European fingerprint study on omeprazole drug substances using a multi analytical approach and chemometrics as a tool for the discrimination of manufacturing sources

Like drug products, Active Pharmaceutical Ingredients (APIs) are subject to substandard and falsification issues, which represent a threat to patient health. In order to monitor the quality of drug substances and prevent the use of non-compliant APIs, Official Medicine Control Laboratories work together in a European network developing coordinated strategies and programmes. The API working group proposed a market surveillance study on omeprazole and omeprazole magnesium with the objectives of controlling the pharmaceutical quality of samples, checking compliance with the monographs of the European Pharmacopoeia, and collecting analytical fingerprints that could be further used to differentiate manufacturing sources for future authenticity investigations. The study described in this article reports the analysis carried out by 7 European laboratories on 28 samples from 11 manufacturers with 5 analytical techniques (related substances with HPLC, residual solvents with GC-MS, near infrared spectroscopy, proton nuclear magnetic resonance spectroscopy and X-ray powder diffractometry). The large amount of resulting analytical data were centralized and treated with two chemometric methods: Principal Component Analysis and Hierarchical Clustering Analysis. Data were analyzed separately and in combination (data fusion), allowing us to conclude that NMR and XRPD were suitable to differentiate samples originating from 9 out of 11 manufacturers. Analytical fingerprints associated with chemometrics were demonstrated to be a valuable methodology to discriminate manufacturers of omeprazole and omeprazole magnesium APIs and detect future substandard and falsified APIs.

GEONs API fingerprint project: Selection of analytical techniques for clustering of sildenafil citrate API samples

Through its Active Pharmaceutical Ingredient Working Group (API-WG) the General European Official Medicines Control Laboratory (OMCL) Network (GEON), co-ordinated by the European Directorate for the Quality of Medicines & HealthCare (EDQM), regularly organises market surveillance studies for specific APIs for conformity to their monograph in the European Pharmacopoeia. During the past years some studies were combined with a fingerprint study of the APIs. The idea is to obtain a fingerprint for each manufacturer of the API under investigation, allowing the OMCL network to identify future samples as well as to detect substandard and falsified APIs. This paper reports the results of the latest fingerprint study, organised on sildenafil citrate API samples. Seventy-nine samples from 14 different manufacturers were collected throughout the Network. Fingerprint data was collected through Mid-Infrared spectroscopy, Raman spectroscopy, liquid chromatography for related substances, gas chromatography for residual solvents, X-ray diffraction and Nuclear Magnetic Resonance (NMR) spectroscopy. Chemometrics applied to the collected data showed that all manufacturers could be discriminated based on the data of only three of these tests, i.e. gas chromatography for residual solvents, X-ray diffraction and proton NMR. Suspicious API samples for sildenafil citrate will therefore be analysed in the future with the selected techniques in order to link the sample to a manufacturer or demonstrate the absence of such link. If the sample cannot be attributed to one of the manufacturers, further analysis and research on provenance and identity will be required. Of course, if the suspected sample claims to originate from one of the manufacturers included in the study, analysis can be limited to the test distinguishing this manufacturer.

A strategy based on fingerprinting and chemometrics for the detection of regulated plants in plant food supplements from the Belgian market: Two case studies

The sale and consumption of plant food supplements is increasing, especially in the western world. A lot of these supplements can be bought through internet, where a lot of illegal trade is going on. Every year seized dietary supplements are send to laboratories in order to screen for the presence of chemical adulterants or illegally added active pharmaceutical ingredients, though also herbal adulteration occurs and is given less attention. In this paper a two-step approach is presented based on fingerprints recorded by both infrared spectroscopy as liquid chromatography with UV-detection for the screening of five regulated plants used in respectively dietary supplements for slimming and potency enhancement. Both types of fingerprints are combined with chemometric techniques in order to obtain classification models. A first classification model is calculated based on the infrared data and gives a first idea about the plant suspected to be present. This suspicion is then confirmed based on binary classification models calculated with the chromatographic data obtained for the suspected plant. In general, good classification models were obtained for each of the targeted plants. The approach was applied in a small market study comprising 35 dietary supplements for slimming and 34 for male potency enhancement. In total 21 samples were found to contain one of the five targeted plants.

Chemometrics and chromatographic fingerprints to classify plant food supplements according to the content of regulated plants

Plant food supplements are gaining popularity, resulting in a broader spectrum of available products and an increased consumption. Next to the problem of adulteration of these products with synthetic drugs the presence of regulated or toxic plants is an important issue, especially when the products are purchased from irregular sources. This paper focusses on this problem by using specific chromatographic fingerprints for five targeted plants and chemometric classification techniques in order to extract the important information from the fingerprints and determine the presence of the targeted plants in plant food supplements in an objective way. Two approaches were followed: (1) a multiclass model, (2) 2-class model for each of the targeted plants separately. For both approaches good classification models were obtained, especially when using SIMCA and PLS-DA. For each model, misclassification rates for the external test set of maximum one sample could be obtained. The models were applied to five real samples resulting in the identification of the correct plants, confirmed by mass spectrometry. Therefore chromatographic fingerprinting combined with chemometric modelling can be considered interesting to make a more objective decision on whether a regulated plant is present in a plant food supplement or not, especially when no mass spectrometry equipment is available. The results suggest also that the use of a battery of 2-class models to screen for several plants is the approach to be preferred.

HS-GC-MS method for the analysis of fragrance allergens in complex cosmetic matrices

Potential allergenic fragrances are part of the Cosmetic Regulation with labelling and concentration restrictions. This means that they have to be declared on the ingredients list, when their concentration exceeds the labelling limit of 10 ppm or 100 ppm for leave-on or rinse-off cosmetics, respectively. Labelling is important regarding consumer safety. In this way, sensitised people towards fragrances might select their products based on the ingredients list to prevent elicitation of an allergic reaction. It is therefore important to quantify potential allergenic ingredients in cosmetic products. An easy to perform liquid extraction was developed, combined with a new headspace GC-MS method. The latter was capable of analysing 24 volatile allergenic fragrances in complex cosmetic formulations, such as hydrophilic (O/W) and lipophilic (W/O) creams, lotions and gels. This method was successfully validated using the total error approach. The trueness deviations for all components were smaller than 8%, and the expectation tolerance limits did not exceed the acceptance limits of ± 20% at the labelling limit. The current methodology was used to analyse 18 cosmetic samples that were already identified as being illegal on the EU market for containing forbidden skin whitening substances. Our results showed that these cosmetic products also contained undeclared fragrances above the limit value for labelling, which imposes an additional health risk for the consumer.

Comparative dissolution study on counterfeit medicines of PDE-5 inhibitors

Counterfeit medicines are a growing problem in both developing and industrialised countries. In general the evaluation of these medicines is limited to the identification and the dosage of the active ingredients. In this study in vitro dissolution tests were conducted on two sets of counterfeit medicines containing PDE-5 inhibitors (sildenafil citrate and tadalafil). The dissolution profiles were statistically compared to the ones of the genuine products using the f₂-method and a comparison at each time point using the Cochran test.

The results showed low equivalences between counterfeit and genuine products as well as higher variations around the mean dissolution value at the different time points for the counterfeit products.

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.

Evaluation of the residual solvent content of counterfeit tablets and capsules

A group of counterfeit samples of Viagra and Cialis were screened for their residual solvent content and compared to the content of the genuine products. It was observed that all counterfeit samples had higher residual solvent contents compared to the genuine products. A more diverse range of residual solvents was found as well as higher concentrations. In general these concentrations did not exceed the international imposed maximum limits. Only in a few samples the limits were exceeded. A Projection Pursuit analysis revealed clusters of samples with similar residual solvent content, possibly enabling some future perspectives in forensic research.