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Giunchi, V.

Publications and source records attributed to Giunchi, V..

2 recordsLinked to original sources

The environmental impact of pharmaceuticals: an evidence-mapping review of recent data on aquatic concentrations and predictable effects

Pharmaceuticals are recognised among emerging contaminants, particularly in water. They have the potential to alter ecosystem dynamics, with notable examples including hormone-induced feminization of male fish and disruptions to oogenesis in invertebrates. To assess the risk posed by pharmaceuticals, it is essential to understand their amount (via Measured Environmental Concentrations - MEC) and their actual effects on target species (via Predicted No Effect Concentrations - PNEC). Recently, many studies have aimed to collect MEC data from around the world, but a comprehensive overview is still lacking. Thus, the objective of this study is to provide a comprehensive overview by examining recently published literature on MEC data for a wide range of pharmaceuticals. Additionally, to enable risk assessment, this study also reviewed the published literature on PNEC data and integrated it with existing databases. A total of 315 substances were selected for MEC data extraction, with the inclusion of 56 articles. The most frequently monitored locations were Cadiz Bay in Spain (90 samples), the River Thames in the UK (51), and Hrd[e]jovice in the Czech Republic (49). Most MEC samples were collected from surface water (N=325), influent wastewater treatment plants (WWTP) (205), and effluent WWTP (118). Based on PNEC values, risk analysis identified 81 pharmaceuticals as high-risk, with the highest risk values for propranolol (risk quotient [RQ]: 29,450,000), diclofenac (395,920), and 17alpha-ethinylestradiol (95,946). Additionally, the ATC classes with the most high-risk substances were anti-infectives (J), nervous system agents (N), cardiovascular agents (C), antineoplastic agents (L), analgesics (M), and sex hormones (G). The findings of this study highlight the widespread impact of pharmaceuticals across the globe and the involvement of multiple therapeutic classes. To move beyond the current point-in-time overview, which is limited to specific locations and sampling periods, systems for continuous monitoring of pharmaceuticals should be developed. This could involve the creation of resource-efficient methods and the integration of sampling data with estimation models. Furthermore, these results could serve as a starting point for developing and implementing actions to prevent and mitigate the environmental impact of pharmaceuticals.

ecology↗

A collection of Predicted No-Effect Concentrations of human pharmaceuticals and their metabolites

The environmental impact of pharmaceuticals is a growing concern, necessitating methodologies for risk assessment. Current evaluation methods rely on comparing pharmaceutical concentrations in exposed environments with relevant animal or plant tolerance thresholds, often represented by Predicted No-Effect Concentration (PNEC) values. However, challenges arise from the limited accessibility and standardization of PNEC data. This study addresses these challenges by consolidating PNEC values from diverse sources into a unified and accessible tool. Investigated data sources were the NORMAN Ecotoxicology Database, the Swedish National Formulary of Drugs (FASS) website, the EU Watch List working documents, the European Public Assessment Reports (EPAR), the US EPA ECOTOX database, the UBA ETOX database, the WikiPharma database, the AstraZeneca documents, the European Chemical Agency registration dossiers, and the AMR Industry Alliance database. We retrieved 93,287 PNEC values associated with 92,850 substances, primarily medicines or their metabolites. Notably, 352 substances had more than one PNEC value, with the highest discrepancies often attributed to in-silico predicted values. The resulting database, available in the related OSF repository as a spreadsheet file, includes source information and processing scripts and is freely available for risk assessment analyses. While acknowledging limitations, future efforts should prioritize integrating additional data sources, addressing misspellings, and enhancing information on PNEC derivation. Collaboration in PNEC data collection is crucial for advancing collective knowledge in pharmaceutical risk assessment.

pharmacology and toxicology↗