A multivariate-based wavenumber selection method for classifying medicines into authentic or counterfeit classes

Combining wavelength importance ranking to the random forest classifier to analyze multiclass spectral data

Near Infrared (NIR) is a type of vibrational spectroscopy widely used in different areas to characterize substances. NIR datasets are comprised of absorbance measures on a range of wavelengths (λ). Typically noisy and correlated, the use of such datasets tend to compromise the performance of several statistical techniques; one way to overcome that is to select portions of the spectra in which wavelengths are more informative. In this paper we investigate the performance of the Random Forest (RF) classifier associated with several wavelength importance ranking approaches on the task of classifying product samples into categories, such as quality levels or authenticity. Our propositions are tested using six NIR datasets comprised of two or more classes of food and pharmaceutical products, as well as illegal drugs. Our proposed classification model, an integration of the χ² ranking score and the RF classifier, substantially reduced the number of wavelengths in the dataset, while increasing the classification accuracy when compared to the use of complete datasets. Our propositions also presented good performance when compared to competing methods available in the literature.

Wavenumber selection based on Singular Value Decomposition for sample classification

The dissemination of falsified medicines is a public health risk. Techniques such as attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy are commonly adopted for fraudulent drug detection. However, the spectrum generated by the ATR-FTIR typically results in hundreds of wavenumbers, reducing the performance of classification methods aimed at discriminating between authentic and falsified medicines. This article proposes a novel method for selecting a reduced size subset of wavenumbers that improves the classifier performance. The singular value decomposition SVD is used to generate a wavenumber importance index. An iterative process creates k-nearest neighbor (KNN) models by adding the wavenumbers in a decreasing order according to the importance index. Wavenumbers that increase classification accuracy are selected. When applied to Cialis® ATR-FTIR data, the proposed approach retained average 0.51% of the original wavenumbers with 100% accurate classifications; as for the Viagra® data set, the method yielded perfect classifications retaining average 0.17% of the original wavenumbers.

Instrumental neutron activation analysis (INAA) and liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) characterisation of sildenafil based products seized on the Italian illegal market

The commerce of illegal and counterfeit medicinal products on internet is a serious criminal problem. Drugs for erectile dysfunction such as phosphodiesterase type 5 inhibitor are the most commonly counterfeited medicines in Europe. The search of possible toxic chemical substances in seized products is needed. Moreover, the profiling of the material can be the source of relevant forensic information. For the first time a combined approach based on liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) and instrumental neutron activation analysis (INAA) is proposed and tested, allowing characterisation of both authentic and illegal pharmaceuticals containing sildenafil seized in Italy. LC-HRMS allowed the detection and identification of unknown impurities not reported on labels in illegal products and the quantitation of the sildenafil. INAA showed to be suitable to provide both qualitative and quantitative information for forensic purposes on 23 elements, allowing discrimination between legal and illegal products.

Spectroscopic and Spectrometric Methods Used for the Screening of Certain Herbal Food Supplements Suspected of Adulteration

Purpose: This study was carried out in order to find a reliable method for the fast detection of adulterated herbal food supplements with sexual enhancement claims. As some herbal products are advertised as "all natural", their "efficiency" is often increased by addition of active pharmaceutical ingredients such as PDE-5 inhibitors, which can be a real health threat for the consumer.

Methodes: Adulterants, potentially present in 50 herbal food supplements with sexual improvement claims, were detected using 2 spectroscopic methods - Raman and Fourier Transform Infrared - known for reliability, reproductibility, and an easy sample preparation. GC-MS technique was used to confirm the potential adulterants spectra.

Results: About 22% (11 out of 50 samples) of herbal food supplements with sexual enhancement claims analyzed by spectroscopic and spectrometric methods proved to be "enriched" with active pharmaceutical compounds such as: sildenafil and two of its analogues, tadalafil and phenolphthalein. The occurence of phenolphthalein could be the reason for the non-relevant results obtained by FTIR method in some samples. 91% of the adulterated herbal food supplements were originating from China.

Conclusion: The results of this screening highlighted the necessity for an accurate analysis of all alleged herbal aphrodisiacs on the Romanian market. This is a first such a screening analysis carried out on herbal food supplements with sexual enhancement claims.

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.

Counterfeit medicines in Peru: a retrospective review (1997-2014)

OBJECTIVE

To consolidate and assess information on counterfeit medicines subject to pharmaceutical alerts issued by the Peruvian Medicines Regulatory Authority over 18 years (1997-2014) of health monitoring and enforcement.

DESIGN

A retrospective review of drug alerts.

SETTING

A search of the website of the General Directorate of Medicines, Supplies and Drugs (DIGEMID) of the Ministry of Health of Peru for drug alerts issued between 1997 and 2014.

ELIGIBILITY CRITERIA

Drug alerts related to counterfeit medicines.

RESULTS

A total of 669 DIGEMID alerts were issued during the study period, 354 (52.91%) of which cover 1738 cases of counterfeit medicines (many alerts deal with several cases at a time). 1010 cases (58.11%) involved pharmaceutical establishments and 349 (20.08%) involved non-pharmaceutical commercial outlets. In 126 cases (7.25%), counterfeit medicines were seized in an unauthorised trade (without any marketing authorisation); in 253 cases (14.56%) the type of establishment or business associated with the seized product was not identified.

CONCLUSIONS

Counterfeit medicines are a serious public health problem in Peru. A review of the data cannot determine whether counterfeit medicines in Peru increased during the study period, or if monitoring by different government health agencies highlighted the magnitude of the problem by providing more evidence. The problem is clearly structural, since the majority of cases (58.11% of the total) were detected in legitimate supply chains. Most counterfeit medicines involve staple pharmaceutical products and common dosage forms. Considerable work remains to be done to control the serious problem of counterfeit medicines in Peru.