NIR-based approach to counterfeit-drug detection,☆☆

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Abstract

There is no simple solution to the problem of counterfeit-drug detection. So-called “high-quality fakes” with proper composition are most difficult to reveal. Methods based only on quantitative determination of active ingredients are sometimes insufficient. A more general approach is to consider a remedy as a whole object, taking into account the complex composition of active ingredients and incipients, as well as manufacturing conditions (e.g., degree of drying). NIR measurement combined with chemometric data processing is an effective method but the superficial simplicity of its application may lead to wrong conclusions that undermine confidence in the technique. The main drawback of the NIR-based approach is the need to apply multivariate/chemometric data analysis in order to extract useful information from the acquired spectra.

This article provides an overview of the experience of different research groups in NIR drug detection and highlights the main issues that should be taken into account. The common problems to be dealt with are:

  • (1)

    each medicinal product should be carefully tested for batch-to-batch variability;

  • (2)

    the selection of a specific spectral region and the data pre-processing method should be done for each type of medicine individually; and,

  • (3)

    it is crucial to recognize counterfeits as well as to avoid misclassification of genuine samples.

The real-world examples presented in the article illustrate these points.

Introduction

At present, drug counterfeiting is becoming more and more sophisticated. In the past, fake medicines were a common problem in developing countries where the main issue was often the tremendous lack of a specific remedy (e.g., antimalarial drugs). According to the European Agency for the Evaluation of Medicinal Products (EMEA), the phenomenon has spread. More and more frequently, fakes are being revealed all over the world. In developing countries, the majority of counterfeited medicines are used to treat serious diseases (e.g., malaria, tuberculosis, and HIV/AIDS).

“In wealthy countries, fakes are mainly new, expensive lifestyle medicines, such as hormones, steroids and antihistamines. In recent years, fakes were revealed among expensive drugs, such as anti-cancer ones, and those highly in demand, such as antivirals,” according to EMEA [1].

Counterfeit drugs are produced using modern pharmaceutical equipment in packages of excellent printing quality. According to the World Health Organization (WHO) definition [2]: “A counterfeit medicine is one which is deliberately and fraudulently mislabeled with respect to identity and/or source. Counterfeiting can apply to both branded and generic products and counterfeit products may include products with the correct ingredients or with the wrong ingredients, without active ingredients, with insufficient active ingredient or with fake packaging.”

The growing circulation and variety of counterfeit medicines all over the world forces analysts to design different methods to recognize fakes [3], [4].

It is evident that the simplest way of testing is visual, based on special drug packages, holograms, and unique printing on the tablet surface. These methods are always used by manufacturers to protect their products. Unfortunately, everyday practice shows that such an approach is insufficient, though it is important as a first step against dissemination of fake medicines.

Testing a remedy itself leads to much more reliable conclusions. Traditional methods of rapid analysis include a simple disintegration test, simple qualitative reactions, and thin-layer chromatography (TLC). These basic drug-testing schemes were published by the WHO some 30 years ago, shortly after the report in 1982 about counterfeit drugs, mainly referring to developing countries. The testing methods were successfully implemented in Germany, Japan and the USA. However, at that time, the problem was prevalent in the developing countries, where many imported medicines (e.g., to treat malaria and tuberculosis) were fakes. To combat these counterfeit drugs, special testing kits [5] were developed for use by both foreign specialists and local laboratories.

Nowadays, these traditional methods are insufficient, as drug counterfeiting has become increasingly sophisticated. Even for the developing world, the problem is no longer straightforward, as “counterfeit antimalarial drugs are found in many developing countries, but it is challenging to differentiate between genuine and fakes due to increasing sophistication of the latter” [6].

Other analytical methods described in pharmacopoeia [e.g., gas chromatography (GC), high-performance liquid chromatography (HLPC), mass spectrometry (MS)] take time and are labor intensive, and they cannot generally be used for screening analysis. Analysts therefore have to design special methods, which are simple and rapid, and can be applied directly on site and face the challenge of the modern counterfeit market.

One such approach suggests using near-infrared (NIR) spectroscopy followed by chemometrics-based data analysis. At the end of the 1990s, NIR testing was included in pharmacopoeias of different countries (e.g., European Pharmacopoeia since 1997). NIR equipment is now widespread among analytical laboratories, as spectrometers have become cheaper and more reliable. On-site usage of inexpensive portable NIR spectrometers is feasible [6], [7]. Especially well known is the Chinese experience in small mobile laboratories equipped with NIR spectrometers [8].

Several research groups [9], [10], [11], [12], [13] have reported promising results in applying NIR spectroscopy for counterfeit-drug detection. Some of the researchers follow a traditional analytical route and try to reveal fakes by determining the concentration of an active pharmaceutical ingredient (API), which is then compared to similar medicines produced by various manufacturers [14], [15], [16], [17]. Nowadays, this approach is extensively utilized in China [18], [19]. Another approach is to investigate the types of excipient and their concentrations [20].

We consider that a remedy should be investigated as a whole and that the methods based on determination of API alone are insufficient. Proper API concentration does not guarantee that a tablet is not a fake. As a rule, a remedy is a complex composition of API(s) and a number of excipients, all indispensable for therapeutic efficacy. Not only are the proper ingredients important, but also the way the medication is manufactured. For example, the drug-release time is an essential characteristic for many types of medicines, so that the solid-state properties influence the stability and the dissolution of tablets and pellets [21]. We therefore adhere to the opinion stated in [21] that “the problem appears to be a simple one: to identify whether a drug sample is or is not the drug reported on the label”. NIR spectroscopy is an effective technique for this purpose.

Another aspect closely related to counterfeiting is generic medicines. The discussion of the pros and cons of generics is outside of the scope of this review. However, it is worth mentioning that counterfeiting refers to branded and generic drugs. Speaking of “original” or “genuine” sample, we mean legally produced and legally labeled drugs, as distinct from those that are “intentionally mislabeled so as to mislead the user with respect to composition and/or manufacturer” [22].

A more recent advancement would be NIR imaging. Theoretically, it is clear that NIR imaging is more informative [23], [24], [25], [26], but, at the same time, it is more expensive when it comes to equipment and software requirements. It would be interesting to consider a case of counterfeit-drug detection where an ordinary NIR-based approach fails, while NIR imaging succeeds. For the moment, we do not have such an example to present.

Section snippets

NIR-based approach

NIR spectroscopy has been used extensively since the 1970s. Absorption bands in the NIR region (12500–4000 cm−1) correspond mainly to overtones and combinations of fundamental vibrations, which occur in the mid-IR region [27]. Close attention is now being paid to application of NIR spectroscopy in pharmaceutical analysis and technologies [21], [28], [29]. Among the merits of NIR spectroscopy, the following are most important:

  • measurements are rapid and simple, and they can be conducted without

Counterfeits of different quality

There are different types of false drugs (e.g., placebos, medicines with a reduced concentration of API, and drugs that do not contain the proper concentrations or types of excipient). The most typical classes of the “high-quality” counterfeit drugs differing in their degree of non-conformity with the genuine drugs are as follows:

  • (1)

    medicines with wrong API(s);

  • (2)

    medicines with proper API(s) but wrong in one or several excipients; and,

  • (3)

    medicines with very similar chemical composition, which can hardly

Pre-processing of NIR data and variable selection

Before chemometric analysis is applied, it is important to decrease the influence of various sources that are not related to the chemical or physical information carried by raw spectra. They may be from instrumentation (e.g., light scattering, particle-size distribution, packing density, or the effect of tablet face and tablet position in relation to a probe beam). Usual pre-processing techniques are used to remove these effects. The most popular among them are the first and second derivatives,

Variability of genuine drugs

One of the obstacles in counterfeit-drug analysis is batch-to-batch variation in the original product. This issue is of vital importance where counterfeit drugs are of “high quality”.

To illustrate this aspect, we consider two similar medicines, which were coated tablets containing Pancreatin, produced by different pharmaceutical companies. Data set Pancreatin 1 comprised four batches of genuine pills (5 samples in each batch) and one batch of fakes (10 samples). Data set Pancreatin 2 comprised

Classification

For a reliable classification, it is important not only to collect a representative data set, but also to distribute the samples between the calibration set and the test sets in a proper way. Different studies have applied this issue to the counterfeit-drug detection (e.g., [51]).

Special attention to this aspect is also paid in the Guidance of the European Medicines Agency [52]. To illustrate this, we consider the case of Metronidazole that we discussed in Sections 3 Counterfeits of different

Discussion

Surveying the whole procedure of counterfeit-drug detection using the example of Metronidazole case, we can underline all critical points of the NIR-based approach as a general technique. The representative data set comprised 17 different batches of genuine tablets that were produced in 20 months.

Exploratory analysis of the acquired NIR spectra demonstrates production stability, so chemometric modeling may be effective for such data.

As measurements were conducted on the intact coated tablets,

Conclusions

The NIR-based approach is a rapid technique for recognizing counterfeit drugs, both evident (e.g., placebo) and sophisticated. NIR equipment is becoming common in analytical laboratories and portable NIR instruments provide their application on-site. At the same time, the efficiency of the NIR approach is determined by the quality of data processing. The following main factors should be taken into account and often define the success of the overall procedure:

  • (1)

    There is a great variety in the

References (52)

  • F.E. Dowell et al.

    J. Pharm. Biomed. Anal.

    (2008)
  • O.Ye. Rodionova et al.

    Anal. Chim. Acta

    (2005)
  • P. Chalus et al.

    Talanta

    (2005)
  • X.-M. Chong et al.

    Vib. Spectrosc.

    (2009)
  • I. Baer et al.

    Forensic Sci. Int.

    (2007)
  • Y. Roggo et al.

    J. Pharm. Biomed. Anal.

    (2007)
  • C. Gendrin et al.

    J. Pharm. Biomed. Anal.

    (2008)
  • C. Ravn et al.

    J. Pharm. Biomed. Anal.

    (2008)
  • J.M. Amigo et al.

    Trends Anal. Chem.

    (2008)
  • M. Blanco et al.

    Trends Anal. Chem.

    (2002)
  • P. de Peinder et al.

    J. Pharm. Biomed. Anal.

    (2008)
  • M.P. Derde et al.

    Anal. Chim. Acta

    (1986)
  • Y. Roggo et al.

    Talanta

    (2010)
  • S. Wold

    Pattern Recognition

    (1976)
  • R. De Maesschalck et al.

    Chemom. Intell. Lab. Syst.

    (1999)
  • M. Daszykowski et al.

    Chemom. Intell. Lab. Syst.

    (2007)
  • J. Luypaert et al.

    J. Pharm. Biomed. Anal.

    (2004)
  • Q. Guo et al.

    Anal. Chim. Acta

    (2001)
  • O.Ye. Rodionova et al.

    Anal. Chim. Acta

    (2009)
  • A. Hoskuldsson

    Chemom. Intell. Lab. Syst.

    (2001)
  • C. Abrahamsson et al.

    Chemom. Intell. Lab. Syst.

    (2003)
  • C.S. Soh et al.

    Chemom. Intell. Lab. Syst.

    (2008)
  • W. WU et al.

    Chemom. Intell. Lab. Syst.

    (1996)
  • ...
  • World Health Organization (WHO), Counterfeit Drugs: Guidelines for the Development of Measures to Combat Counterfeit...
  • A.K. Deisingh

    Analyst (Cambridge, UK)

    (2005)
  • Cited by (0)

    Note 1: All medicines described in this paper are given their pharmaceutical names not their manufacturer names. This is done in accordance with agreement with the institution that provided us with counterfeit-drug samples.

    ☆☆

    Note 2: Raw spectra for datasets “Metronidazole” and “Pancreatin 2” are located at the web-site http://rcs.chph.ras.ru/data/

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