A Framework for Algae Modeling in Regulatory Risk Assessment.

The use of toxicokinetic-toxicodynamic (TKTD) modeling in regulatory risk assessment of plant protection products is increasingly popular, especially since the 2018 European Food Safety Authority (EFSA) opinion on TKTD modeling announced that several established models are ready for use in risk assessment. With careful adherence to the guidelines laid out by EFSA, we present a stepwise approach to validation and use of the Simple Algae Model Extended (SAM-X) for regulatory submission in Tier 2C. We demonstrate how the use of moving time windows across time-variable exposure profiles can generate thousands of virtual laboratory mimic simulations that seamlessly predict the effects of time-variable exposures across a full exposure profile while maintaining the laboratory conditions of the standard Organisation for Economic Co-operation and Development (OECD) growth inhibition test. Thus, every virtual laboratory test has a duration of 72 h, with OECD medium and constant light and temperature conditions. The only deviation from the standard test setup is the replacement of constant exposure conditions for time-variable concentrations. The present study demonstrates that for simulation of 72-h toxicity tests, the nutrient dynamics in the SAM-X model are not required, and we propose the alternative use of a simplified model version. For risk assessment, in accordance with the EFSA guidelines we use a median exposure profile of 10 as a threshold, meaning that if a time window within the exposure profile causes 50% growth inhibition when magnified by a factor of 10, the threshold will have been exceeded. We present a simplified example for chlorotoluron and isoproturon. The present case study brings to life our proposed framework for TKTD modeling of algae to establish whether a given exposure can be considered to be of low risk. Environ Toxicol Chem 2023;42:1823-1838. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line.

With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.

Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: Meta-analysis and model corroboration.

Understanding the consequences of the combined effects of multiple stressors-including stress from man-made chemicals-is important for conservation management, the ecological risk assessment of chemicals, and many other ecological applications. Our current ability to predict and analyse the joint effects of multiple stressors is insufficient to make the prospective risk assessment of chemicals more ecologically relevant because we lack a full understanding of how organisms respond to stress factors alone and in combination. Here, we describe a Dynamic Energy Budget (DEB) based bioenergetics model that predicts the potential effects of single or multiple natural and chemical stressors on life history traits. We demonstrate the plausibility of the model using a meta-analysis of 128 existing studies on freshwater invertebrates. We then validate our model by comparing its predictions for a combination of three stressors (i.e. chemical, temperature, and food availability) with new, independent experimental data on life history traits in the daphnid Ceriodaphnia dubia. We found that the model predictions are in agreement with observed growth curves and reproductive traits. To the best of our knowledge, this is the first time that the combined effects of three stress factors on life history traits observed in laboratory studies have been predicted successfully in invertebrates. We suggest that a re-analysis of existing studies on multiple stressors within the modelling framework outlined here will provide a robust null model for identifying stressor interactions, and expect that a better understanding of the underlying mechanisms will arise from these new analyses. Bioenergetics modelling could be applied more broadly to support environmental management decision making.

Potential impact of chemical stress on freshwater invertebrates: A sensitivity assessment on continental and national scale based on distribution patterns, biological traits, and relatedness.

Current chemical risk assessment approaches rely on a standard suite of test species to assess toxicity to environmental species. Assessment factors are used to extrapolate from single species to communities and ecosystem effects. This approach is pragmatic, but lacks resolution in biological and environmental parameters. Novel modelling approaches can help improve the biological resolution of assessments by using mechanistic information to identify priority species and priority regions that are potentially most impacted by chemical stressors. In this study we developed predictive sensitivity models by combining species-specific information on acute chemical sensitivity (LC50 and EC50), traits, and taxonomic relatedness. These models were applied at two spatial scales to reveal spatial differences in the sensitivity of species assemblages towards two chemical modes of action (MOA): narcosis and acetylcholinesterase (AChE) inhibition. We found that on a relative scale, 46% and 33% of European species were ranked as more sensitive towards narcosis and AChE inhibition, respectively. These more sensitive species were distributed with higher occurrences in the south and north-eastern regions, reflecting known continental patterns of endemic macroinvertebrate biodiversity. We found contradicting sensitivity patterns depending on the MOA for UK scenarios, with more species displaying relative sensitivity to narcotic MOA in north and north-western regions, and more species with relative sensitivity to AChE inhibition MOA in south and south-western regions. Overall, we identified hotspots of species sensitive to chemical stressors at two spatial scales, and discuss data gaps and crucial technological advances required for the successful application of the proposed methodology to invertebrate scenarios, which remain underrepresented in global conservation priorities.

Vision of a near future: Bridging the human health-environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment.

There is a growing recognition that application of mechanistic approaches to understand cross-species shared molecular targets and pathway conservation in the context of hazard characterization, provide significant opportunities in risk assessment (RA) for both human health and environmental safety. Specifically, it has been recognized that a more comprehensive and reliable understanding of similarities and differences in biological pathways across a variety of species will better enable cross-species extrapolation of potential adverse toxicological effects. Ultimately, this would also advance the generation and use of mechanistic data for both human health and environmental RA. A workshop brought together representatives from industry, academia and government to discuss how to improve the use of existing data, and to generate new NAMs data to derive better mechanistic understanding between humans and environmentally-relevant species, ultimately resulting in holistic chemical safety decisions. Thanks to a thorough dialogue among all participants, key challenges, current gaps and research needs were identified, and potential solutions proposed. This discussion highlighted the common objective to progress toward more predictive, mechanistically based, data-driven and animal-free chemical safety assessments. Overall, the participants recognized that there is no single approach which would provide all the answers for bridging the gap between mechanism-based human health and environmental RA, but acknowledged we now have the incentive, tools and data availability to address this concept, maximizing the potential for improvements in both human health and environmental RA.

Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits.

In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

Integrated presentation of ecological risk from multiple stressors.

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

A Multimedia Fate Model to Support Chemical Management in China: A Case Study for Selected Trace Organics.

SESAMe v3.3, a spatially explicit multimedia fate model for China, is a tool suggested to support quantitative risk assessment for national scale chemical management. The key advantage over the previous version SESAMe v3.0 is consideration of spatially varied environmental pH. We evaluate the model performance using estimates of emission from total industry usage of three UV filters (benzophenone-3, octocrylene, and octyl methoxycinnamate) and three antimicrobials (triclosan, triclocarban, and climbazole). The model generally performs well for the six case study chemicals as shown by the comparison between predictions and measurements. The importance of accounting for chemical ionization is demonstrated with the fate and partitioning of both triclosan and climbazole sensitivity to environmental pH. The model predicts ionizable chemicals (triclosan, climbazole, benzophenone-3) to primarily partition into soils at steady state, despite hypothetically only being released to freshwaters, as a result of agricultural irrigation by freshwater. However, further model calibration is needed when more field data becomes available for soils and sediments and for larger areas of water. As an example, accounting for the effect of pH in the environmental risk assessment of triclosan, limited freshwater areas (0.03% or ca. 55 km(2)) in mainland China are modeled to exceed its conservative environmental no-effect threshold. SESAMe v3.3 can be used to support the development of chemical risk assessment methodologies with the spatial aspects of the model providing a guide to the identification regions of interest in which to focus monitoring campaigns or develop a refined risk assessment.

Accounting for dissociation and photolysis: a review of the algal toxicity of triclosan.

Triclosan, an antimicrobial agent commonly used in down-the-drain consumer products, is toxic to freshwater microalgae. However, the rapid photolysis and pH-dependent dissociation of this compound may give rise to uncertainty in growth inhibition tests with freshwater microalgae, if these are not well characterized. Methods are presented to minimize these uncertainties by stabilizing pH with an organic buffering agent (Bis-Tris) and by the application of ultraviolet (UV) covers to remove UV wavelengths. Toxicity tests with these methods were in compliance with the validity criteria of the Organisation for Economic Co-operation and Development test 201, and no negative effects were seen in controls relative to the unmodified method. The methods were used for toxicity tests with triclosan at pH levels of 7.0, 8.0, and 8.5, yielding effective concentration, 10% values of 0.5 µg/L, 0.6 µg/L, and 12.1 µg/L, respectively. The observed change in toxicity with pH was proportional to the change in bioconcentration factor (BCF) as calculated using the cell model (a dynamic flux model based on the Fick-Nernst-Planck equations, in this case parameterized for an algal cell). Effect concentrations produced with the methods presented in the present study offer robust data on which to base risk assessment, and it is suggested that similar approaches be used to minimize uncertainty when other compounds that dissociate and photolyse are tested.

Effect of pH on the toxicity and bioconcentration of sulfadiazine on Daphnia magna.

The antimicrobial sulfonamide sulfadiazine has in the last decades been detected in environmental water bodies, both surface and ground water. Since pH in the environment may vary considerably, this study examined the toxicity of the amphoter sulfadiazine towards Daphnia magna at pH levels of 6.0, 7.5 and 8.5, thus taking the impact of speciation into consideration, contrary to earlier eco-toxicity studies conducted at standard conditions. Toxicity tests were performed using the standard ISO 6341 test procedure modified to accommodate the three pH levels and the toxicity was expressed as EC50. After 48 h the EC50 was determined to be 27.2, 188 and 310 mg L(-1) at pH 6.0, 7.5 and 8.5, respectively, thus demonstrating a significant effect of pH on the toxicity of sulfadiazine. Furthermore, the bioconcentration factor (dry weight) was determined to be 50 and 36 at pH 6.0 and 8.5, respectively. The higher toxicity at the lower pHs was assumed to be caused by the higher fraction of un-ionized sulfadiazine at the lower pHs. However, the one and a half fold higher bioconcentration at pH 6.0 relative to pH 8.5 does not match the more than ten times higher toxicity at pH 6.0. When comparing the fraction of neutral compound to toxicity and bioconcentration results neither toxicity nor bioconcentration can be ascribed solely to the unionized fraction of sulfadiazine.

Critical evaluation and further development of methods for testing ecotoxicity at multiple pH using Daphnia magna and Pseudokirchneriella subcapitata.

To meet the requirements of risk assessment legislature regarding the ecotoxicity of ionizing compounds, the present study attempts to establish easy, robust methods for testing ecotoxicity at various pH levels. An overview is given of the buffering methods found in the literature. This is supplemented by a series of experiments where toxicity and ability to stabilize pH of seven common buffering compounds was tested on Daphnia magna and Pseudokirchneriella subcapitata. We consider a buffer applicable at a given concentration if the pH drift is below 0.2 pH units, and if there are no toxic effects. Twenty-four- and 48-h acute toxicity tests with D. magna were carried on a series of organic buffers with pH monitoring. Based on the experimental results it is possible to give recommendations for buffer concentrations for use in toxicity testing with D. magna at pH levels in the range of pH 6.0-7.8 for 48 h exposure, and pH 6.0-9.5 for 24 h exposure. Forty-eight- and 72-h growth inhibition tests with P. subcapitata were carried out, and recommendations for buffer concentrations at pH 7.5 and 8.0 are made for both 48 and 72 h of exposure.

Optimal choice of pH for toxicity and bioaccumulation studies of ionizing organic chemicals.

It is recognized that the pH of exposure solutions can influence the toxicity and bioaccumulation of ionizing compounds. The present study investigates whether it can be considered a general rule that an ionizable compound is more toxic and more bioaccumulative when in the neutral state. Three processes were identified to explain the behavior of ionizing compounds with changing pH: the change in lipophilicity when a neutral compound becomes ionized, electrical attraction, and the ion trap. The literature was screened for bioaccumulation and toxicity tests of ionizing organic compounds performed at multiple pH levels. Toxicity and bioconcentration factors (BCFs) were higher for acids at lower pH values, whereas the opposite was true for bases. The effect of pH was most pronounced when pH - pK(a) was in the range of -1 to 3 for acids, and -3 to 1 for bases. The factor by which toxicity and BCF changed with pH was correlated with the lipophilicity of the compound (log K(OW) of the neutral compound). For both acids and bases, the correlation was positive, but it was significant only for acids. Because experimental data in the literature were limited, results were supplemented with model simulations using a dynamic flux model based on the Fick-Nernst-Planck diffusion equation known as the cell model. The cell model predicts that bases with delocalized charges may in some cases show declining bioaccumulation with increasing pH. Little information is available for amphoteric and zwitterionic compounds; however, based on simulations with the cell model, it is expected that the highest toxicity and bioaccumulation of these compounds will be found where the compounds are most neutral, at the isoelectric point.

The effect of pH on the uptake and toxicity of the bivalent weak base chloroquine tested on Salix viminalis and Daphnia magna.

The uptake and accumulation of most electrolytes will change with pH because of the different speciation states of these compounds at various pH. Non-ionized compounds will partition into fatty and organic phases (such as cell membranes) more readily than the corresponding charged compounds, and therefore a higher toxicity can be expected. The current study examines the pH-dependent toxicity and bioaccumulation of the bivalent weak base chloroquine (pK(a): 10.47 and 6.33, log K(OW) 4.67) tested on Salix viminalis (basket willow) and Daphnia magna (water flea). The transpiration rates of hydroponically grown willow cuttings were used to determine the toxicity of chloroquine at pH levels of 6, 7, 8, and 9. Root concentration factors were calculated from solution measurements. Results showed more than 10-fold higher toxicity and four to seven times higher root concentration factor at pH 9 than at pH 6. The toxicity of chloroquine was tested on Daphnia magna using the standard Organisation for Economic Co-operation and Development acute toxicity test modified to accommodate testing at pH levels of 7, 8, and 9. Increasing toxicity was seen at higher pH. The results of the current study confirm that the toxicity of weak bases with intermediate pK(a) values is higher at high pH levels.