Search

BackgroundOver the past 4 decades, obesity has escalated into a global epidemic, with its worldwide prevalence nearly tripling. Pharmacological treatments have evolved with the recent development of glucagon-like peptide 1 agonists, such as semaglutide. However, off-label use of drugs such as Ozempic for cosmetic weight loss has surged in popularity, raising concerns about potential misuse and the emergence of substandard and falsified products in the unregulated supply chain. ObjectiveThis study aims to conduct a multifactor investigation of product quality and patient safety risks associated with the unregulated online sale of semaglutide by examining product availability and vendor characteristics and assessing product quality through test purchases. MethodsWe used a complex risk and quality assessment methodology combining online market surveillance, search engine results page analysis, website content assessment, domain traffic analytics, conducting targeted product test purchases, visual quality inspection of product packaging, microbiological sterility and endotoxin contamination evaluation, and quantitative sample analysis using liquid chromatography coupled with mass spectrometry. ResultsWe collected and evaluated 1080 links from search engine results pages and identified 317 (29.35%) links belonging to online pharmacies, of which 183 (57.7%) led to legal pharmacies and 134 (42.3%) directed users to 59 unique illegal online pharmacy websites. Web traffic data for the period between July and September 2023 revealed that the top 30 domains directly or indirectly affiliated with illegal online pharmacies accumulated over 4.7 million visits. Test purchases were completed from 6 illegal online pharmacies with the highest number of links offering semaglutide products for sale without prescription at the lowest price range. Three injection vial purchases were delivered; none of the 3 Ozempic prefilled injection pens were received due to nondelivery e-commerce scams. All purchased vials were considered probable substandard and falsified products, as visual inspection indicated noncompliance in more than half (59%-63%) of the evaluated criteria. The semaglutide content of samples substantially exceeded labeled amounts by 28.56%-38.69%, although no peptide-like impurities were identified. The lyophilized peptide samples were devoid of viable microorganisms at the time of testing; however, endotoxin was detected in all samples with levels ranging between 2.1645 EU/mg and 8.9511 EU/mg. Furthermore, the measured semaglutide purity was significantly low, ranging between 7.7% and 14.37% and deviating from the 99% claimed on product labels by manufacturers. ConclusionsGlucagon-like peptide 1 agonist drugs promoted for weight loss, similar to erectile dysfunction medications more than 2 decades ago, are becoming the new blockbuster lifestyle medications for the illegal online pharmacy market. Protecting the pharmaceutical supply chain from substandard and falsified weight loss products and raising awareness regarding online medication safety must be a public health priority for regulators and technology platforms alike.

In recent years, several changes have occurred in the management of chronic immunological conditions with the emerging use of targeted therapies. This two-phase cross-sectional study was conducted through structured in-person interviews in 2018–2019 and 2022. Additional data sources included ambulatory medical records and the itemized reimbursement reporting interface of the National Health Insurance Fund. Drug interactions were analyzed using the UpToDate Lexicomp, Medscape drug interaction checker, and Drugs.com databases. The chi-square test was used, and odds ratios (ORs) were calculated. In total, 185 patients participated. In 53% of patients (n = 53), a serious drug–drug interaction (DDI) was identified (mean number: 1.07 ± 1.43, 0–7), whereas this value was 38% (n = 38) for potential drug–supplement interactions (mean number: 0.58 ± 0.85, 0–3) and 47% (n = 47) for potential targeted drug interactions (0.72 ± 0.97, 0–5) in 2018. In 2022, 78% of patients (n = 66) were identified as having a serious DDI (mean number: 2.27 ± 2.69, 0–19), 66% (n = 56) had a potential drug–supplement interaction (mean number: 2.33 ± 2.69, 0–13), and 79% (n = 67) had a potential targeted drug interactions (1.35 ± 1.04, 0–5). Older age (>60 years; OR: 2.062), female sex (OR: 3.387), and polypharmacy (OR: 5.276) were identified as the main risk factors. Screening methods and drug interaction databases do not keep pace with the emergence of new therapeutics.

Introduction: The public health threat of substandard and falsified medicines has been well known in the last two decades, and several studies focusing on the identification of products affected and preventing consumption have been published. However, the number of these products reaching patients and causing health consequences and adverse drug reactions is not a well-researched area.Objectives: Our aim was to identify and describe the characteristics of cases that are related to adverse drug reactions potentially originating from counterfeit medication using publicly available pharmacovigilance data.Methods: A descriptive study was performed based on pharmacovigilance data retrieved from Individual Case Safety Reports (ICSRs) identified in the European Medicines Agency’s EudraVigilance and FDA Adverse Event Reporting System (FAERS) databases in April 2022 using selected MedDRA preferred terms: counterfeit product administered, product counterfeit, product label counterfeit, product packaging counterfeit, suspected counterfeit product, adulterated product, product tampering, and suspected product tampering. ICSRs were analyzed by age and gender, by year of reporting, region of origin, reporter’s profession, and severity of the outcome. The disproportionality method was used to calculate pharmacovigilance signal measures.Results: A total of 5,253 cases in the FAERS and 1,049 cases in the EudraVigilance database were identified, generally affecting middle-aged men with a mean age of 51.055 (±19.62) in the FAERS and 64.18% of the cases between 18 and 65 years, while the male to female ratios were 1.18 and 1.5. In the FAERS database, we identified 138 signals with 95% confidence interval including sildenafil (n = 314; PRR, 12.99; ROR, 13.04; RRR, 11.97), tadalafil (n = 200; PRR, 11.51; ROR, 11.55; RRR, 10.94), and oxycodone (n = 190; PRR, 2.47; ROR, 2.14; RRR, 2.47). While in the EV data 31, led by vardenafil (n = 16, PRR = 167.19; 101.71–274.84; 95% CI, RRR = 164.66; 100.17–270.66; 95% CI, ROR = 169.47; 103.09–278.60; 95% CI, p < 0.001), entecavir (n = 46, PRR = 161.26, RRR = 154.24, ROR = 163.32, p < 0.001), and tenofovir (n = 20, PRR = 142.10, RRR = 139.42, ROR = 143.74, p < 0.001).Conclusion: The application of pharmacovigilance datasets to identify potential counterfeit medicine ADRs can be a valuable tool in recognition of potential risk groups of consumers and the affected active pharmaceutical ingredients and products. However, the further development and standardization of ADR reporting, pharmacovigilance database analysis, and prospective and real-time collection of potential patients with health consequences are warranted in the future.

Mycotoxins are frequent toxic contaminants in foods and beverages, causing a significant health threat. Interactions of mycotoxins with biotransformation enzymes (e.g., cytochrome P450 enzymes, sulfotransferases, and uridine 5′-diphospho-glucuronosyltransferases) may be important due to their possible detoxification or toxic activation during enzymatic processes. Furthermore, mycotoxin-induced enzyme inhibition may affect the biotransformation of other molecules. A recent study described the strong inhibitory effects of alternariol and alternariol-9-methylether on the xanthine oxidase (XO) enzyme. Therefore, we aimed to test the impacts of 31 mycotoxins (including the masked/modified derivatives of alternariol and alternariol-9-methylether) on XO-catalyzed uric acid formation. Besides the in vitro enzyme incubation assays, mycotoxin depletion experiments and modeling studies were performed. Among the mycotoxins tested, alternariol, alternariol-3-sulfate, and α-zearalenol showed moderate inhibitory actions on the enzyme, representing more than tenfold weaker impacts compared with the positive control inhibitor allopurinol. In mycotoxin depletion assays, XO did not affect the concentrations of alternariol, alternariol-3-sulfate, and α-zearalenol in the incubates; thus, these compounds are inhibitors but not substrates of the enzyme. Experimental data and modeling studies suggest the reversible, allosteric inhibition of XO by these three mycotoxins. Our results help the better understanding of the toxicokinetic interactions of mycotoxins.