Ames test study designs for nitrosamine mutagenicity testing: qualitative and quantitative analysis of key assay parameters.

The robust control of genotoxic N-nitrosamine (NA) impurities is an important safety consideration for the pharmaceutical industry, especially considering recent drug product withdrawals. NAs belong to the 'cohort of concern' list of genotoxic impurities (ICH M7) because of the mutagenic and carcinogenic potency of this chemical class. In addition, regulatory concerns exist regarding the capacity of the Ames test to predict the carcinogenic potential of NAs because of historically discordant results. The reasons postulated to explain these discordant data generally point to aspects of Ames test study design. These include vehicle solvent choice, liver S9 species, bacterial strain, compound concentration, and use of pre-incubation versus plate incorporation methods. Many of these concerns have their roots in historical data generated prior to the harmonization of Ames test guidelines. Therefore, we investigated various Ames test assay parameters and used qualitative analysis and quantitative benchmark dose modelling to identify which combinations provided the most sensitive conditions in terms of mutagenic potency. Two alkyl-nitrosamines, N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) were studied. NDMA and NDEA mutagenicity was readily detected in the Ames test and key assay parameters were identified that contributed to assay sensitivity rankings. The pre-incubation method (30-min incubation), appropriate vehicle (water or methanol), and hamster-induced liver S9, alongside Salmonella typhimurium strains TA100 and TA1535 and Escherichia coli strain WP2uvrA(pKM101) provide the most sensitive combination of assay parameters in terms of NDMA and NDEA mutagenic potency in the Ames test. Using these parameters and further quantitative benchmark dose modelling, we show that N-nitrosomethylethylamine (NMEA) is positive in Ames test and therefore should no longer be considered a historically discordant NA. The results presented herein define a sensitive Ames test design that can be deployed for the assessment of NAs to support robust impurity qualifications.

Predictive Fault Diagnosis for Ship Photovoltaic Modules Systems Applications.

In this paper, an application for the management and supervision by predictive fault diagnosis (PFD) of solar power generation systems is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for measuring and supervising the parameters inherent to solar power generation and renewable energy supply are applied. The importance of renewable power generation systems in ships is discussed, as well as the causes of photovoltaic modules (PVMs) aging due to superimposed causes of degradation, which is a natural and inexorable phenomenon that affects photovoltaic installations in a special way. In ships, PVMs are doubly exposed to inclement weather (solar radiation, cold, rain, dust, humidity, snow, wind, electrical storms, etc.), pollution, and a particularly aggressive environment in terms of corrosion. PFD techniques for the real-world installation and safe navigation of PVMs are discussed. A specific method based on the online analysis of the time-series data of random and seasonal I-V parameters is proposed for the comparative trend analyses of solar power generation. The objective is to apply PFD using as predictor symptom parameter (PS) the generated power decrease in affected PVMs. This PFD method allows early fault detection and isolation, whose appearance precedes by an adequate margin of maneuver, from the point of view of maintenance tasks applications. This early detection can stop the cumulative degradation phenomenon that causes the development of the most frequent and dangerous failure modes of solar modules, such as hot-spots. It is concluded that these failure modes can be conveniently diagnosed by performing comparative trend analyses of the measured power parameters by NMEA sensors.

Marine NMEA 2000 Smart Sensors for Ship Batteries Supervision and Predictive Fault Diagnosis.

In this paper, an application for the management, supervision and failure forecast of a ship's energy storage system is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for the measurement and supervision of the parameters inherent to energy storage and energy supply are reviewed. The importance of energy storage systems in ships, the causes and models of battery aging, types of failures, and predictive diagnosis techniques for valve-regulated lead-acid (VRLA) batteries used for assisted and safe navigation are discussed. In ships, battery banks are installed in chambers that normally do not have temperature regulation and therefore are significantly conditioned by the outside temperature. A specific method based on the analysis of the time-series data of random and seasonal factors is proposed for the comparative trend analyses of both the battery internal temperature and the battery installation chamber temperature. The objective is to apply predictive fault diagnosis to detect any undesirable increase in battery temperature using prior indicators of heat dissipation process failure-to avoid the development of the most frequent and dangerous failure modes of VRLA batteries such as dry out and thermal runaway. It is concluded that these failure modes can be conveniently diagnosed by easily recognized patterns, obtained by performing comparative trend analyses to the variables measured onboard by NMEA sensors.

Long-term monitoring and risk assessment of N-nitrosamines in the finished water of drinking water treatment plants in South Korea.

Approximately 99.1% of South Koreans have access to drinkable tap water from river basins. Due to such a high access rate, the South Korean government has been running, since 2013, a long-term program for monitoring the quality of tap water for drinking. Under this program, the maximum allowed concentrations of N-nitroso-di-n-methylamine (NDMA) and N-nitrosomethylethylamine (NMEA) are defined and applied. In this study, the data from this monitoring program were used to investigate the changes in six N-nitrosamine substances in the finished water of 33 drinking water treatment plants (DWTPs) in South Korea from 2013 to 2020, based on time and location. The effect of the applied water treatment steps on the appearance of N-nitrosamines was analyzed. The excess cancer risk (ECR) due to the oral intake of these substances was assessed. The results before the maximum allowed concentrations of NDMA and NMEA were defined showed that the oral intake ECR of these substances exceeded the carcinogenesis risk of one per one million people per year. After the maximum allowed concentrations of the substances were applied, the concentrations of the substances in the finished water of the DWTPs significantly dropped. The drinking water treated through sand filtration, and then with granular activated carbon, showed the highest efficiency in preventing the appearance of NDMA. Considering the potency of N-nitrosamines in tap water for drinking, the levels of these substances in the finished water of DWTPs in South Korea should be continuously monitored.

The contamination of valsartan and other sartans, part 1: New findings.

In July 2018 one of the bestselling antihypertensive agents valsartan manufactured in China was found to be contaminated by the "probably carcinogenic" nitrosamine N-nitrosodimethylamine (NDMA), followed by the detection of N-nitrosodiethylamine (NDEA) by us and others soon after. Our work also revealed that two additional non-nitrosamine contaminations valeramide (VLA) and N,N-dimethylvaleramide (VLA-DEM) were present in sartan tablets. Early measurements by others and us were performed by GC-MS or GC-MS/MS, which does not reach the sensitivity needed to find and quantitate trace levels of NDMA and NDEA. A highly sensitive LC-MS/MS method with APCI ionization was developed to detect and quantitate NDMA, NDEA, VLA and VLA-DIM in 152 sartan tablets from 8 structurally different sartan molecules. Good linearity for each compound could be demonstrated over calibration ranges in the lower nanograms. The assay for all substances was accurate and precise. With this method, a LLOQ of 0.00026 ppm for NDMA and 0.00013 ppm for NDEA could be achieved. NDMA, NDEA, VLA and VLA-DIM were found in 21 (13.8%), 9 (5.9%), 13 (8.6%) and 7 (4.6) % of the tablets, respectively. In addition, one candesartan product was found contaminated with NDEA. The implications of our findings for the testing of pharmaceutical products are discussed.