Untitled

ORIENTAL JOURNAL OF CHEMISTRY
An International Open Free Access, Peer Reviewed Research Journal Spectroscopic and Chemometric Analysis of Illegally
Manufactured Formulations of Selected Medicines
SAFWAN M. OBEIDAT* and BAN AL-TAYYEM
Department of Chemistry, Yarmouk University, Irbid (Jordan).
*Corresponding author E-mail: [email protected] (Received: May 14, 2012; Accepted: June 15, 2012) ABSTRACT
In this study, three common drugs (Cipram®, Panadol extra ®, Xenical®) were investigated.
The study involved analyzing the above drugs using the portable NIR spectroscopy. Ten adulteratedtablets of each of the above drugs were tested along with ten genuine tablets and other tenplacebo tablets which represents another adulterated source for all drugs. ChemometricalAlgorithms like Principal Components Analysis (PCA) and Cluster Analysis (CA) were used toextract the useful information from the collected data. Differentiating among original and the counterfeitdrugs was successfully demonstrated with no chemical pretreatment. Identifying adulterationsource was also possible using the above algorithms.
Key words: Potable NIRS, Counterfeit Drugs, PCA, CA. Medicines.
INTRODUCTION
access to digital technology, etc…). Thecounterfeiting drugs can cause serious health problems such as diseases, dissatisfaction and in Organization (WHO) the problem of counterfeit some cases they might cause death 2,3. On the other medicines was first addressed at the international side, the reputation and the profits of the level in 1985 at the Conference of Experts on the manufacturer are badly affected by adulterating a Rational Use of Drugs in Nairobi. The WHO has particular brand name. The Jordanian market as identified counterfeit medicine as “the medicine any drug market around the world is subjected to which is deliberately fraudulently mislabeled, with the drug adulteration problems. According to the respect to its identity and/or source. This includes Jordanian Food and Drug Administration (JFDA), products with correct or wrong ingredients, without several drugs are being adulterated. Many active ingredients or with insufficient active adulterated drugs are being captured in the Jordanian market. These dr ugs are rangingbetween several categories (antidepressant, pain relievers, inhibitors and others). The list of counterfeit recently increased because of many reasons (i.e.
drugs in Jordan includes expensive drugs as well financial gain, minimal penalties, demand, cheap as shelf drugs such as common pain killers. The OBEIDAT & TAYYEM., Orient. J. Chem., Vol. 28(2), 795-801 (2012)
current standard method of detecting the counterfeit Portable Near-infrared (NIR) spectroscopy
drugs involves chromatographic techniques.
The Polychromix PHAZIR is the first of its However, these methods suffer from several kind handheld NIR material analyzer. The light drawbacks. Most of the uncovering the adulteration source is a tungsten lamp and the detector is a PbS studies focused on both drugs Viagra and Cialis.
For this purpose XRD, Raman spectroscopy, NIR,FT-IR, DOSY 1HNMR and other analytical methods Measurements and software
were reported in literature for detecting the illegally manufactured drugs especially Viagra and Cialis 4- placebo) for each drug were first measured by the 11. In this study Cipram®, Panadol extra®, Xenical® portable NIRS. The scan covered the range (1000 will be investigated. Table 1 shows the active to 2400) nm (about 8 nm increments). The spectrum ingredient and indications for each drug.
of each tablet was an average of three scans.
MATLAB 7.0.4. (MathWorks, MA, USA) with PLS The aim of the current study is to obtain a Toolbox 4.0 (Eigenvector Research, Inc, WA and rapid and a reliable method for detecting illegally USA) were used for the data processing and formulated drugs using portable NIR with no sample analysis. All recoded spectra were background and preparation. The NIR is well known for its powerful blank corrected. Hence, three separate data files in providing too many details in the spectra.
were constructed correspond to the three studied However, the new portable NIR instrument is less drugs. Each file contains the NIR spectral data for sensitive compared to the bench top NIR instrument.
all drug samples including (original, counterfeit and To extract the maximum useful information from the placebo). PCA and CA techniques were applied to NIR data Principal Component Analysis (PCA) and the above files. The goal of this step is to differentiate Cluster Analysis (CA) were employed. Tracking the among the spectra for the original and the counterfeit adulteration source was also a major goal in his study. For this purpose placebo samples were usedto simulate another adulterated drug in composition Principle Component Analysis (PCA)
in the three studied drugs. The choice of placebo to represent another adulterated drug is that most recognition technique based on calculating the adulterated drugs caught in Jordan were with no eigenvectors in a data set. PCA uses orthogonal active ingredients. Hence the composition of the transformation to convert a number of measurements adulterated drug could be very close in composition for variables that might be correlated into a set of linearly uncorrelated variables. In summary PCA investigated in the same way as the rest of drug that is used for finding similarities and differences among the samples in a given data set. Usually, thefirst few PCs express the maximum variation within EXPERIMENTAL
a dataset. The number of principal componentsequals to the number of variables. In PCA the score Samples collection
plot is used to display similarities and differences In this study counterfeit samples of Cipram, among the objects in a data set. Samples that have Panadol extra and Xenical (all in tablet form) were similar composition and hence similar spectra will studied. Ten counterfeit tablets from each drug above form an independent cluster. The distances between were donated by the Jordanian Food and Drug the clusters in the PCA model reflect the degree of Administration (JFDA). A similar number of the original samples were donated or purchased fromthe exclusive importers in Jordan. Placebo tablets Cluster Analysis (CA)
To understand the patterns exist in a given Manufacturing (JPM) Company. Ten tablets of data set and to identify similar samples the CA is placebo were also used for each drug. All samples used. Cluster analysis (CA) is a classification including the adulterated, original and placebo were technique that is used to classify the objects of a data set into clusters. The distances (Hierarchical) OBEIDAT & TAYYEM., Orient. J. Chem., Vol. 28(2), 795-801 (2012)
between the objects in the multidimensional space Fig 2, displays the PCA score plot for the Cipram are calculated. Objects of minimum distances samples. The best view for the PCA plot was when (largest similarity) are merged in a single cluster.
using the second and the third PCs. In Fig 2, three This approach is repeated. The distances between independent groups of samples (clusters) can be all pairs of clusters are also calculated. The final recognized. Each one of the three groups of results including objects and clusters distances are represented by a tree like diagram called (counterfeit, original and placebo). In predicting dendrogram. In the dendreogram, objects fall in one PCA score plots, samples that form a cluster are cluster are believed to have to same origin or have believed to belong to the same origin. Moreover, as it can be noticed in Fig 2 the object varianceobserved in the counterfeit samples is greater than RESULTS AND DISCUSSION
that in the original and placebo clusters. This mightdue to the poor mixing process used by the counterfeiters resulted in inhomogeneous drug spectral fingerprint that identifies the brand of the formulation. Figure 3, represents the PCA score plot drug. Incorrect formulations containing foreign or for the Xenical samples. Again, the best PCA plot substitute ingredients can put the patient’s life under was created using the first two PCs. In Fig 3, three risk. The NIR spectra recorded for the Cipram, separate clusters were also observed in this drug.
Panadol extra and Xenical (counterfeit, original and Each cluster represents one form of the Xenical placebo) were displayed. Fig 1 (A, B and C) (original, counterfeit and placebo). The same results represents the NIR spectra for the above drugs in were obtained upon applying the PCA on the NIR all cases, respectively. It is obvious that the eye spectra of the Panadol extra (figure not shown).
balling for the spectra seems to be inefficient for These results demonstrate the powerful of the NIR differentiating original and counterfeit drugs. This and PCA in detecting counterfeit drugs. Not only might due to the low sensitivity of the spectrometer that, but it also can differentiate counterfeit drugs (only 100 wavelengths). Hence, to compare the from different origins (placebo and counterfeit). For entire spectra chemometrical techniques (PCA, CA) further investigations, cluster analysis such as K- were used to detect fine differences in the spectra.
nearest neighbor (KNN) was also used. In KNN In PCA case the first few PCs were used because distances among all samples are calculated. The they carry the maximum variation in all data sets.
KNN dendrograms obtained for the Cipram is Therefore, a PCA model was created for each drug.
illustrated in Fig 4. As it can be seen in this figure, Fig. 1(A): NIR spectra obtained for Xeincal (counterfeit, original and placebo)
OBEIDAT & TAYYEM., Orient. J. Chem., Vol. 28(2), 795-801 (2012)
Fig. 1(B): NIR spectra obtained for Cipram (counterfeit, original and placebo)
Fig. 1(C): NIR spectra obtained for Panadol Extra (counterfeit, original and placebo)
Fig. 2: PCA score plot for the Cipram samples
Fig. 3: PCA score plot for the Xenical samples
OBEIDAT & TAYYEM., Orient. J. Chem., Vol. 28(2), 795-801 (2012)
Fig. 4: The dendrogram for the NIR spectral data recorded for all Cipram samples
Fig. 5: The dendrogram for the NIR spectral data recorded for all Panadol extra samples
Table 1: Some details about the studied medications in the current work
Medication
Indication
Producer
Ingredient
OBEIDAT & TAYYEM., Orient. J. Chem., Vol. 28(2), 795-801 (2012)
three separate groups in the dendrograms were CONCLUSION
recognized. Each group contains the samples ofone form of the drug (original, counterfeit and placebo). Similar results were obtained upon in this paper for detecting counterfeit drugs. The applying the KNN in case of both Panadol extra tested drugs were Cipram, Xenical and Panaol extra.
(Fig 5) and Xenical (figure not shown). As indicated The detection of counterfeit drugs was successfully in the dendrogams the distinguished groups are achieved by applying PCA and KNN to the collected the counterfeit, original and placebo with no NIR data for all drugs. Were in both cases (PCA and interference between samples. Once more, the KNN) three independent groups or clusters were current technique using the portable NIR and PCA clearly identified for each drug. These clusters or KNN could differentiate among original and correspond for the original, counterfeit and placebo counterfeit tablets efficiently from different samples in each medicine. The placebo samples were used in this study to simulate anotheradulteration source. This result suggests a methodfor tracking illegally formulated by source ispossible.
REFERENCES
WHO, Counterfeit Drugs: Guidelines for the Counterfeit Drugs, WHO, Geneva, (1999).
1HNMR and Raman spectroscopy, J. Pharm.
Biomed. Anal. 47: 103-113 (2008).
Identification of counterfeit drugs using near- infrared spectroscopy, Analyst, 126: 2218-
Rao. Orient J. Chem. 27(1): 313-316 (2011).
B. J. Venhuis, G. Zomer, M. J. Vredenbregt and legislative proposal to combat counterfeit D. de Kaste, The identification of (-)-trans- tadalafil, tadalafil, and sildenafil in counterfeit Cialis® and the optical purity of tadalafil stereoisomers, J. Pharm. Biomed. Anal. 51:
J. K. Maurin, F. Plucinski, A. P. Mazurek and Z.
723-727 (2010).
P. Y. Sacré, E. Deconinck, T. De Beer, P.
powder diffraction analysis for counterfeit Courselle, R. Vancauwenberghe, P. Chiap, J.
control – The Viagra example, J. Pharm.
Biomed. Anal. 43: 1514-1518 (2007).
M. de Veij, A. Deneckere, P. Vandenabeele, techniques for the detection of counterfeit medicines, J. Pharm. Biomed. Anal. 53: 445-
counterfeit Viagra with Raman spectroscopy, J. Pharm. Biomed. Anal. 46: 303-309 (2008).
Identification of counterfeit medicines from the internet and world market using near- infrared spectroscopy, Anal. Meth. 3: 2231-
Viagra® and imitation of Viagra® with near- infrared spectroscopy, J. Pharm. Biomed.
Anal. 40: 840-849 (2006).
Martinez, A. Edmind, N Jent, A review of near S. Trefi, C. Routaboul, S. Hamieh, V. Gilard, M.
infrared spectroscopy and chemometrics in Malet-Martino and R. Martino, Analysis of pharmaceutical technologies, J. Pharm.
OBEIDAT & TAYYEM., Orient. J. Chem., Vol. 28(2), 795-801 (2012)
Biomed. Anal. 44, 683-700 (2007).
K.H. Esbensen, Multivariate Data Analysis – S. Wold, K. Esbensen, P. Geladi, Principal component analysis, Chemomet. Intell. Lab.
A. F. M. Alkarahi, A. Ahmad and A. Mat Easa, Syst. 2, 37–52 (1987).
E. Venumadhav, T. Neetha, P. Bhargavi, G.
selected estuaries of Malaysia: multivariate Ramanand G. Devala Rao, Orient J. Chem.
statistical techniques, Environmentalist, 26(3): 1175-1178 (2010).
29:255-262 (2009).
K. Šnuderl, M. Simoniè, J. Mocak and D.
B. M. Wise, N. B. Gallagher, R. Bro, and J.
Brodnjak-Vonèina Multivariate data analysis of natural mineral waters, Acta chim. Slov.
54: 33-39 (2007).

Source: http://www.orientjchem.org/dnload/SAFWAN-M-OBEIDAT-and-BAN-AL-TAYYEM/OJCV028I02P795-801.pdf