Defining the data gap: What do we know about environmental exposure, hazards and risks of pharmaceuticals in the European aquatic environment?

Active pharmaceutical ingredients (APIs) and their transformation products inevitably enter waterways where they might cause adverse effects to aquatic organisms. Identifying the potential risks of APIs in the environment is therefore a goal and current strategic direction of environmental management described in the EU Strategic Approach to Pharmaceuticals in the Environment and the Green Deal. This is challenged by a paucity of monitoring and ecotoxicity data to adequately describe risks. In this study we analyze measured environmental concentrations (MECs) of APIs from 5933 sites in 25 European countries as documented in the EMPODAT database or collected by the German Environment Agency for the time period between 1997 and 2020. These data were compared with empirical data on the ecotoxicity of APIs from the U.S. EPA ECOTOX database. Although 1763 uniquely identifiable APIs are registered with the European Medicines Agency (EMA) for sale in the European Economic Area (EEA), only 312 (17.7%) of these are included in publicly available monitoring data, 36 (1.8%) compounds have sufficient ecotoxicological data to derive a PNEC, and only 27 (1.5%) compounds meet both the hazard and exposure data requirements required to to perform an environmental risk assessment according to EMA guidelines. Four of these compounds (14.8%) had a median risk quotient (RQ) > 1. Endocrine disruptors had the highest median RQ, with 7.0 and 5.6 for 17α-ethinyl-estradiol and 17β-estradiol respectively. A comparison of in-silico and empirical exposure data for 72 APIs demonstrated the high protectiveness of the current EMA guidelines, with predicted environmental concentrations (PECs) exceeding median MECs in 98.6% of cases, with a 100-fold median increase. This study describes the data shortfalls hindering an accurate assessment of the risk posed to European waterways by APIs, and identifies 68 APIs for prioritized inclusion in monitoring programs, and 66 APIs requiring ecotoxicity testing to fill current data gaps.

Risk assessment of chemicals and their mixtures are hindered by scarcity and inconsistencies between different environmental exposure limits

In chemical risk assessment, measured or modelled environmental concentrations are compared to environmental exposure limits (EELs), such as Predicted No Effect Concentrations (PNECs) or hazardous concentrations for 5% of species (HC05s) derived from species sensitivity distributions (SSDs). However, for many chemicals the EELs include large uncertainties or, in the worst case, the necessary data for their estimation are completely missing. This makes the assessment of chemical risks and any subsequent implementation of management strategies challenging. In this study we analyzed the uncertainty of EELs and its impact on chemical risk assessment. First, we compared three individual EEL datasets, two primarily based on experimental data and one based on computational predictions. The comparison demonstrates large disagreements between EEL data sources, with experimentally derived EELs differing by more than seven orders of magnitude. In a case-study, based on the predicted emissions of 2005 chemicals, we showed that these uncertainties lead to significantly different risk assessment outcomes, including large differences in the magnitude of the total risk, risk driver identification, and the ranking of use categories as risk contributors. We also show that the large data-gaps in EEL datasets cannot be covered by commonly used computational approaches (QSARs). We conclude that an expanded framework for interpreting risk characterization outcomes is needed. We also argue that the large data-gaps present in ecotoxicological data need to be addressed in order to achieve the European zero pollution vision as the growing emphasis on ambient exposures will further increase the demand for accurate and well-established EELs.

Estimating the release of chemical substances from consumer products, textiles and pharmaceuticals to wastewater

Chemical emissions from households originate from a wide range of sources and results in highly diverse mixtures. This makes traditional monitoring based on analytical chemistry challenging, especially for compounds that appear in low concentrations. We therefore developed a method for predicting emissions of chemicals from households into wastewater, relying on consumption patterns from multiple data sources. The method was then used to predict the emissions of chemical preparations, chemicals leaching from textiles and prescription pharmaceuticals in Sweden. In total we predicted emissions of 2007 chemicals with a combined emission of 62,659 tonnes per year - or 18 g/person and day. Of the emitted chemicals, 2.0% (w/w) were either classified as hazardous to the environment or were both persistent and mobile. We also show that chemical emissions come from a wide range of uses and that the total emission of any individual chemical is determined primarily by its use pattern, not by the total amount used. This emphasizes the need for continuous updates and additional knowledge generation both on emission factors and excretion rates as well as a need for improved reporting on the intended use of individual chemicals. Finally, we scrutinize the model and its uncertainty and suggest areas that need improvement to increase the accuracy of future emission modelling. We conclude that emission modelling can help guide environmental monitoring and provide input into management strategies aimed at reducing the environmental effect caused by hazardous chemicals.

Risks of floating microplastic in the global ocean

Despite the ubiquitous and persistent presence of microplastic (MP) in marine ecosystems, knowledge of its potential harmful ecological effects is low. In this work, we assessed the risk of floating MP (1 μm-5 mm) to marine ecosystems by comparing ambient concentrations in the global ocean with available ecotoxicity data. The integration of twenty-three species-specific effect threshold concentration data in a species sensitivity distribution yielded a median unacceptable level of 1.21 ∗ 10⁵ MP m^-³ (95% CI: 7.99 ∗ 10³-1.49 ∗ 10⁶ MP m^-³). We found that in 2010 for 0.17% of the surface layer (0-5 m) of the global ocean a threatening risk would occur. By 2050 and 2100, this fraction increases to 0.52% and 1.62%, respectively, according to the worst-case predicted future plastic discharge into the ocean. Our results reveal a spatial and multidecadal variability of MP-related risk at the global ocean surface. For example, we have identified the Mediterranean Sea and the Yellow Sea as hotspots of marine microplastic risks already now and even more pronounced in future decades.

Perspectives for integrating human and environmental risk assessment and synergies with socio-economic analysis

For more than a decade, the integration of human and environmental risk assessment (RA) has become an attractive vision. At the same time, existing European regulations of chemical substances such as REACH (EC Regulation No. 1907/2006), the Plant Protection Products Regulation (EC regulation 1107/2009) and Biocide Regulation (EC Regulation 528/2012) continue to ask for sector-specific RAs, each of which have their individual information requirements regarding exposure and hazard data, and also use different methodologies for the ultimate risk quantification. In response to this difference between the vision for integration and the current scientific and regulatory practice, the present paper outlines five medium-term opportunities for integrating human and environmental RA, followed by detailed discussions of the associated major components and their state of the art. Current hazard assessment approaches are analyzed in terms of data availability and quality, and covering non-test tools, the integrated testing strategy (ITS) approach, the adverse outcome pathway (AOP) concept, methods for assessing uncertainty, and the issue of explicitly treating mixture toxicity. With respect to exposure, opportunities for integrating exposure assessment are discussed, taking into account the uncertainty, standardization and validation of exposure modeling as well as the availability of exposure data. A further focus is on ways to complement RA by a socio-economic assessment (SEA) in order to better inform about risk management options. In this way, the present analysis, developed as part of the EU FP7 project HEROIC, may contribute to paving the way for integrating, where useful and possible, human and environmental RA in a manner suitable for its coupling with SEA.

Joint algal toxicity of 16 dissimilarly acting chemicals is predictable by the concept of independent action

For a predictive assessment of the aquatic toxicity of chemical mixtures, two competing concepts are available: concentration addition and independent action. Concentration addition is generally regarded as a reasonable expectation for the joint toxicity of similarly acting substances. In the opposite case of dissimilarly acting toxicants the choice of the most appropriate concept is a controversial issue. In tests with freshwater algae we therefore studied the extreme situation of multiple exposure to chemicals with strictly different specific mechanisms of action. Concentration response analyses were performed for 16 different biocides, and for mixtures containing all 16 substances in two different concentration ratios. Observed mixture toxicity was compared with predictions, calculated from the concentration response functions of individual toxicants by alternatively applying both concepts. The assumption of independent action yielded accurate predictions, irrespective of the mixture ratio or the effect level under consideration. Moreover, results even demonstrate that dissimilarly acting chemicals can show significant joint effects, predictable by independent action, when combined in concentrations below individual NOEC values, statistically estimated to elicit insignificant individual effects of only 1%. The alternative hypothesis of concentration addition resulted in overestimation of mixture toxicity, but differences between observed and predicted effect concentrations did not exceed a factor of 3.2. This finding complies with previous studies, which indicated near concentration-additive action of mixtures of dissimilarly acting substances. Nevertheless, with the scientific objective to predict multi-component mixture toxicity with the highest possible accuracy, concentration addition obviously is no universal solution. Independent action proves to be superior where components are well known to interact specifically with different molecular target sites, and provided that reliable statistical estimates of low toxic effects of individual mixture constituents can be given. With a regulatory perspective, however, fulfilment of both conditions may be regarded as an extraordinary situation, and hence concentration addition may be defendable as a pragmatic and precautionary default assumption.

Water quality objectives for mixtures of toxic chemicals: problems and perspectives

The need to develop water quality objectives not only for single substances but also for mixtures of chemicals seems evident. For that purpose, the conceptual basis could be the use of the two existing biometric models: concentration addition (CA) and independent action (IA), which is also called response addition. Both may allow calculation of the toxicity of mixtures of chemicals with similar modes of action (CA) or dissimilar modes of action (IA), respectively. The joint research project Prediction and Assessment of the Aquatic Toxicity of Mixtures of Chemicals (PREDICT) within the framework of the IVth Environment and Climate Programme of the European Commission, provided the opportunity to address (a) chemometric and QSAR criteria to classify substances as supposedly similarly or dissimilarly acting; (b) the predictive values of both models for the toxicity of mixtures at low, statistically nonsignificant effect concentrations of the individual components; and (c) the predictability of mixture toxicity at higher levels of biological complexity. In this article, the general outline, methodological approach, and some preliminary findings of PREDICT are presented. A procedure for classifying chemicals in relation to their structural and toxicological similarities has been developed. The predictive capabilities of CA and IA models have been demonstrated for single species and, to some extent, for multispecies testing. The role of very low effect concentrations in multiple mixtures has been evaluated. Problems and perspectives concerning the development of water quality objectives for mixtures are discussed.

Predicting the joint algal toxicity of multi-component s-triazine mixtures at low-effect concentrations of individual toxicants

Herbicidal s-triazines are widespread contaminants of surface waters. They are highly toxic to algae and other primary producers in aquatic systems. This results from their specific interference with photosynthetic electron transport. Risk assessment for aquatic biota has to consider situations of simultaneous exposure to various of these toxicants. In tests with freshwater algae we predicted and determined the toxicity of multiple mixtures of 18 different s-triazines. The toxicity parameter was the inhibition of reproduction of Scenedesmus vacuolatus. Concentration-response analyses were performed for single toxicants and for mixtures containing all 18 s-triazines in two different concentration ratios. Experiments were designed to allow a valid statistical description of the entire concentration-response relationships, including the low concentration range down to EC1. Observed effects and effect concentrations of mixtures were compared to predictions of mixture toxicity. Predictions were calculated from the concentration-response functions of individual s-triazines by applying the concepts of concentration addition and independent action (response addition) alternatively. Predictions based on independent action tend to underestimate the overall toxicity of s-triazine mixtures. In contrast, the concept of concentration addition provides highly accurate predictions of s-triazine mixture toxicity, irrespective of the effect level under consideration and the concentration ratio of the mixture components. This also holds true when the mixture components are present in concentrations below their individual NOEC values. Concentrations statistically estimated to elicit non-significant effects of only 1% still contribute to the overall toxicity. When present in a multi-component mixture they can co-operate to give a severe joint effect. Applicability of the findings obtained with s-triazines to mixtures of other contaminants in aquatic systems and consequences for risk assessment procedures are discussed.

A general best-fit method for concentration-response curves and the estimation of low-effect concentrations

Risk assessments of toxic chemicals currently rely heavily on the use of no-observed-effect concentrations (NOECs). Due to several crucial flaws in this concept, however, discussion of replacing NOECs with statistically estimated low-effect concentrations continues. This paper describes a general best-fit method for the estimation of effects and effect concentrations by the use of a pool of 10 different sigmoidal regression functions for continuous toxicity data. Due to heterogeneous variabilities in replicated data (i.e., heteroscedasticity), the concept of generalized least squares is used for the estimation of the model parameters, whereas a nonparametric variance model based on smoothing spline functions is used to describe the heteroscedasticity. To protect the estimates against outliers, the generalized least-squares method is improved by winsorization. On the basis of statistical selection criteria, the best-fit model is chosen individually for each set of data. Furthermore, the bootstrap methodology is applied for constructing confidence intervals for the estimated effect concentrations. The best-fit method for the estimation of low-effect concentrations is validated by a simulation study, and its applicability is demonstrated with toxicity data for 64 chemicals tested in an algal and a bacterial bioassay. In comparison with common methods of concentration-response analysis, a clear improvement is achieved.

The single substance and mixture toxicity of quinolones to the bioluminescent bacterium Vibrio fischeri

Quinolones are one of the most important group of synthetic antibiotics used in aquaculture. We studied the single substance and mixture toxicity of ten quinolones using a long term bioluminescence inhibition assay with the marine bacterium Vibrio fischeri as the test organism. All tested quinolones are highly toxic to the test organism with EC50 values ranging from 14 µg/l for ofloxacin to 1020 µg/l for pipemidic acid. Adapting the approach outlined in EEC directive 93/21/EEC to these results, all but one of the ten quinolones belong to the group classified as being 'very toxic to aquatic organisms' (EC50 below 1 mg/l). On the basis of the concentration-response relationships of the single compounds, the mixture toxicity of the ten compounds was estimated by the concepts of concentration addition and independent action. Complete concentration-response relationships were experimentally recorded for the quinolone mixture in three different mixture ratios, based on the relative toxicity of the components (EC50, EC1 and NOEC). The results show that the mixture toxicity of the quinolones is best predictable by concentration addition, whereas independent action underestimates the toxicity of the mixture. As the quinolones have an identical specific mechanism of action (the inhibition of bacterial gyrases), these results are in agreement with the pharmacological assumptions that form the basis of the concept of concentration addition. It is therefore concluded, that concentration addition can be useful for hazard assessment procedures of mixtures of similarly acting compounds. One important implication of this concept is that even mixture components that are present only at their individual no observed effect concentrations (NOECs) contribute to the overall toxicity of the mixture. Under these conditions more than 99% effect of the quinolone mixture are observed. This result emphasises the unsuitability of NOECs as an approximation of a 'safe' concentration.

Bioassays with Vibrio fischeri for the assessment of delayed toxicity

The standardized bioluminescence assay with Vibrio fischeri underestimates the aquatic toxicity of chemicals which interfere with metabolic pathways supporting long term processes like growth and reproduction due to its short incubation time (30 min). Therefore this short term assay was compared with two alternative bioassays with prolonged incubation times using the same test organism: the growth inhibition assay (7 h) and the long term bioluminescence assay (24 h). Two sets of compounds were selected to reflect acute and delayed toxicity. The first group comprised pentachlorophenol, dodecylpyridiniumbromide and 3,4-dichloroaniline and the second nalidixic acid, chloramphenicol and streptomycinsulfate. The effects of compounds with acute toxicity are determined with similar sensitivity in all bioassays. Substances with delayed toxicity show only minor or no toxicities in the standardized short term bioassay but severe effects in both long term bioassays independent of the parameter used. It is concluded that the standardized short term bioluminescence assay exhibits serious limitations for the assessment of aquatic toxicity. The long term bioassays, however, may help to overcome these limitations.

The toxicity of antibiotic agents to the luminescent bacterium Vibrio fischeri

Despite their common use the fate and effects of antibiotics in the environment are largely unknown. These compounds may enter the environment through different pathways, resulting in the contamination of waste water or fresh water, where bacteria are most likely the primarily affected organisms. In this paper the toxicity of several drugs, reflecting the most important groups of antibiotics and chemotherapeutics, towards Vibrio fischeri are presented. The chronic bioluminescence inhibition assay with Vibrio fischeri is shown to be sensitive against many of the high volume antibiotics used for veterinary purposes and in aquaculture. Thus the assay may be a valuable tool for an effects assessment and biomonitoring of these xenobiotics. The available data for both parts of the risk assessment procedure--exposure assessment and effects assessment--have to be regarded as insufficient for most antibiotics. When the available data about environmental concentrations of antibiotics are compared with their toxicity towards Vibrio fischeri, direct effects on natural microbial communities are to be expected.

Xenobiotic biotransformation in unicellular green algae. Involvement of cytochrome P450 in the activation and selectivity of the pyridazinone pro-herbicide metflurazon

The N-demethylation of the pyridazinone pro-herbicide metflurazon into norflurazon implies a toxification in photosynthetic organisms. This is confirmed by quantitative structure activity relationships determined for two unicellular green algae, Chlorella sorokiniana and Chlorella fusca; however, the latter is 25 to 80 times more sensitive to metflurazon. This sensitivity is linked to differences in the N-demethylase activity of both algae, as determined by an optimized in vivo biotransformation assay. Apparent K(m) values of the metflurazon-N-demethylase indicate a 10-fold higher affinity for this xenobiotic substrate for Chlorella fusca. Furthermore, algal metflurazon-N-demethylation is characterized by distinct variations in activity, depending on the stage of cell development within the cell cycle. Several well-established inhibitors of cytochrome P450-mediated reactions, including piperonylbutoxide, 1-aminobenzotriazole, 1-phenoxy-3-(1H-1,2,4-triol-1yl)-4-hydroxy-5,5-dimethylhexane++ +, and tetcyclacis, as well as cinnamic acid, a potential endogenous substrate, inhibited the N-demethylation of metflurazon. The results suggest that the N-demethylation of metflurazon by both algae is mediated by a cytochrome P450 monooxygenase. The determination of antigenic cross-reactivity of algal proteins with heterologous polyclonal antibodies originally raised against plant P450s, anti-cinnamic acid 4-hydroxylase (CYP73A1), anti-ethoxycoumarin-O-dealkylase, anti-tulip allene oxidase (CYP74), and an avocado P450 (CYP71A1) or those of bacterial origin, CYP105A1 and CYP105B1, suggests the presence of distinct P450 isoforms in both algae.