Use of acute and chronic ecotoxicity data in environmental risk assessment of pharmaceuticals

Vestel, Jessica; Caldwell, Daniel J.; Constantine, Lisa A.; D’Aco, Vincent J.; Davidson, Thomas; Dolan, David G.; Millard, Steven P.; Murray‐Smith, Richard; Parke, Neil J.; Ryan, Jim J.; Straub, Jürg Oliver; Wilson, Peter

doi:10.1002/etc.3260

Cited by 84 publications

(45 citation statements)

References 48 publications

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“…6,29 Existing PNEC values of the selected APIs have been compiled in SI Table S1. To maintain consistency, the values for most APIs were chosen from the Vestel et al study, 31 as many are derived from OECD studies used as part of a regulatory marketing application and are lower than those reported in other studies. For the APIs not included in the Vestel et al study, the lowest value from other literature sources or databases were used in this study ( Table 1).…”

Section: Methodsmentioning

confidence: 99%

Spatially Explicit Large-Scale Environmental Risk Assessment of Pharmaceuticals in Surface Water in China

Zhu

Snape

Jones

et al. 2019

Environ. Sci. Technol.

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With improving health care and an aging population, the consumption of human pharmaceuticals in China has been increasing dramatically. Environmental risks posed by many active pharmaceutical ingredients (APIs) are still unknown. This study used a spatially-explicit dilution-factor methodology to model predicted environmental concentrations (PECs) of 11 human-use APIs in surface water for a preliminary environmental risk assessment (ERA). Median PECs in surface water across China range between 0.01-8.0×10 3 ng/L for the different APIs, under a moderate patient use scenario. Higher environmental risks of APIs in surface water are in regions with high water stress, e.g. northern China. Levonorgestrel, estradiol, ethinyl estradiol and abiraterone acetate were predicted to potentially pose a high or moderate environmental risk in China if consumption levels reach those in Europe. Relative risks of these four APIs have the potential to be amongst those chemicals with the highest impact on surface water in China when compared to the risks associated with other regulated chemicals, including triclosan and some standard water quality parameters including BOD5 (5-day biological oxygen demand), COD (chemical oxygen demand), Cu, Zn and Hg and linear alkylbenzene sulphonate. This method could support the regulation of this category of chemicals and risk mitigation strategies in China.

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Section: Methodsmentioning

confidence: 99%

Spatially Explicit Large-Scale Environmental Risk Assessment of Pharmaceuticals in Surface Water in China

Zhu

Snape

Jones

et al. 2019

Environ. Sci. Technol.

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“…This is due in part to their potential toxicological effects on organisms (Brausch et al, 2012, Corcoran et al, 2010, Vestel et al, 2016). These substances enter the environment through a number of routes, with domestic and hospital waste effluents considered the most important sources (Nikolaou et al, 2007, Monteiro and Boxall, 2010).…”

Section: Introductionmentioning

confidence: 99%

Quantitative structure-property relationships for predicting sorption of pharmaceuticals to sewage sludge during waste water treatment processes

Berthod

Whitley

Roberts

et al. 2017

Science of The Total Environment

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Understanding the sorption of pharmaceuticals to sewage sludge during waste water treatment processes is important for understanding their environmental fate and in risk assessments. The degree of sorption is defined by the sludge/water partition coefficient (Kd). Experimental Kd values (n = 297) for active pharmaceutical ingredients (n = 148) in primary and activated sludge were collected from literature. The compounds were classified by their charge at pH 7.4 (44 uncharged, 60 positively and 28 negatively charged, and 16 zwitterions). Univariate models relating log Kd to log Kow for each charge class showed weak correlations (maximum R2 = 0.51 for positively charged) with no overall correlation for the combined dataset (R2 = 0.04). Weaker correlations were found when relating log Kd to log Dow. Three sets of molecular descriptors (Molecular Operating Environment, VolSurf and ParaSurf) encoding a range of physico-chemical properties were used to derive multivariate models using stepwise regression, partial least squares and Bayesian artificial neural networks (ANN). The best predictive performance was obtained with ANN, with R2 = 0.62–0.69 for these descriptors using the complete dataset. Use of more complex Vsurf and ParaSurf descriptors showed little improvement over Molecular Operating Environment descriptors. The most influential descriptors in the ANN models, identified by automatic relevance determination, highlighted the importance of hydrophobicity, charge and molecular shape effects in these sorbate-sorbent interactions. The heterogeneous nature of the different sewage sludges used to measure Kd limited the predictability of sorption from physico-chemical properties of the pharmaceuticals alone. Standardization of test materials for the measurement of Kd would improve comparability of data from different studies, in the long-term leading to better quality environmental risk assessments.

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“…The lowest PNEC for each species group was used to derive risk characterization ratios (RCRs) for each chemical (see Calculation of prospective risk section below). We acknowledge that for some chemicals it is not known whether the European Union assessment factors adequately incorporate potential endocrine disruption effects (Vestel et al ). Differentiating between species groups provides enhanced diagnostic resolution and may help identify the species group most at risk.…”

Section: Methodsmentioning

confidence: 99%

Use of prospective and retrospective risk assessment methods that simplify chemical mixtures associated with treated domestic wastewater discharges

Diamond

Altenburger

Coors

et al. 2018

Enviro Toxic and Chemistry

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A framework is presented that is intended to facilitate the evaluation of potential aquatic ecological risks resulting from discharges of down-the-drain chemicals. A scenario is presented using representatives of many of the types of chemicals that are treated domestically. Predicted environmental chemical concentrations are based on reported loading rates and routine removal rates for 3 types of treatment: trickling filter, activated sludge secondary treatment, and activated sludge plus advanced oxidation process as well as instream effluent dilution. In tier I, predicted effluent concentrations were compared with the lowest predicted-no-effect concentration (PNEC) obtained from the literature using safety factors as needed. A cumulative risk characterization ratio (cumRCR) < 1.0 indicates that risk is unlikely and no further action is needed. Otherwise, a tier 2 assessment is used, in which PNECs are based on trophic level. If tier 2 indicates a possible risk, then a retrospective assessment is recommended. In tier 1, the cumRCR was > 1.0 for all 3 treatment types in our scenario, even though no chemical exceeded a hazard quotient of 1.0 in activated sludge or advanced oxidation process. In tier 2, activated sludge yielded a lower cumRCR than trickling filter because of higher removal rates, and the cumRCR in the advanced oxidation process was << 1.0. Based on the maximum cumulative risk ratio (MCR), more than one-third of the predicted risk was accounted for by one chemical, and at least 90% was accounted for by 3 chemicals, indicating that few chemicals influenced the mixture risk in our scenario. We show how a retrospective assessment can test whether certain chemicals hypothesized as potential drivers in the prospective assessment could have, or are having, deleterious effects on aquatic life. Environ Toxicol Chem 2018;37:690-702. C

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Use of acute and chronic ecotoxicity data in environmental risk assessment of pharmaceuticals

Cited by 84 publications

References 48 publications

Spatially Explicit Large-Scale Environmental Risk Assessment of Pharmaceuticals in Surface Water in China

Spatially Explicit Large-Scale Environmental Risk Assessment of Pharmaceuticals in Surface Water in China

Quantitative structure-property relationships for predicting sorption of pharmaceuticals to sewage sludge during waste water treatment processes

Use of prospective and retrospective risk assessment methods that simplify chemical mixtures associated with treated domestic wastewater discharges

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