models for both PDA and TIC fingerprints, characterized by correct classification rates of external validation of 85% and 80%, respectively. For the MS fingerprints, the best model was obtained by CART (65% correct classification rate of external validation). Despite a lower correct classification rate, exploration of the concerned misclassifications revealed that the MS fingerprints proved to be superior since even very low concentrations of sibutramine could be detected. This study shows that reliable chemometric models can be obtained, based on the presence of prohibited chemical substances, which allow high-throughput data analysis of such samples. Moreover, they generate a prime notion of potential threat to a patients health posed by these kinds of slimming aids. Copyright