Development of a probabilistic risk model for pharmaceuticals in the environment under population and wastewater treatment scenarios.

Preparing for future environmental pressures requires projections of how relevant risks will change over time. Current regulatory models of environmental risk assessment (ERA) of pollutants such as pharmaceuticals could be improved by considering the influence of global change factors (e.g., population growth) and by presenting uncertainty more transparently. In this article, we present the development of a prototype object-oriented Bayesian network (BN) for the prediction of environmental risk for six high-priority pharmaceuticals across 36 scenarios: current and three future population scenarios, combined with infrastructure scenarios, in three Norwegian counties. We compare the risk, characterized by probability distributions of risk quotients (RQs), across scenarios and pharmaceuticals. Our results suggest that RQs would be greatest in rural counties, due to the lower development of current wastewater treatment facilities, but that these areas consequently have the most potential for risk mitigation. This pattern intensifies under higher population growth scenarios. With this prototype, we developed a hierarchical probabilistic model and demonstrated its potential in forecasting the environmental risk of chemical stressors under plausible demographic and management scenarios, contributing to the further development of BNs for ERA. Integr Environ Assess Manag 2024;00:1-21. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Predicting Environmental Risks of Pharmaceuticals from Wholesale Data: An Example from Norway.

Environmental risk assessment (ERA) of pharmaceuticals relies on available measured environmental concentrations, but often such data are sparse. Predicted environmental concentrations (PECs), calculated from sales weights, are an attractive alternative but often cover only prescription sales. We aimed to rank, by environmental risk in Norway, approximately 200 active pharmaceutical ingredients (APIs) over 2016-2019, based on sales PECs. To assess the added value of wholesale and veterinary data, we compared exposure and risk predictions with and without these additional sources. Finally, we aimed to characterize the persistence, mobility, and bioaccumulation of these APIs. We compared our PECs to available Norwegian measurements, then, using public predicted-no-effect concentrations, we calculated risk quotients (RQs) and appended experimental and predicted persistence and bioaccumulation. Our approach overestimated environmental concentrations compared with measurements for 18 of 20 APIs with comparable predictions and measurements. Seventeen APIs had mean RQs >1, indicating potential risk, while the mean RQ was 2.05 and the median 0.001, driven by sex hormones, antibiotics, the antineoplastic abiraterone, and common painkillers. Some high-risk APIs were also potentially persistent or bioaccumulative (e.g., levonorgestrel [RQ = 220] and ciprofloxacin [RQ = 56]), raising the possibility of impacts beyond their RQs. Exposure and risk were also calculated with and without over-the-counter sales, showing that prescriptions explained 70% of PEC magnitude. Likewise, human sales, compared with veterinary, explained 85%. Sales PECs provide an efficient option for ERA, designed to overestimate compared with analytical techniques and potentially held back by limited data availability and an inability to quantify uncertainty but, nevertheless, an ideal initial approach for identification and ranking of risks. Environ Toxicol Chem 2023;42:2253-2270. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Pharmaceutical pollution: Prediction of environmental concentrations from national wholesales data.

The regulation and monitoring of pharmaceutical pollution in Europe lag behind that of more prominent groups. However, the repurposing of sales data to predict surface water environmental concentrations is a promising supplement to more commonly used market-based risk assessment and measurement approaches. The Norwegian Institute of Public Health (NIPH) has since the 1980s compiled the Drug Wholesale Statistics database - covering all sales of both human and veterinary pharmaceuticals to retailers, pharmacies, and healthcare providers. To date, most similar works have focused either on a small subset of Active Pharmaceutical Ingredients (APIs) or used only prescription data, often more readily available than wholesale data, but necessarily more limited. By using the NIPH's product wholesale records, with additional information on API concentrations per product from, we have been able to calculate sales weights per year for almost 900 human and veterinary APIs for the period 2016-2019. In this paper, we present our methodology for converting the provided NIPH data from a public health to an ecotoxicological resource. From our derived dataset, we have used an equation to calculate Predicted Environmental Concentration per API for inland surface waters, a key component of environmental risk assessment. We further describe our filtering to remove ecotoxicological-exempt and data deficient APIs. Lastly, we provide a limited comparison between our dataset and similar publicly available datasets for a subset of APIs, as a validation of our approach and a demonstration of the added value of wholesale data. This dataset will provide the best coverage yet of pharmaceutical sales weights for an entire nation. Moreover, our developed routines for processing 2016-2019 data can be expanded to older Norwegian wholesales data (1974-present). Consequently, our work with this dataset can contribute to narrowing the gap between desk-based predictions of exposure from consumption, and empirical but expensive environmental measurement.

ECORISK2050: An Innovative Training Network for predicting the effects of global change on the emission, fate, effects, and risks of chemicals in aquatic ecosystems.

By 2050, the global population is predicted to reach nine billion, with almost three quarters living in cities. The road to 2050 will be marked by changes in land use, climate, and the management of water and food across the world. These global changes (GCs) will likely affect the emissions, transport, and fate of chemicals, and thus the exposure of the natural environment to chemicals. ECORISK2050 is a Marie Sklodowska-Curie Innovative Training Network that brings together an interdisciplinary consortium of academic, industry and governmental partners to deliver a new generation of scientists, with the skills required to study and manage the effects of GCs on chemical risks to the aquatic environment. The research and training goals are to: (1) assess how inputs and behaviour of chemicals from agriculture and urban environments are affected by different environmental conditions, and how different GC scenarios will drive changes in chemical risks to human and ecosystem health; (2) identify short-to-medium term adaptation and mitigation strategies, to abate unacceptable increases to risks, and (3) develop tools for use by industry and policymakers for the assessment and management of the impacts of GC-related drivers on chemical risks. This project will deliver the next generation of scientists, consultants, and industry and governmental decision-makers who have the knowledge and skillsets required to address the changing pressures associated with chemicals emitted by agricultural and urban activities, on aquatic systems on the path to 2050 and beyond.