A validated GC–MS method for the determination and quantification of residual solvents in counterfeit tablets and capsules

Clustering of Tadalafil API Samples According to their Manufacturer in the Context of API Falsification Detection

This paper reports the results of the active pharmaceutical ingredient (API) fingerprint study, organised by the General European Official Medicines Control Laboratory Network (GEON), on tadalafil. A classical market surveillance study, evaluating compliance to the European Pharmacopoeia, was combined with a fingerprint study, the latter to obtain characteristic data for the different manufacturers, allowing the network laboratories to conduct authenticity tests for future samples, as well as to detect substandard and falsified samples. In total, 46 tadalafil API samples from 13 different manufacturers were collected. For all samples fingerprint data was collected through analysis of impurities and residual solvents, mass spectrometric screening, X-ray powder diffraction and proton nuclear magnetic resonance (1H-NMR). Chemometric analysis revealed that all manufacturers could be characterised based on the impurity, residual solvent and 1H-NMR data. Future suspicious samples in the network will therefore be analysed with these techniques in order to attribute the sample to one of the manufacturers. If the sample cannot be attributed, a more profound investigation will be necessary to reveal the origin of the sample. In cases where the suspect sample is claimed to be from one of the manufacturers included in this study, analysis can be limited to the test distinguishing that manufacturer.

Identification of pressed and extracted vegetable oils by headspace GC-MS

Edible vegetable oils are produced either by mechanical pressing or extraction. Although pressing retains the inherent flavor and nutritional value of the oil, the oil yield is low and the process expensive. Extraction methods have high oil yields, low processing costs, and economic benefits; however, No. 6 solvent, which may pose potential risks to human health, is commonly used in the extraction and cleaning process. Differentiating extracted oil containing these solvents from pressed oil, for quality control, based on visual appearance is difficult. Hence, in this study, an identification method using the characteristic components of solvent No. 6 under optimized headspace Gas chromatography-mass spectrometry (GC-MS) conditions was established. It also provided a reference for quality control of industrial production by estimating the amount of solvent present in the oil. Results showed that, in addition to five main components (2-methylpentane, 3-methylpentane, and n-hexane, Methylcyclopentane, Cyclohexane), accounting for 97% of the solvent, No. 6 solvent also contains 16 types of organic substances, such as olefins, aromatic hydrocarbons, and polycyclic aromatic hydrocarbons. Under optimized headspace GC-MS conditions (headspace sampler equilibrium temperature = 150 °C), the No. 6 solvent exhibits high linearity over a concentration range of 0.05-1 mg/kg with a correlation coefficient of 0.999 and a detection limit of 0.01 mg/kg. Pressed and extracted oils can be determined as follows: If three or fewer main components of the No. 6 solvent are detected, and the total content of No. 6 solvent is less than 0.5 mg/kg, it is a pressed oil; if four or more main components of No. 6 solvent are detected, or the total content of No. 6 solvent is ≥0.5 mg/kg, it is confirmed as an extracted oil.

A NIR, 1H-NMR, LC-MS and chemometrics pilot study on the origin of carvedilol drug substances: a tool for discovering falsified active pharmaceutical ingredients

Falsification of drugs, entailing the use of drug substances from unknown unapproved suppliers, is one of the main concerns for the quality of medicines. Therefore, traceability of active ingredients represents an effective tool to fight the illegal trade of medicinal products. In this view, the present pilot study explores the profile of carvedilol active ingredients and possible differences related to the origin. Sixteen samples were examined by near-infrared spectroscopy (NIR), proton nuclear magnetic resonance (¹H-NMR spectrometry) and liquid chromatography mass spectrometry (LC-MS) Q-TOF and the data were analysed by principal component analysis (PCA), cluster analysis and PLSDA discriminant analysis. The results evidenced that the combined information from the three techniques gave good classification of the samples neatly distinguishing the APIs from European countries from the APIs manufactured out of Europe. In particular, NIR spectroscopy provided effective separation between European and non-European manufacturers and ¹H-NMR or LC-MS added specific information related to the separation. Concerning LC-MS Q-TOF, the analysis of multiple isobaric peaks proved to be highly predictive of the drug substance origin and emerged as a promising tool in the field of medicine traceability.

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.

Determination of certain VOCs in paints and architectural coatings by dynamic headspace gas chromatography-mass spectrometry

A quantitative method for the determination of the following VOCs: acetone, dichloromethane, dimethyl carbonate, methyl acetate, tertiary butyl acetate, chlorobenzotrifluoride (4-CBTF) and propylene carbonate in paints was developed in support of Environment and Climate Change Canada's Automotive Refinishing Product and Architectural Coatings VOC Concentration Limits regulations. These compounds are excluded from the VOC definition by Canadian Environmental Protection Act (CEPA) regulations, and their content do not contribute to the overall VOC content in products for regulatory purposes. The method is based on Dynamic Headspace GC-MS. It was determined that activated carbon is the best trapping medium for these compounds. The technique has been compared to a currently used direct injection technique, with comparable results. Contrary to the direct injection method which requires complex sample handling prior to injection in the gas chromatograph, the dynamic headspace method practically eliminates the need for sample handling allowing for much shorter sample turnover and reducing the possibility of sampling handling errors.

Determination of ethanol in foods and beverages by magnetic stirring-assisted aqueous extraction coupled with GC-FID: A validated method for halal verification

An in-house method, employing magnetic stirring-assisted aqueous extraction combined with gas chromatography-flame ionization detector, for determination of ethanol in different foods and beverages was validated according to the ISO/IEC 17025 standard. Validation parameters, including selectivity, method limits of detection (approx. 0.006 mg/g) and quantification (approx. 0.02 mg/g), linearity (R² of >0.999), trueness (relative biases of <3%), accuracy (recoveries of 96-105%), and precision (relative standard deviations of <5%), were satisfactory. The proposed method was as accurate and precise as and more sensitive than the AOAC method 2016.12, with estimated relative expanded uncertainties of around 8% for all samples. The validated method was successfully applied for determination of ethanol in 108 commercially processed foods and beverages, and it could be used for halal verification. Accordingly, this study provided a reliable method for routine quantitative analysis of ethanol in processed foods and beverages to ensure their halal integrity prior to halal certification.

Non-steroidal anti-inflammatory drugs in the environment: Where were we and how far we have come?

Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most well-known pharmaceuticals with a broad scope of properties that are widely used in human and veterinary medicine. Because of their extensive utilization, NSAIDs are commonly identified in the environment as trace emerging contaminants. Regardless of vast experience with these drugs, NSAIDs are full of contradictions that trigger major concerns for environmental researchers. A limited understanding on NSAID's occurrence, distribution and eco-toxicological effects have led to an escalated dilemma in the last decade. Thus, a broad-spectrum study covering all aspects of occurrence, detection and removal is required to meet the fundamental levels of knowledge on the effects of NSAIDs in all exposed environmental aspects. Therefore, this paper focuses on classifying the sources and entry points of residual NSAIDs. Further, detecting and regulating their concentrations in both input streams and receiving environments, along with the removal processes of this specific class of emerging compounds, in the direction of developing a management policy is comprehensively reviewed.

Application of Design Space, Uncertainty, and Risk Profile Strategies to the Development and Validation of UPLC Method for the Characterization of Four Authorized Phosphodiesterase Type 5 Inhibitors to Combat Counterfeit Drugs

BACKGROUND

Counterfeit medicines are an increasing scourge that are difficult to identify and they have become industrialized and widespread through highly organized illegal channels.

OBJECTIVE

This research aims to develop a robust method to determine four phosphodiesterase type-5 inhibitors in counterfeit drugs based on ultra-performance liquid chromatography.

METHOD

Experimental design methodology (DOE) and design space (DS) recommended by ICH Q8 were used side-by-side in the development phase to define the optimal parameters as well as the robustness of the chromatographic method. Moreover, both the uncertainty and risk profile derived from the β-content and γ-confidence tolerance interval were investigated during the validation phase to examine the performance of this method.

RESULTS

Successful chromatographic results, in a high resolution between the four active ingredients and an optimal analysis time of less than 1.6 min, were achieved at the end of the optimization phase. In addition, validation results show a low risk of future measurements outside acceptance limits set at 5%.

CONCLUSIONS

Our procedure was successfully applied in the routine phase to identify 23 illicit formulations of an erectile dysfunction drug.

HIGHLIGHTS

An efficient method for the characterization of 4 authorized phosphodiesterase in less than 1.6 min was established. A DS approach was applied to test the performance of this analytical method during analytical development. A risk profile was then carried out to approve the validity of the analytical method through the uncertainty profile approach.

Loading paclitaxel into porous starch in the form of nanoparticles to improve its dissolution and bioavailability

In this work, paclitaxel was loaded into porous starch in the form of nanoparticles (PNPS), and the properties of PNPS were investigated by using raw paclitaxel and the system of paclitaxel directly loaded into porous starch (PPS) as control groups. According to the tested results, the drug loading (DL) and encapsulation efficiency (EE) of PNPS were 14.13%±0.27% and 73.92%±0.54%, higher than that of PPS (9.79%±0.31% and 71.17%±0.67%) respectively. Compared with raw paclitaxel and PPS, PNPS exhibited the more prominent dissolution rate and bioavailability, in which the bioavailability of PPS and PNPS were 2.94 and 5.42 times of that of raw paclitaxel respectively. In addition, the IC₅₀ values of raw paclitaxel, PPS and PNPS on Lewis Lung Carcinoma (LLC) cells were 17,703.41±15.76μM, 95.10±5.32μM and 85.68±7.38μM respectively. Furthermore, the residues of acetone in PPS and PNPS were less than the ICH limit for acetone in class III solvents. To summarize, the preparation of PNPS was a potential method to improve the dissolution and bioavailability of paclitaxel.

Accuracy Profiles for Analyzing Residual Solvents in Textiles by GC-MS

Excess residual solvents (RSs) in clothes or other textiles could be toxic and pose risks to both humans and the environment. N,N-Dimethylformamide (DMF), N,N-dimethylacetamide (DMAc) and 1-methyl-2-pyrrolidinone (NMP) are important chemicals frequently used as solvents in the textile industry. Several organizations have proposed limiting DMF, DMAc and NMP in textiles, but an appropriate detection method has not been proposed. A sensitive GC-MS method for the quantification of DMF, DMAc and NMP in textiles was developed. After extraction with ethyl acetate, these RSs were separated on a DB-5MS capillary column. The oven temperature was increased from 50°C (held for 0.5 min) at 10°C/min to 120°C (held for 1 min). The method was fully validated according to the accuracy profile procedure, which is based on β-expectation tolerance intervals for the total measurement bias. Linearity was observed in the range of 0.5-10 mg/L for the solvents with limit of quantification values of 4.2, 3.5 and 2.5 mg/kg for DMF, DMAc and NMP, respectively. The repeatability and intermediate precision were <5.34% and 7.95% for DMF, 5.37% and 9.68% for DMAc, and 2.68% and 5.85% for NMP. The recoveries of DMF, DMAc and NMP were 91.2-106.3%, 89.5-97.7% and 85.6-101.3%, respectively.

Innovative Strategy for Counterfeit Analysis

Currently, counterfeit medicine is a significant issue for the pharmaceutical world, and it targets all types of therapeutic areas. The health consequences are appalling, since counterfeit medicines can contain impurities and the wrong chemical composition, and can be manufactured and/or stored in dreadful conditions. The provision of fast and reliable analytical tools can contribute to an efficient fight against this phenomenon. In this paper, an analytical strategy based on mobile and forensic laboratories is presented. The mobile equipment, composed of handheld x-ray fluorescence, Raman, infrared, and near-infrared spectrometers, and a handheld microscope, can be used as a first screening tool to detect counterfeits. The counterfeits can then be confirmed in a forensic-dedicated lab in which the chemical composition of the counterfeits is determined to evaluate the danger encountered by the patients. Relevant links with former counterfeit cases then can be revealed based on the analytical data, and can be interpreted from a forensic intelligence perspective in order to provide additional information for law enforcement.

Fighting falsified medicines: The analytical approach

Given the harm to human health, the fight against falsified medicines has become a priority issue that involves numerous actors. Analytical laboratories contribute by performing analyses to chemically characterise falsified samples and assess their hazards for patients. A wide range of techniques can be used to obtain individual information on the organic and inorganic composition, the presence of an active substance or impurities, or the crystalline arrangement of the formulation's compound. After a presentation of these individual techniques, this review puts forward a methodology to combine them. In order to illustrate this approach, examples from the scientific literature (products used for erectile dysfunction treatment, weight loss and malaria) are placed in the centre of the proposed methodology. Combining analytical techniques allows the analyst to conclude on the falsification of a sample, on its compliance in terms of pharmaceutical quality and finally on the safety for patients.

Near infrared spectroscopy for counterfeit detection using a large database of pharmaceutical tablets

Medicine counterfeiting is one of the current burdens of the pharmaceutical world. Reliable technologies have become available for the chemical analysis of suspect medicines. Near infrared spectroscopy (NIRS) allows for instance fast, specific and non-destructive authentication of pharmaceutical products. In this paper, a NIRS method is presented for the identification of 29 different pharmaceutical product families of tablets, one family containing one or more formulation (s), e.g. different dosages. This selection represents the whole tablet portfolio of our firm. The high number of product families constituted a challenge, given that the measurement of the samples, made on two similar instruments, generated a dataset of 7120 spectra. Several chemometric tools proved efficient for the identification of these medicines. The dataset was first investigated with a Principal Component Analysis (PCA) in order to provide an overview of the distribution of the samples. The K-Nearest Neighbors (KNN), the Support Vector Machines (SVM) and the Discriminant Analysis (DA) supervised classification tools were successfully applied and generated an outstanding classification rate of 100% of correct answer. The methods were then fully validated with an independent set of spectra. The DA was selected as the method for the routine analysis of suspect tablets with the Mahalanobis distance as acceptance criterion for identification. Counterfeits, generics and placebos samples, constituting a second validation set, were tested and rejected by the method. NIRS has thus been demonstrated as an efficient tool for the quick identification of a large dataset of pharmaceutical tablets and the detection of counterfeit medicines.

A simple dilute and shoot methodology for the identification and quantification of illegal insulin

The occurrence of illegal medicines is a well-established global problem and concerns mostly small molecules. However, due to the advances in genomics and recombinant expression technologies there is an increased development of polypeptide therapeutics. Insulin is one of the best known polypeptide drug, and illegal versions of this medicine led to lethal incidents in the past. Therefore, it is crucial for the public health sector to develop reliable, efficient, cheap, unbiased and easily applicable active pharmaceutical ingredient (API) identification and quantification strategies for routine analysis of suspected illegal insulins. Here we demonstrate that our combined label-free full scan approach is not only able to distinguish between all those different versions of insulin and the insulins originating from different species, but also able to chromatographically separate human insulin and insulin lispro in conditions that are compatible with mass spectrometry (MS). Additionally, we were also able to selectively quantify the different insulins, including human insulin and insulin lispro according to the validation criteria, put forward by the United Nations (UN), for the analysis of seized illicit drugs. The proposed identification and quantification method is currently being used in our official medicines control laboratory to analyze insulins retrieved from the illegal market.

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.

Determination of Residual Solvents in Linezolid by Static Headspace GC

A headspace gas chromatographic method was developed for the determination of residual solvents in linezolid active substances. The solvents include petroleum ether (60-90°C), acetone, tetrahydrofuran, ethyl acetate, methanol, dichloromethane (DCM) and pyridine. The method showed the possibility to detect the tested solvents with a linear determination correlation coefficient (r) greater than 0.9995 except for petroleum ether (0.9980). The limits of detection ranged between 0.12 μg/mL (petroleum ether) and 3.56 μg/mL (DCM), and the limits of quantity ranged between 0.41 μg/mL (petroleum ether) and 11.86 μg/mL (DCM). The method achieved good accuracy (recoveries ranging from 92.8 to 102.5%) and precision for both run-to-run and day-to-day assay (relative standard deviation ranging from 0.4 to 1.3%) for all seven solvents concerned, which were applied in the quality control of three batches of linezolid successfully.

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.

Understanding and fighting the medicine counterfeit market

Medicine counterfeiting is a serious worldwide issue, involving networks of manufacture and distribution that are an integral part of industrialized organized crime. Despite the potentially devastating health repercussions involved, legal sanctions are often inappropriate or simply not applied. The difficulty in agreeing on a definition of counterfeiting, the huge profits made by the counterfeiters and the complexity of the market are the other main reasons for the extent of the phenomenon. Above all, international cooperation is needed to thwart the spread of counterfeiting. Moreover effort is urgently required on the legal, enforcement and scientific levels. Pharmaceutical companies and agencies have developed measures to protect the medicines and allow fast and reliable analysis of the suspect products. Several means, essentially based on chromatography and spectroscopy, are now at the disposal of the analysts to enable the distinction between genuine and counterfeit products. However the determination of the components and the use of analytical data for forensic purposes still constitute a challenge. The aim of this review article is therefore to point out the intricacy of medicine counterfeiting so that a better understanding can provide solutions to fight more efficiently against it.