Journal of Pharmaceutical and Biomedical Analysis
Detection of counterfeit Viagra® by Raman microspectroscopy imaging and multivariate analysis
Introduction
During the past years, pharmaceutical counterfeiting was mainly a problem of developing countries with weak enforcement and inspection programs. Asia and Latin America are the most contaminated geographical regions. However, Europe and North America are more and more confronted to the counterfeiting problem [1].
Recently, the Belgian Federal Agency for Medicines and Health Products (AFMPS/FAGG) participated in PANGEA III, an international operation fighting against the online sale of counterfeit and illegal medicines [2]. The most encountered therapeutic categories in Belgium were weight-loss drugs and potency enhancing drugs such as Viagra® (Pfizer).
Since its approval by the American Food and Drug Agency (FDA) [3] and the European Medicines Agency (EMA) [4] in 1998, Viagra® has become one of the most counterfeited medicines in industrialized countries. Several spectroscopic techniques have been used to detect counterfeit Viagra®. Rodomonte et al. used colorimetry to detect counterfeit medicines based on their differences of tablets and second packaging colour [5]. Vredenbregt et al. applied NIR spectroscopy on 103 samples to detect counterfeit Viagra® but also to check the homogeneity of batches and screen the presence of sildenafil citrate [6]. De Veij et al. showed for the first time that Raman spectroscopy was able to detect counterfeit Viagra® [7]. However, this study compared 18 illegal samples to only one genuine tablet. Our group concluded that the combination of FT-IR and NIR spectroscopy was more powerful than FT-IR, NIR or Raman spectroscopy alone to discriminate genuine from illegal Viagra® samples [8]. X-ray powder diffraction [9], NMR (1H, 13C, 15N) [10], and NMR (2D DOSY, 3D DOSY-COSY, 1H NMR) [11] were also used to detect counterfeit Viagra®. However, compared to the first cited techniques, X-ray diffraction and NMR necessitate a more elaborated sample preparation and are therefore only performed by well trained analysts.
Chemical imaging is a powerful tool since it provides physico-chemical information and spatial information of the sample. Raman microspectroscopy imaging is widely used in the biomedical field. Among others, it has been recently used to predict the cellular response to cisplatin in lung adenocarcinoma [12] and to study the molecular interactions between zoledronic acid and bone [13]. It is also used in the pharmaceutical field since it necessitates a negligible sample preparation (e.g. for tablet analysis, sample preparation is only cutting tablets in two). It has been mostly used in pharmaceutical technology applications [14], [15], [16], [17].
Near infrared chemical imaging (NIR-CI) has also been used in the field of pharmaceutical technology [18], [19], [20], [21]. More recently, NIR-CI has been used by Lopes et al. to detect and classify counterfeit antiviral drugs [22] and to determine their chemical composition [23]. Puchert et al. successfully used NIR-CI to detect counterfeit bisoprolol tablets [24].
During this study, 26 counterfeits and imitations of Viagra® tablets and 8 genuine tablets of Viagra® were analysed by Raman microspectroscopy imaging. After an exploratory PCA analysis, linear discriminant analysis (LDA), k-nearest neighbours (k-NN) and soft independent modelling by class analogy (SIMCA) were applied on the full spectra dataset, as classification algorithms. Other spectral ranges were also investigated to detect counterfeit medicines based on the presence of lactose and the spatial distribution of sildenafil inside the tablet. The aim of this study was to discriminate illegal samples and to evaluate which of the three applied classification algorithm was the best suited for purpose. As far as we know, this is the first time that Raman microspectroscopy imaging is used to detect counterfeit medicines.
Section snippets
Principal component analysis
PCA is a variable reduction technique, which reduces the number of variables by making linear combinations of the original variables. These combinations are called the principal components and are defined in such way that they explain the highest (remaining) variability in the data and are by definition orthogonal.
The importance of the original variables in the definition of a principal component is represented by its loading and the projections of the objects on to the principal components are
Illegal samples
A total of 26 counterfeit and imitation tablets of Viagra® were donated by the Federal Agency for Medicines and Health Products in Belgium (AFMPS/FAGG). They all come from postal packs ordered by individuals through Internet sites. All samples were delivered in blisters or closed jars with or without packaging. All samples, once received, were stored at ambient temperature and protected from light.
Reference samples
Pfizer SA/NV (Belgium) kindly provided one batch of each different dosage of Viagra® (25 mg, 50 mg,
Raman microspectroscopy maps
Fig. 2 shows typical genuine Viagra® maps at the three dosage forms and Fig. 3 shows the maps of 3 illegal samples which are representative of the other illegal samples. There is no visible difference between the dosage forms of the genuine samples at the chosen intensity range (1 × 107 to 10 × 107 Raman counts). However, as can be seen, the spectral intensities are much higher in illegal preparations than in genuine tablets. This is sometimes due to higher sildenafil content but in most cases this
Conclusion
Raman microspectroscopy is a powerful tool allowing a complete mapping of a limited area of a tablet with a limited sample preparation. The analysis of these maps may provide a lot of information about the identification of chemical compounds present, their distribution and their amount [30]. In this study, the core of 26 counterfeit and imitation tablets of Viagra® and 8 genuine samples of Viagra® were analysed by Raman microspectroscopy over the spectral regions of 200–1800 cm−1, 830–880 cm−1
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These authors contributed equally to this work.