Prioritizing human pharmaceuticals for ecological risks in the freshwater environment of Korea

Computational modeling (in silico) methods combined with ecotoxicological experiments (in vivo) to predict the environmental risks of an antihistamine drug (loratadine)

This study employed computational modeling (in silico) methods, combined with ecotoxicological experiments (in vivo) to predict the persistence/biodegradability, bioaccumulation, mobility, and ecological risks of an antihistamine drug (Loratadine: LOR) in the aquatic compartment. To achieve these goals, four endpoints of the LOR were obtained from different open-source computational tools, namely: (i) "STP total removal"; (ii) Predicted ready biodegradability; (iii) Octanol-water partition coefficient (KOW); and (iv) Soil organic adsorption coefficient (KOC). Moreover, acute and chronic, ecotoxicological assays using non-target freshwater organisms of different trophic levels (namely, algae Pseudokirchneriella subcapitata; microcrustaceans Daphnia similis and Ceriodaphnia dubia; and fish Danio rerio), were used to predict the ecological risks of LOR. The main results showed that LOR: (i) is considered persistent (after a weight-of-evidence assessment) and highly resistant to biodegradation; (ii) is hydrophobic (LOG KOW = 5.20), immobile (LOG KOC = 5.63), and thus, it can potentially bioaccumulate and/or can cause numerous deleterious effects in aquatic species; and (iii) after ecotoxicological evaluation is considered "toxic" and/or "highly toxic" to the three trophic levels tested. Moreover, both the ecotoxicological assays and risk assessment (RQ), showed that LOR is more harmful for the crustaceans (RQcrustaceans = moderate to high risks) than for algae and fish. Ultimately, this study reinforces the ecological concern due to the indiscriminate disposal of this antihistamine drug in worldwide aquatic ecosystems.

Occurrence, removal, and prioritization of organic micropollutants in four full-scale wastewater treatment plants in Korea

This study investigated the occurrence, removal rate, and potential risks of 43 organic micropollutants (OMPs) in four municipal wastewater treatment plants (WWTPs) in Korea. Results from two-year intensive monitoring confirmed the presence of various OMPs in the influents, including pharmaceuticals such as acetaminophen (pain relief), caffeine (stimulants), cimetidine (H2-blockers), ibuprofen (non-steroidal anti-inflammatory drugs- NSAIDs), metformin (antidiabetics), and naproxen (NSAIDs) with median concentrations of >1 μg/L. Some pharmaceuticals (carbamazepine-anticonvulsants, diclofenac-NSAIDs, propranolol-β-blockers), corrosion inhibitors (1H-benzotriazole-BTR, 4-methyl-1H-benzotriazole-4-TTR), and perfluorinated compounds (PFCs) were negligibly removed during WWTP treatment. The OMP concentrations in the influents and effluents were mostly lower in August than those of other months (p-value <0.05) possibly due to wastewater dilution by high precipitation or enhanced biodegradation under high-temperature conditions. The anaerobic-anoxic-oxic process (A2O) with a membrane bioreactor exhibited higher OMP removal than other processes, such as A2O with sedimentation or the conventional activated sludge process (p-value <0.05). Pesticides (DEET and atrazine), corrosion inhibitors (4-TTR and BTR), and metformin were selected as priority OMPs in toxicity-driven prioritization, whereas PFCs were determined as priority OMPs given their persistence and bioaccumulation properties. Overall, our results contribute to an important database on the occurrence, removal, and potential risks of OMPs in Korean WWTPs.

Pharmaceuticals and Personal Care Products in the Aquatic Environment: How Can Regions at Risk be Identified in the Future?

Pharmaceuticals and personal care products (PPCPs) are an indispensable component of a healthy society. However, they are well-established environmental contaminants, and many can elicit biological disruption in exposed organisms. It is now a decade since the landmark review covering the top 20 questions on PPCPs in the environment (Boxall et al., 2012). In the present study we discuss key research priorities for the next 10 years with a focus on how regions where PPCPs pose the greatest risk to environmental and human health, either now or in the future, can be identified. Specifically, we discuss why this problem is of importance and review our current understanding of PPCPs in the aquatic environment. Foci include PPCP occurrence and what drives their environmental emission as well as our ability to both quantify and model their distribution. We highlight critical areas for future research including the involvement of citizen science for environmental monitoring and using modeling techniques to bridge the gap between research capacity and needs. Because prioritization of regions in need of environmental monitoring is needed to assess future/current risks, we also propose four criteria with which this may be achieved. By applying these criteria to available monitoring data, we narrow the focus on where monitoring efforts for PPCPs are most urgent. Specifically, we highlight 19 cities across Africa, Central America, the Caribbean, and Asia as priorities for future environmental monitoring and risk characterization and define four priority research questions for the next 10 years. Environ Toxicol Chem 2024;43:575-588. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Ecotoxicity and photodegradation of Montelukast (a drug to treat asthma) in water

The present work focuses on the ecotoxicological effects of montelukast sodium (MTL) and its photoproducts, obtained under environmentally-like conditions. Despite of the potential presence in surface waters and the common use of MTL as asthma drug, limited data has been published for its photodegradation, while no information is available for its ecotoxicity. Light-induced degradation is an effective way for drugs to degrade in aquatic environments, and MTL is highly photosensitive, even by exposure to sunlight. In this study, solar-simulated irradiation of the drug in water was investigated. The drug was quickly converted into a series of photoproducts that were spectroscopically characterized. The possible photoreaction pathways were proposed. Ecotoxicity tests were performed on parent compound and mixture of photoproducts towards two bioindicators (Raphidocelis subcapitata and Daphnia magna). Results evidenced that effects of MTL on D. magna (EC50 = 16.4 mg/L) were greater than effects on R. subcapitata (EC50 = 195.7 mg/L). Microscopy observations revealed that MTL had mainly accumulated in the gut of daphnia. Toxicity data on photolysed solutions highlighted the presence of residual toxicity in all samples, evidencing that no complete mineralization occurred. Future research should focus on monitoring of MTL concentrations in the environment and study its effects in bioaccumulation tests.

Performance Comparison between the Specific and Baseline Prediction Models of Ecotoxicity for Pharmaceuticals: Is a Specific QSAR Model Inevitable?

Assessing the ecotoxicity of pharmaceuticals is of urgent need due to the recognition of their possible adverse effects on nontarget organisms in the aquatic environment. The reality of ecotoxicity data scarcity promotes the development and application of quantitative structure activity relationship (QSAR) models. In the present study, we aimed to clarify whether a QSAR model of ecotoxicity specifically for pharmaceuticals is needed considering that pharmaceuticals are a class of chemicals with complex structures, multiple functional groups, and reactive properties. To this end, we conducted a performance comparison of two previously developed and validated QSAR models specifically for pharmaceuticals with the commonly used narcosis toxicity prediction model, i.e., Ecological Structure Activity Relationship (ECOSAR), using a subset of pharmaceuticals produced in China that had not been included in the training datasets of QSAR models under consideration. A variety of statistical measures demonstrated that the pharmaceutical specific model outperformed ECOSAR, indicating the necessity of developing a specific QSAR model of ecotoxicity for the active pharmaceutical contaminants. ECOSAR, which was generally used to predict the baseline or the minimum toxicity of a compound, generally underestimated the ecotoxicity of the analyzed pharmaceuticals. This could possibly be because some pharmaceuticals can react through specific modes of action. Nonetheless, it should be noted that 95% prediction intervals spread over approximately four orders of magnitude for both tested QSAR models specifically for pharmaceuticals.

Identifying unknown antibiotics with persistent and bioaccumulative properties and ecological risk in river water in Beijing, China

The goal of this study was to identify antibiotics with potential risk in river water of the megacity Beijing, China. This was accomplished by using a tiered approach that combined hazard (phase I) and monitoring-based risk (phase II) assessment. Ninety-five candidate antibiotics were screened and 31 was identified as hazardous during phase I assessment. Of these hazardous antibiotics, 29 were identified as persistent and 7 were identified as bioaccumulative antibiotics. Fluoroquinolones, macrolides, sulfonamides, and aminoglycosides account for over 80% of these hazardous antibiotics. During phase II, four antibiotics (erythromycylamine, cefotaxime, ampicillin, and fusidic acid) that were not previously reported were detected in the surface water sampled from four major rivers in Beijing, with concentrations ranging from not detected to approximately 300 ng/L. The ecological risk assessment showed that erythromycylamine, cefotaxime, and ampicillin posed low to high levels of risk to the aquatic organisms. To summarize, erythromycylamine, cefotaxime, and ampicillin were identified as priority antibiotics in rivers in Beijing, China. Our results demonstrated the necessity of conducting monitoring-based verification process in identification of priority antibiotics in a specific region.

Replacing the internal standard to estimate micropollutants using deep and machine learning

Similar to the worldwide proliferation of urbanization, micropollutants have been involved in aquatic and ecological environmental systems. These pollutants have the propensity to wreak havoc on human health and the ecological system; hence, it is important to persistently monitor micropollutants in the environment. Micropollutants are commonly quantified via target analysis using high resolution mass spectrometry and the stable isotope labeled (SIL) standard. However, the cost-intensiveness of this standard presents a major obstacle in measuring micropollutants. This study resolved this problem by developing data-driven models, including deep learning (DL) and machine learning (ML), to estimate the concentration of micropollutants without resorting to the SIL standard. Our study hypothesized that natural organic matter (NOM) could replace internal standards if there was a specific mass spectrum (MS) subset, including NOM information, which correlated with an SIL standard peak. Therefore, we analyzed the MS to find the specific MS subsets for replacing the SIL standard peak. Thirty-five alternative MS subsets were determined for applying DL and ML as input data. Thereafter, we trained four different DL models, namely, ResNet101, GoogLeNet, VGG16, and Inception v3, as well as three different ML models, i.e., random forest (RF), support vector machine (SVM), and artificial neural network (ANN). A total of 680 MS data were used for the model training to estimate five different micropollutants, namely Sulpiride, Metformin, and Benzotriazole. Among the DL models, ResNet 101 exhibited the highest model performance, showing that the average validation R² and MSE were 0.84 and 0.26 ng/L, respectively, while RF was the best in the ML models, manifesting R² and MSE values of 0.69 and 0.58 ng/L. The trained models showed accurate training and validation results for the estimation of the five micropollutant concentrations. Therefore, this study demonstrates that the suggested analysis has a potential for alternative micropollutant measurement that has rapid and economic vantages.

Identifying targets of potential concern by a screening level ecological risk assessment of human use pharmaceuticals in China

The pollution of pharmaceuticals has attracted a lot of concerns during recent years. The goal of this study was to identify targets of ecological concern considering human use pharmaceuticals marketed in China. We constructed a database for 593 active pharmaceutical ingredients (APIs) by collecting their information on use and emission (e.g. production, human excretion, and removal by wastewater treatment) to calculated predicted environmental concentrations (PECs) by using an adapted European Medicines Agency method. PECs were comparable to the reported measurements for most APIs, demonstrating that the adapted method is reliable for the prioritization practice. Then PECs were compared to toxicity thresholds of three aquatic taxa (algae, daphnia, and fish). As a result, a total of 31 APIs, which were potentially risky and should be taken into consideration in future studies, were identified. Three APIs would pose a high risk with risk quotient (RQ) greater than 10. Six APIs were identified with moderate risks (1 < RQ < 10), and four of them were not reported before: rifaximin, griseofulvin, amikacin, and niclosamide. Of the 22 APIs with low risks (0.1 < RQ < 1), 17 have never been monitored previously in China and even worldwide. This study has yielded some probable antibiotics that should be considered as monitoring targets in China in the future.

Occurrence and removal of progestagens in municipal wastewater treatment plants from different regions in China

Progestagens discharged from municipal wastewater treatment plants (WWTPs) have increasingly gained attention due to their potential risks to the aquatic organisms. However, limited information is available on the occurrence and removal of various progestagens in WWTPs in different cities of China. This work investigated the occurrence and removal of 11 progestagens in 21 WWTPs from 19 Chinese cities. Results showed that progestagens are widely distributed in the investigated WWTPs, with higher influent concentrations of total progestagens in northern WWTPs. The concentration of progestagens in WWTP influent were closely correlated with influent quality, service population and daily service volume of the WWTPs. Additionally, progesterone (PGT) and dydrogesterone (DDT) were two predominant progestagens in influent, effluent and excess sludge. Up to 5 of 11 progestagens showed high aqueous removal efficiencies (median removal efficiency >90%), whereas megestrol acetate (MTA), chlormadinone acetate (CMA), drospirenone (DSP) and levonorgestrel (LNG) had a removal efficiency of below 50%. Specially, the behaviors of progestagens along the anaerobic-anoxic-oxic of a WWTP were further explored and the aerobic tank is the main contributor to the removal of progestagens. Finally, in the effluent of these 21 WWTPs, daily mass loadings of the total progestagens ranged from 0.51 to 10.4 g d^-1. Notably, LNG exhibited high potential risk to the fish base on risk quotient.

Ranking and prioritizing pharmaceuticals in the aquatic environment of China

Pharmaceuticals have become "persistent" pollutants in the aquatic environment, due to their wide usage in daily life and their continuous release into the aquatic environment. Hence, prioritization and ranking lists are required to screen for target compounds as part of risk assessments. A ranking system based on three criteria, such as occurrence, exposure potential and ecological effects, was developed in this study for specific application to China. A total of 100 pharmaceuticals were selected as candidates based on the ranking system and available consumption data. These pharmaceuticals have been previously reported by wastewater treatment plants (WWTPs) in China. 13 pharmaceuticals were classified as priority pharmaceuticals, among which diclofenac, erythromycin, and penicillin G were highly prioritized. Due to their abuse, antibiotics contributed a majority to the priority pharmaceuticals among all therapeutic classes, indicating that antibiotics should be considered based on their behaviors in WWTPs. The pharmaceuticals ranking list achieved good applicability and will help to establish a focus for future monitoring and management of pharmaceuticals. It will also provide an important basis for both ecological risk assessment and pollution control of pharmaceuticals in the aquatic environment.

Understanding Electrochemically Activated Persulfate and Its Application to Ciprofloxacin Abatement

This study offers insight into the roles anodic and cathodic processes play in electrochemically activated persulfate (EAP) and screens EAP as a viable technique for ciprofloxacin degradation in wastewater. Sulfate radical formation at a boron-doped diamond (BDD) anode and persulfate activation at a graphite cathode were experimentally elucidated using different electrolytes and electrochemical setups. Rapid ciprofloxacin transformation occurred via pseudo-first-order mechanisms with respect to ciprofloxacin in persulfate electrolyte, reaching 84% removal in 120 min using EAP. Transformation pathways were compared to those in nitrate and sulfate electrolytes. Ciprofloxacin removal rates in the electrochemical system were 88% and 33% faster in persulfate than nitrate and sulfate electrolytes, respectively. Total organic carbon removal rates were 93% and 48% faster in persulfate than nitrate and sulfate, respectively. Use of sulfate electrolyte resulted in removal rates 6-7 times faster than those in nitrate solution. Accelerated removal in sulfate was attributed to anodic sulfate radical formation, while enhanced removal in persulfate was associated with cathodic persulfate activation and nonradical persulfate activation at the BDD anode. Quenching experiments indicated both sulfate radicals and hydroxyl radicals contributed to degradation. Comparisons between platinum and graphite cathodes showed similar cathodic persulfate activation and ciprofloxacin degradation.

Determination of progestogens in surface and waste water using SPE extraction and LC-APCI/APPI-HRPS

The aim of this study was to develop a reliable analytical method for the measurement of 17 selected progestogens in waste water and surface water. Automated whole water solid phase extraction (SPE) was used for sample concentration. Liquid chromatography tandem atmospheric pressure chemical ionization/atmospheric pressure photoionization with hybrid quadrupole/orbital trap mass spectrometry operated in high resolution product scan mode (LC-APCI/APPI-HRPS) was applied for the analyses. The whole-method recoveries ranged from 60% to 140% for all analytes at two different spike levels (5 and 50ng/L) in the studied matrices. The method is very sensitive with LOQs ranging from 0.02 to 0.87ng/L. The developed method was used for the determination of progestogens in real samples of waste water from three waste water treatment plants (WWTPs) and in surface water from the corresponding recipients. Progesterone was detected in all samples with concentrations in the range of 0.82 to 1.1ng/L in surface water and 0.11 to 110ng/L in waste water samples. Three synthetic progestogens, namely, megestrol acetate, medroxyprogesterone acetate, and dienogest, were detected most frequently in effluents; therefore, further attention should be paid to the monitoring of these compounds. To the best of our knowledge, this study is the first to present analysis of altrenogest, etonogestrel, dienogest, nomegestrol acetate and ulipristal acetate in waste water and surface water using a solid-phase extraction method.

Occurrence and environmental impact of pharmaceutical residues from conventional and natural wastewater treatment plants in Gran Canaria (Spain)

The presence and fate of pharmaceutical residues in environmental samples are of great interest. There is a vast number of studies published regarding their input, presence, effects and risks in ecosystems. Moreover, it has been demonstrated that the primary source of input of these contaminants in the environment is from Wastewater Treatment Plants (WWTPs). It is therefore essential to evaluate the efficiency of commonly used treatments and the necessity of applying novel purification processes in order to eliminate or reduce the concentration of pharmaceuticals from wastewater or from the effluent of WWTPs. The aim of this work was to quantify twenty-three pharmaceutical compounds in the aqueous phase at different stages of a conventional and a natural WWTP situated in Gran Canaria (Spain). The results indicate concentration levels in the range of 0.004±0.001 to 59.2±11.7μgL^-1 and 0.018±0.001 to 148±14.7μgL^-1 from conventional and natural WWTPs, respectively. Better efficiency was, however, offered by the conventional WWTP with a removal median of 99.7%. In addition, the impact on different aquatic organisms (algae, daphnids and fish) was assessed in terms of risk quotients. The results reveal a possible highly harmful effect towards organisms by gemfibrozil, ibuprofen and ofloxacin.

Are exposure predictions, used for the prioritization of pharmaceuticals in the environment, fit for purpose?

Prioritization methodologies are often used for identifying those pharmaceuticals that pose the greatest risk to the natural environment and to focus laboratory testing or environmental monitoring toward pharmaceuticals of greatest concern. Risk-based prioritization approaches, employing models to derive exposure concentrations, are commonly used, but the reliability of these models is unclear. The present study evaluated the accuracy of exposure models commonly used for pharmaceutical prioritization. Targeted monitoring was conducted for 95 pharmaceuticals in the Rivers Foss and Ouse in the City of York (UK). Predicted environmental concentration (PEC) ranges were estimated based on localized prescription, hydrological data, reported metabolism, and wastewater treatment plant (WWTP) removal rates, and were compared with measured environmental concentrations (MECs). For the River Foss, PECs, obtained using highest metabolism and lowest WWTP removal, were similar to MECs. In contrast, this trend was not observed for the River Ouse, possibly because of pharmaceutical inputs unaccounted for by our modeling. Pharmaceuticals were ranked by risk based on either MECs or PECs. With 2 exceptions (dextromethorphan and diphenhydramine), risk ranking based on both MECs and PECs produced similar results in the River Foss. Overall, these findings indicate that PECs may well be appropriate for prioritization of pharmaceuticals in the environment when robust and local data on the system of interest are available and reflective of most source inputs. Environ Toxicol Chem 2017;36:2823-2832. © 2017 SETAC.

Significance of metabolites in the environmental risk assessment of pharmaceuticals consumed by human

The purpose of this study is to demonstrate the significance of metabolites to the ERA of human pharmaceuticals. The predicted exposure concentrations (PECs) in surface water were estimated for a total of 24 selected active pharmaceutical ingredients (APIs) and their metabolites using a life cycle based emission estimation model combined with a multimedia fate model with Monte-Carlo calculations. With the eco-toxicity data, the hazard quotients (HQs) of the metabolites were compared with those of individual parents alone. The results showed that PEC or toxicity or both of the metabolites was predicted to be higher than that of their parent APIs, which resulted in a total of 18 metabolites (from 12 parents) that have greater HQs than their parents. This result clearly demonstrated that some metabolites may potentially pose greater risk than their parent APIs in the water environment. Therefore, significance of metabolites should be carefully evaluated for monitoring strategy, priority setting, and scoping of the environmental risk assessment of APIs. The method used in the present work may serve as a pragmatic approach for the purpose of preliminary screening or priority setting of environmental risk posed by both APIs and their metabolites.