Assessment of correlations between sildenafil use and comorbidities and lifestyle factors using wastewater-based epidemiology.

Sildenafil (SIL) is widely used to treat erectile dysfunction. Information on its consumption and the factors influencing its use is limited in China. In this study, we sampled composite influent wastewater samples from 33 Chinese cities and analyzed SIL using liquid chromatography-tandem mass spectrometry. SIL consumption was estimated using wastewater-based epidemiology (WBE) and ranged from 10.6 mg/d/1000 people to 132 mg/d/1000 people, with a mean of 53 mg/d/1000 people. Prescription sales (3570 kg) accounted for 13.3% of the estimated SIL use (26842 kg) in 2018, thereby implying that SIL illicit use was greater than prescription use in China. Some regional differences were observed in SIL use, which was significantly higher in North China than South China (p < 0.05), thereby reflecting that the prevalence of SIL was affected by differences in lifestyle and socioeconomic factors. We found significant positive correlations between SIL use and consumption of allopurinol, hydrochlorothiazide, nicotine, and alcohol, thereby suggesting that the prevalence of SIL was associated with the prevalence of gout, hypertension, smoking, and drinking. Moreover, age structures, internet use, and marriage rates were positively correlated with SIL use, whereas the unemployment rate was negatively correlated with SIL use. Our study demonstrates that WBE is valuable for medical research to investigate licit and illicit drug use and to assess the underlying associations of different chemical uses.

Detection Method of Falsified Medicines by Using a Low-Cost Raman Scattering Spectrometer Combined with Soft Independent Modeling of Class Analogy and Partial Least Squares Discriminant Analysis.

There are many reports of falsified medicines that may cause harm to patients. A rapid and simple method of identifying falsified medicines that could be used in the field is required. Although Raman scattering spectroscopy has become popular as a non-destructive analysis, few validation experiments on falsified medicines that are actually distributed on the market have been conducted. In this study, we validated a discriminant analysis using an ultra-compact, portable, and low-cost Raman scattering spectrometer combined with multivariate analysis. The medicines were three types of erectile dysfunction therapeutic tablet and one type of antifungal tablet: tadalafil (Cialis), vardenafil hydrochloride (Levitra), sildenafil citrate (Viagra), and fluconazole (Diflucan), which is sometimes advertised as female Viagra. For each medicine, the authentic standard product and products obtained by personal import via the internet (genuine or falsified) were used. Discriminant analyses were performed on the Raman spectra combined with soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). It was possible to identify all falsified samples by SIMCA using the standard product model for all four products. Using the PLS-DA using the PLS models of the four standard products, falsified Levitra and Diflucan samples were classified correctly, although some falsified Cialis and all Viagra samples also belonged to the standard class. In this study, SIMCA might be more suitable than PLS-DA for identifying falsified medicines. A spectroscopic module that combines the low-cost Raman scattering spectroscopy with SIMCA might contribute to the rapid identification of falsified medicines in the field.

Falsified vardenafil tablets available online.

It is often reported that falsified medicines have harmful effects on patients both Japan and abroad. In this study, we purchased vardenafil tablets on the internet and investigated their quality and authenticity using visual observations, authenticity investigations, non-destructive tests (handheld NIR and Raman spectroscopy), and quality analyses (active ingredient content and tablet dissolution rate). We used genuine 20-mg Levitra tablets that were sold in Japan and tablets from Bayer AG (Germany) as controls. In April 2015, we obtained 28 samples from 15 websites on the internet. Our authenticity investigations revealed that 11 (40%) were genuine products and 17 (60%) were falsified products. Handheld NIR and Raman results revealed that the falsified products had different spectra to the genuine products. Principal component analysis of the NIR and Raman spectra showed variation among the falsified products. The 11 genuine products were of good quality, and the 17 falsified products were of poor quality. The falsified products contained sildenafil (the active ingredient of Viagra) or tadalafil (the active ingredient of Cialis) instead of vardenafil. Our results show that falsified Vardenafil tablets are sold on the internet and that it is important to prevent illegal internet sales and increase consumer awareness of the presence of falsified medicines.

An LDI-MSI approach for targeted and untargeted differentiation and assessment of pharmaceutical formulations.

Falsified, counterfeit and adulterated medicines are an endemic problem worldwide that results in both monetary and health-related losses. Developing fast and reliable methods that are able to present a timely result based on the drug's spectral profile is an effort that is sure to benefit those involved in the whole distribution chain. We propose herein a Laser Desorption/Ionization imaging-based method that provides simple and minimal sample preparation; this method is capable of providing specific markers that characterize adulterations, using as proof of concept one of the most adulterated drug products for oral use, sildenafil. Our approach is able to provide quality markers, which can be applied in the fast screening of any product within the same molecular class. This same strategy may be a useful alternative to provide accurate measurements with high specificity for unraveling contaminants and/or byproducts in virtually any given pharmaceutical product.

Detection of adulterated drugs in traditional Chinese medicine and dietary supplements using hydrogen as a carrier gas.

Helium, a minor component of natural gas and radioactive minerals, is most commonly used as a carrier in gas chromatography-mass spectrometry (GC-MS). Its scarcity leads to limited availability and higher costs. In this experiment, hydrogen from a safe source of a hydrogen generator was tested as a substitutive carrier gas for the detection of adulterant in traditional Chinese medicine (TCM) and food supplements by GC-MS analysis. We found that the limits of detection (LODs) of using hydrogen were from 10 to 1000 µg/g. The levels of LODs tested among 170 drugs remain the same whether hydrogen or helium was used as a carrier gas with the exception of 7 drugs-benzbromarone, estradiol benzoate, bezafibrate, mefenamic acid, oxymetholone, piperidenafil and cetilistat. The real sample analysis results using hydrogen were as satisfactory as those using helium. In addition, the retention time was shortened after the chromatographic performance was optimized. In summary, it is worth considering hydrogen as a carrier gas due to its affordable costs, energy efficiency, carbon reduction and chromatographic advantages to detect adulterated drugs in TCM and dietary supplement using GC-MS.

The Monte Carlo validation framework for the discriminant partial least squares model extended with variable selection methods applied to authenticity studies of Viagra® based on chromatographic impurity profiles.

The aim of this work was to develop a general framework for the validation of discriminant models based on the Monte Carlo approach that is used in the context of authenticity studies based on chromatographic impurity profiles. The performance of the validation approach was applied to evaluate the usefulness of the diagnostic logic rule obtained from the partial least squares discriminant model (PLS-DA) that was built to discriminate authentic Viagra® samples from counterfeits (a two-class problem). The major advantage of the proposed validation framework stems from the possibility of obtaining distributions for different figures of merit that describe the PLS-DA model such as, e.g., sensitivity, specificity, correct classification rate and area under the curve in a function of model complexity. Therefore, one can quickly evaluate their uncertainty estimates. Moreover, the Monte Carlo model validation allows balanced sets of training samples to be designed, which is required at the stage of the construction of PLS-DA and is recommended in order to obtain fair estimates that are based on an independent set of samples. In this study, as an illustrative example, 46 authentic Viagra® samples and 97 counterfeit samples were analyzed and described by their impurity profiles that were determined using high performance liquid chromatography with photodiode array detection and further discriminated using the PLS-DA approach. In addition, we demonstrated how to extend the Monte Carlo validation framework with four different variable selection schemes: the elimination of uninformative variables, the importance of a variable in projections, selectivity ratio and significance multivariate correlation. The best PLS-DA model was based on a subset of variables that were selected using the variable importance in the projection approach. For an independent test set, average estimates with the corresponding standard deviation (based on 1000 Monte Carlo runs) of the correct classification rate, sensitivity, specificity and area under the curve were equal to 96.42% ± 2.04, 98.69% ± 1.38, 94.16% ± 3.52 and 0.982 ± 0.017, respectively.