Revisiting simplified DEBtox models for analysing ecotoxicity data

Sedimentary co-exposure to bis(2-ethylhexyl) phthalate and titanium dioxide nanoparticles aggravate ecotoxicity and ecological risks through disrupted bioenergetics in Caenorhabditis elegans

Emerging contaminants in estuarine sediments, such as bis(2-ethylhexyl) phthalate (DEHP) and titanium dioxide nanoparticles (nTiO2), pose ecotoxicological risks that may be exacerbated by co-contamination. This study investigated the impacts of DEHP, nTiO2, and their combinations at environmentally relevant concentrations (1, 10, and 100 μg/g) on the soil nematode Caenorhabditis elegans in estuarine-like sediment (14.25‰ salinity). Life history traits and bioenergetics endpoints were examined, with a sample size of ≥ 45 worms or 9 technical repeats per treatment. While individual exposures did not affect growth, the combination of DEHP (1 μg/g) and nTiO2 (100 μg/g) significantly reduced body length by 19%. Single exposure reduced total offspring by 18-41%, whereas the combination of DEHP and nTiO2 synergistically worsened reproductive toxicity (52-74% inhibition), as revealed by Loewe's additivity model and Bliss's independence. DEBtox modeling revealed a shift in physiological mode of action from "increased reproductive costs" in singular exposures to "increased growth and reproductive cost" in co-exposure. Moreover, co-exposure significantly intensified the impacts on bioenergetics-related endpoints, including ATP level (single exposure: 33-34%; co-exposure: 56%), mitochondrial damage (single exposure: 15-17%; co-exposure: 40%), and oxidative stress (single exposure: 5-7%; co-exposure: 13%). Risk quotients based on reproductive toxicity EC10 and DEBtox-derived zb suggested that environmental concentrations of DEHP and nTiO2 pose high risks in global estuarine sediments, with a 2-fold increase during co-exposure. This study demonstrates that co-contamination of DEHP and nTiO2 synergistically aggravates ecotoxicities through disrupted energy allocation, highlighting the importance of assessing mixture toxicity in environmental risk assessment of estuarine sediments.

From water to land-Usage of Generalized Unified Threshold models of Survival (GUTS) in an above-ground terrestrial context exemplified by honeybee survival data

In regulatory aquatic risk assessment, toxicokinetic-toxicodynamic (TKTD) methods, such as the generalized unified threshold model of survival (GUTS), are already established and considered ready for use, whereas TKTD methods for aboveground terrestrial species, like arthropods, are less developed and currently not intended for risk assessment. This could be due to the fact that exposure in aboveground terrestrial systems is more event-based (feeding, contact, overspray, etc.), whereas exposure in aquatic systems is simply related to substance concentrations in the surrounding water. To provide a generic TKTD framework for terrestrial invertebrates, we propose a new GUTS variant that includes an intermediate buffer between the external exposure and inside of the organism. This buffer can be interpreted as residues on the exoskeleton or in the stomach, depending on the uptake route. Such an uptake behavior is mechanistically reasonable and observable in laboratory experiments. This GUTS variant, BufferGUTS, is particularly suitable for discrete or discretized exposure scenarios. Testing our model on honeybee datasets for 13 pesticides reveals a similar or better reproduction of survival curves than existing models (GUTS-RED and BeeGUTS) while keeping the number of parameters the same and making no substance or species-specific assumptions. The proposed new BufferGUTS approach can prospectively be used to derive TKTD parameters for a variety of terrestrial arthropod species. A standardized model definition for terrestrial species will facilitate the comparison and extrapolation of parameters between species and the applicability for terrestrial risk assessments.

Application of the DEB-TKTD model with multi-omics data: Prediction of life history traits of Chinese mitten crab (Eriocheir sinensis) under different salinities

Saline-alkaline aquaculture plays a crucial role in the ecological restoration of saline soils, yet high water salinity can significantly restrict the growth of cultured organisms. The Chinese mitten crab (Eriocheir sinensis) is typically farmed in freshwater, to evaluate the effects of salinity stress on these crabs, this study conducted laboratory aquaculture experiments at salinities of ≤ 0.5 (freshwater), 6, 12, and 18 ‰. Regular data on crab survival and growth were collected over 35 days. Subsequently, tissues including the eyestalk, posterior gill, hepatopancreas, and ovary were sampled from crabs in both the freshwater control group and the 18 ‰ salinity treatment group for transcriptional and metabolomic analysis. The omics data were used to ascertain the physiological mode of action (pMoA) affected by salinity in the crabs. A dynamic energy budget toxicokinetic-toxicodynamic (DEB-TKTD) model was built based on these pMoAs to predict the life history traits of crabs across different salinities, including survival, growth, and reproduction. The omics results indicated that at 18 ‰, the osmoregulatory capacity and oxidative stress resistance were enhanced, and vitellogenin synthesis was stimulated. This suggests that the two pMoAs involved increasing maintenance costs and reallocating energy between soma and reproduction. DEB-TKTD model predictions fit well with the observed data, with high R2 values (0.9704 for survival, 0.9842 for carapace width, and 0.9283 for reproduction) and low NRMSE (0.0093, 0.1175, and 0.0778, respectively). The predictions indicate that after 60 days, survival rates under salinities of 6, 12, and 18 ‰ decreased by 35.7 %, 56.7 %, and 66.2 %, respectively, compared to freshwater conditions. Growth in carapace width was similarly affected, with reductions of 21.5 %, 42.3 %, and 62.5 %, respectively. The maturation process was accelerated for crabs in saline conditions, with puberty achieved at 45, 36, and 31 days, compared to the freshwater group that had not matured. Furthermore, the LC50 for salinity decreased from 9.07 ‰ (95 % CI: 7.33-10.15 ‰) at 35 days to 4.59 ‰ (95 % CI: 3.12-5.83 ‰) at 60 days. The findings of this study indicate the significant impact of salinity on the survival, growth, and maturation of Chinese mitten crabs by altering maintenance costs and energy allocation. The DEB-TKTD model, informed by omics data, accurately predicts the life history traits of crabs under saline stress. This approach provides an innovative tool for ecological toxicological research in the aquaculture environment.

Comparing freshwater mussel responses to stress using life-history and Dynamic Energy Budget theory

Freshwater mussels are experiencing severe population declines, affecting their critical role in freshwater ecosystems. A thorough assessment of threats posed by various stressors is needed; however, the large number of species to be considered and significant data gaps, especially for listed species, hinder the process. We combined a traits-based approach to represent multiple species grouped into three life-history categories - Equilibrium, Opportunistic, and Periodic - with the Dynamic Energy Budget modeling principles to capture the physiological mechanisms driving individual-level responses. We used the DEB model to simulate individual life cycles and explore relationships between underlying energetics and emerging individual traits of 47 freshwater mussel species and the common toxicity test surrogate, the Eastern oyster (Crassostrea virginica), under control and stressed conditions. Stress was introduced via physiological modes of action related to four key metabolic pathways: energy assimilation, maintenance, growth, and reproduction. We recorded maximum length, age at maturity, and fecundity and compared these endpoints and their stress-induced changes among life-history categories. The life-history differences among freshwater mussels directly emerged from underlying energetics, with high assimilation and maintenance supporting opportunistic traits. Stress imposed on energy assimilation had the strongest effect on all life-history traits, and a 25 % reduction in assimilation rate resulted in an average 25 % and 60 % decrease in maximum length and fecundity, respectively, and a 24 % increase in age at maturity. Equilibrium species suffered the greatest negative effects overall, indicating that this life-history strategy might be the most susceptible to stressors. The Eastern oyster displayed extreme opportunism in its life-history traits, but its responses to stress were generally within the range observed for freshwater mussels. The study provides a much-needed general understanding of stress responses across freshwater mussel life-history categories and contributes to the foundation for developing life-history-driven population models.

Population Modeling in Metal Risk Assessment: Extrapolation of Toxicity Tests to the Population Level

Population models can be a useful tool for ecological risk assessment to increase ecological realism. In the present study, population models were used to extrapolate toxicity test results of four metals (Ag, Cu, Ni, Zn) to the population level. In total, three primary producers, five invertebrate species, and five fish species were covered. The ecological modeling-based laboratory to population effect extrapolation factor (ECOPEX factor), defined as the ratio of the predicted 10% effect concentration (EC10) at the population level and the observed EC10 for the laboratory toxicity test, ranged from 0.7 to 78.6, with a median of 2.8 (n = 27). Population modeling indicated clearly higher effect concentrations in most of the cases (ECOPEX factor >2 in 14 out of 27 cases), but in some cases the opposite was observed (in three out of 27 cases). We identified five main contributors to the variability in ECOPEX factors: (1) uncertainty about the toxicity model, (2) uncertainty about the toxicity mechanism of the metal, (3) uncertainty caused by test design, (4) impact of environmental factors, and (5) impact of population endpoint chosen. Part of the uncertainty results from a lack of proper calibration data. Nonetheless, extrapolation with population models typically reduced the variability in EC10 values between tests. To explore the applicability of population models in a regulatory context, we included population extrapolations in a species sensitivity distribution for Cu, which increased the hazardous concentration for 5% of species by a factor 1.5 to 2. Furthermore, we applied a fish population model in a hypothetical Water Framework Directive case using monitored Zn concentrations. This article includes recommendations for further use of population models in (metal) risk assessment. Environ Toxicol Chem 2024;43:2308-2328. © 2024 SETAC.

Environmental Risk Assessment of Time-Variable Toxicant Exposure with Toxicokinetic-Toxicodynamic Modeling of Sublethal Endpoints and Moving Time Windows: A Case Study with Ceriodaphnia dubia

Toxicokinetic-toxicodynamic (TKTD) modeling has received increasing attention in terms of the regulatory environmental risk assessment of chemicals. This type of mechanistic model can integrate all available data from individual-level bioassays into a single framework and enable refined risk assessments by extrapolating from laboratory results to time-variable exposure scenarios, based, for instance, on surface water exposure modeling (e.g., FOCUS). Dynamic energy budget (DEB) models coupled with TKTD modules (DEB-TKTD) constitute the leading approach to assess and predict sublethal effects of chemicals on individual organisms. However, thorough case studies are rare. We provide a state-of-the-art example with the standard aquatic test species Ceriodaphnia dubia and the fungicide azoxystrobin, including all steps, from bespoke laboratory toxicity tests to model calibration and validation, through to environmental risk assessment. Following the framework proposed in the European Food Safety Authority Scientific Opinion from 2018, we designed bespoke good laboratory practice-compliant laboratory toxicity studies based on test guideline 211 of the Organisation for Economic Co-operation and Development and then identified robust parameter values from those data for all relevant model parameters through model calibration. The DEB-TKTD model, DEBtox2019, then informed the design of the validation experiment. Once validated, the model was used to perform predictions for a time-variable exposure scenario generated by FOCUS. A moving time-window approach was used to perform the environmental risk assessment. This assessment method reduces uncertainty in the risk assessment while maintaining consistency with the traditional measures of risk. Environ Toxicol Chem 2024;43:2409-2421. © 2024 Syngenta Crop Protection AG. ibacon GmbH and The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Advancing Soil Risk Assessment: A Novel Earthworm Cocoon Test with a Complementary Toxicokinetic-Toxicodynamic Modeling Approach

In the current European Union pesticide risk assessment for soil organisms, effect endpoints from laboratory studies (Tier 1) and field studies (higher-tier risk assessment) are compared with predicted environmental concentrations in soil, derived from the proposed use pattern. The simple but conservative initial Tier 1 risk assessment considers a range of worst-case assumptions. In contrast, the higher-tier assessment focuses on specific conditions tested in the corresponding field study. Effect modeling, such as toxicokinetic-toxicodynamic (TKTD) modeling, is considered a promising future tool to address uncertainties in soil risk assessment, such as extrapolation to different ecological, pedo-climatical, or agronomical situations, or to serve as an intermediate tier for potential refinement of the risk assessment. For the implementation of TKTD modeling in soil organism risk assessment, data on earthworm growth and reproduction over time are required, which are not provided by the standard Organisation for Economic Co-operation and Development (OECD) 222 laboratory test. The underlying study with carbendazim presents a new earthworm cocoon test design, based on the OECD 222 test, to provide the necessary data as input for TKTD modeling. This proposed test design involves destructive samplings at days 7, 14, 21, and 28, enabling the determination of growth, cocoon number, and the number of juveniles hatched per cocoon in 7-day intervals. The new cocoon test allowed the disentanglement of the toxic effect of carbendazim in earthworms: At the highest concentration prominent effects on growth and reproductive output were observed, and the number of cocoons was significantly reduced compared to control. The results highlighted different physiological modes of action: effect on growth via higher maintenance costs as a primary mode of action as well as a reduced number of cocoons (effect on reproduction) and a lower number of juveniles hatching from each cocoon (hazard during oogenesis) as a secondary mode of action. We provide an example of how this new test's data can be used to feed a dynamic energy budget theory-TKTD model of Eisenia fetida. We also validate it against the original OECD 222 test design, outlining its potential future use in soil risk assessment. Environ Toxicol Chem 2024;43:2377-2386. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Application of toxicokinetic-toxicodynamic models in the aquatic ecological risk assessment of metals: A review

The issue of toxic metal pollution is a considerable environmental concern owing to its complex nature, spatial and temporal variability, and susceptibility to environmental factors. Current water quality criteria and ecological risk assessments of metals are based on single-metal toxicity data from short-term, simplified indoor exposure conditions, ignoring the complexity of actual environmental conditions. This results in increased uncertainty in predicting toxic metal toxicity and risk assessment. Using appropriate bioavailability and effect modeling of metals is critical for establishing environmental quality standards and performing risk assessments for metals. Traditional dose-effect models are based on a static statistical relationship and fall short of revealing the bioavailability and effect processes of metals and do not effectively assess ecological impacts under complex exposure conditions. This paper summarizes the toxicokinetic-toxicodynamic (TK-TD) model, which is gaining interest in environmental and ecotoxicological research. The key concepts, and theories of its construction theories, are discussed and the application of the TK-TD model in toxicity prediction and risk assessment of different metals in the aquatic environment, and trends in the development of the TK-TD model are highlighted. The findings of our review prove that the TK-TD model can effectively predict toxic metal toxicity in real time and under complex exposure conditions in the future.

Dynamic Energy Budget model for E. coli growth in carbon and nitrogen limitation conditions

The simulations and predictions obtained from mathematical models of bioprocesses conducted by microorganisms are not overvalued. Mechanistic models are bringing a better process understanding and the possibility of simulating unmeasurable variables. The Dynamic Energy Budget (DEB) model is an energy balance that can be formulated for any living organism and can be classified as a structured model. In this study, the DEB model was used to describe E. coli growth in a batch reactor in carbon and nitrogen substrate limitation conditions. The DEB model provides a possibility to follow the changes in the microbes' cells including their elemental composition and content of some important cell ingredients in different growth phases in substrate limitation conditions which makes it more informative compared to Monod's model. The model can be used as an optimal choice between Monod-like models and flux-based approaches. KEY POINTS: • The DEB model can be used to catch changes in elemental composition of E. coli • Bacteria batch culture growth phases can be explained by the DEB model • The DEB model is more informative compared to Monod's based models.

Reproductive toxicity in birds predicted by physiologically-based kinetics and bioenergetics modelling

Effects on the growth and reproduction of birds are important endpoints in the environmental risk assessment (ERA) of pesticides. Toxicokinetic-toxicodynamic models based on dynamic energy budget theory (DEB) are promising tools to predict these effects mechanistically and make extrapolations relevant to ERA. However, before DEB-TKTD models are accepted as part of ERA for birds, ecotoxicological case studies are required so that stakeholders can assess their capabilities. We present such a case-study, modelling the effects of the fluopyram metabolite benzamide on the northern bobwhite quail (Colinus virginianus). We parametrised a DEB-TKTD model for the embryo stage on the basis of an egg injection study, designed to provide data for model development. We found that information on various endpoints, such as survival, growth, and yolk utilisation were needed to clearly distinguish between the performance of model variants with different TKTD assumptions. The calibration data were best explained when it was assumed that chemical uptake occurs via the yolk and that benzamide places stress on energy assimilation and mobilisation. To be able to bridge from the in vitro tests to real-life exposure, we developed a physiologically-based toxicokinetic (PBK) model for the quail and used it to predict benzamide exposure inside the eggs based on dietary exposure in a standard reproductive toxicity study. We then combined the standard DEB model with the TKTD module calibrated to the egg injection studies and used it to predict effects on hatchling and 14-day chick weight based on the exposure predicted by the PBK model. Observed weight reductions, relative to controls, were accurately predicted. Thus, we demonstrate that DEB-TKTD models, in combination with suitable experimental data and, if necessary, with an exposure model, can be used in bird ERA to predict chemical effects on reproduction.

Environmental Risk Assessment with Energy Budget Models: A Comparison Between Two Models of Different Complexity

The extrapolation of effects from controlled standard laboratory tests to real environmental conditions is a major challenge facing ecological risk assessment (ERA) of chemicals. Toxicokinetic-toxicodynamic (TKTD) models, such as those based on dynamic energy budget (DEB) theory, can play an important role in filling this gap. Through the years, different practical TKTD models have been derived from DEB theory, ranging from the full "standard" DEB animal model to simplified "DEBtox" models. It is currently unclear what impact a different level of model complexity can have on the regulatory risk assessment. In the present study, we compare the performance of two DEB-TKTD models with different levels of complexity, focusing on model calibration on standard test data and on forward predictions for untested time-variable exposure profiles. The first model is based on the standard DEB model with primary parameters, whereas the second is a reduced version with compound parameters, based on DEBkiss. After harmonization of the modeling choices, we demonstrate that these two models can achieve very similar performances both in the calibration step and in the forward prediction step. With the data presented in the present study, selection of the most suitable TKTD model for ERA therefore cannot be based alone on goodness-of-fit or on the precision of model predictions (within current ERA procedures for pesticides) but would likely be based on the trade-off between ease of use and model flexibility. We also stress the importance of modeling choices, such as how to fill gaps in the information content of experimental toxicity data and how to accommodate differences in growth and reproduction between different data sets for the same chemical-species combination. Environ Toxicol Chem 2024;43:440-449. © 2023 ibacon GmbH. Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Impact of the antidepressant Bupropion on the Dynamic Energy Budget of Daphnia magna

Psychiatric drugs are considered among the emerging contaminants of concern in ecological risk assessment, due to their potential to disrupt homeostasis in aquatic organisms. Bupropion is an antidepressant that acts by selective reuptake inhibition of norepinephrine and dopamine. Little is known about this compound's effects on aquatic organisms, despite being detected in significant concentrations in both water and biota close to waste-water treatment plants and densely populated areas. Dynamic Energy Budget (DEB) models are flexible mechanistic tools that can be applied to understand toxic effects and extrapolate individual responses to higher biological levels and under untested environmental conditions. In this work, we used the stdDEB-TKTD (an application of the DEB theory to ecotoxicology) approach to investigate the possible physiological mode of action of Bupropion on the model organism Daphnia magna. Next, Dynamic Energy Budget Individual-Based Models (DEB-IBM) were used to extrapolate the results to the population level and to predict the combined effects of Bupropion exposure and food availability on the daphnids. Our results revealed an increasing negative effect of this antidepressant on the reproduction and survival of the animals with increasing concentration (0.004, 0.058, 0.58 and 58 μM). At the population level, we found that even the lowest used doses of Bupropion could reduce the population density and its reproductive output. The impacts are predicted to be stronger under limited food conditions.

Sublethal effects of binary mixtures of Cu2+ and Cd2+ on Daphnia magna: Standard Dynamic Energy Budget (DEB) model analysis

Dynamic Energy Budget theory (DEB) describes mass and energy fluxes that occur in living organisms. DEB models were successfully used to assess the influence of stress, including toxic substances, and changes in pH and temperature, on different organisms. In this study, the Standard DEB model was used to evaluate the toxicity of copper and cadmium ions and their binary mixtures on Daphnia magna. Both metal ions have a significant influence on daphnia growth and reproduction. Different physiological modes of action (pMoA) were applied to primary DEB model parameters. Model predictions for chosen modes of interaction of mixture components were evaluated. The goodness of model fit and the model prediction was assessed to indicate the most likely pMoA and interaction mode. Copper and cadmium influence more than one DEB model primary parameter. Different pMoAs can result in similar model fits, and therefore it is difficult to identify pMoA only by evaluation of the goodness of fit of the model to the growth and reproduction data. Some critical discussion and ideas for model development are therefore provided.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Connecting Suborganismal Data to Bioenergetic Processes: Killifish Embryos Exposed to a Dioxin-Like Compound

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population-level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal responses that influence population dynamics. We describe a novel application of dynamic energy budget (DEB) theory in the context of a toxicity framework (adverse outcome pathways [AOPs]) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early-life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP key events to DEB processes through "damage" that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and DEB models to predict sublethal and lethal effects on young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters point to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern. Environ Toxicol Chem 2023;42:2040-2053. © 2023 Oak Ridge National Laboratory and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Using a dynamic energy budget model to investigate the physiological mode of action of lead (Pb) to Lymnaea stagnalis

Lymnaea stagnalis is a notably sensitive species for a variety of metals, including lead (Pb). However, the mechanism(s) of lead toxicity to L. stagnalis currently remain incompletely understood. Under dynamic energy budget (DEB) theory, different physiological modes of action (PMoAs) result in the emergence of distinct changes to the life histories of exposed organisms. This work aims to better understand the PMoA of lead toxicity to L. stagnalis by applying DEB modeling to previously published datasets. After calibration, the model was utilized to evaluate the relative likelihood of several PMoAs. Assuming decreased assimilation, the L. stagnalis DEB model was able to capture most, but not all, trends in experimentally observed endpoints, including growth, reproduction, and food ingestion. The weight-of-evidence suggests that decreased assimilation via a decrease in food ingestion is the most plausible PMoA for chronic lead toxicity in L. stagnalis. Collectively, our results illustrate how mechanistic modeling can create added value for conventional individual-level toxicity test data by enabling inferences about potential physiological mechanisms of toxicity.

Development of a mechanistic model for analyzing avian reproduction data for pesticide risk assessment

Mechanistic effect models are increasingly recommended as tools for refining evaluations of risk from exposure to pesticides. In the context of bird and mammal risk assessments, DEB-TKTD models have been recommended for characterizing sublethal effects at lower tiers. However, there are currently no such models. Currently, chronic, multi-generational studies are performed to characterize potential effects of pesticides on avian reproduction, but it is has not been established to what extent results from these studies can inform effect models. Here, a standard Dynamic Energy Budget (DEB) model was extended to account for the avian toxicity endpoints observed in regulatory studies. We linked this new implementation to a toxicological module to capture observed pesticide effects on reproduction via a decreased efficiency of egg production. We analysed ten reproduction studies with five different pesticides conducted with the mallard (Anas platyrhynchos) and the northern bobwhite (Colinus virginianus). The new model implementation accurately distinguished between effects on egg production from direct mechanism of toxicity and from food avoidance. Due to the specific nature of regulatory studies, model applicability for risk refinement is currently limited. We provide suggestions for next steps in model development.

Investigating Population-Level Toxicity of the Antidepressant Citalopram in Harpacticoid Copepods Using In Vivo Methods and Bioenergetics-Based Population Modeling

Recent research has revealed various lethal and sublethal effects of the selective serotonin reuptake inhibitor citalopram hydrobromide on the harpacticoid copepod Nitocra spinipes. In the present study, an individual-based model (IBM) grounded in the dynamic energy budget (DEB) theory was developed to extrapolate said effects to the population level. Using a generic DEB-IBM as a template, the model was designed to be as simple as possible, keeping model components that are outside the scope of the core DEB theory to a minimum. To test the model, a 56-day population experiment was performed at 0, 100, and 1000 μg citalopram hydrobromide L^-1 . In the experiment, the populations quickly reached a plateau in the control and at 100 μg L^-1 , which was correctly reproduced by the model and could be explained by food limitations hindering further population growth. At 1000 μg L^-1 , a clear mismatch occurred: Whereas in the experiment the population size increased beyond the supposed (food competition-induced) capacity, the model predicted a suppression of the population size. It is assumed that the IBM still misses important components addressing population density-regulating processes. Particularly crowding effects may have played an important role in the population experiment and should be further investigated to improve the model. Overall, the current DEB IBM for N. spinipes should be seen as a promising starting point for bioenergetics-based copepod population modeling, which-with further improvements-may become a valuable individual-to-population extrapolation tool in the future. Environ Toxicol Chem 2023;42:1094-1108. © 2023 SETAC.

Joint survival modelling for multiple species exposed to toxicants

In environmental risk assessment (ERA), the multitude of compounds and taxa demands cross-species extrapolation to cover the variability in sensitivity to toxicants. However, only the impact of a single compound to a single species is addressed by the general unified threshold model of survival (GUTS). The reduced GUTS is the recommended model to analyse lethal toxic effects in regulatory aquatic ERA. GUTS considers toxicokinetics and toxicodynamics. Two toxicodynamic approaches are considered: Stochastic death (SD) assumes that survival decreases with an increasing internalized amount of the toxicant. Individual tolerance (IT) assumes that individuals vary in their tolerance to toxic exposure. Existing theory suggests that the product of the threshold z_w and killing rate b_w (both SD toxicodynamic parameters) are constant across species or compounds if receptors and target sites are shared. We extend that theory and show that the shape parameter β of the loglogistic threshold distribution in IT is also constant. To verify the predicted relationships, we conducted three tests using toxicity studies for eight arthropods exposed to the insecticide flupyradifurone. We confirmed previous verifications of the relation- between SD parameters, and the newly established relation for the IT parameter β. We enhanced GUTS to jointly model survival for multiple species with shared receptors and pathways by incorporating the relations among toxicodynamic parameters described above. The joint GUTS exploits the shared parameter relations and therefore constrains parameter uncertainty for each of the separate species. Particularly for IT, the joint GUTS more precisely predicted risk to the separate species than the standard single species GUTS under environmentally realistic exposure. We suggest that joint GUTS modelling can improve cross-species extrapolation in regulatory ERA by increasing the reliability of risk estimates and reducing animal testing. Furthermore, the shared toxicodynamic response provides potential to reduce complexity of ecosystem models.

Modelling the effects of the pyrethroid insecticide cypermethrin on the life cycle of the soil dwelling annelid Enchytraeus crypticus, an original experimental design to calibrate a DEB-TKTD model

The Dynamic Energy Budget theory (DEB) enables ecotoxicologists to model the effects of chemical stressors on organism life cycles through the coupling of toxicokinetic-toxicodynamic (TK-TD) models. While good progress has been made in the application of DEB-TKTD models for aquatic organisms, applications for soil fauna are scarce, due to the lack of dedicated experimental designs suitable for collecting the required time series effect data. Enchytraeids (Annelida: Clitellata) are model organisms in soil ecology and ecotoxicology. They are recognised as indicators of biological activity in soil, and chemical stress in terrestrial ecosystems. Despite this, the application of DEB-TKTD models to investigate the impact of chemicals has not yet been tested on this family. Here we assessed the impact of the pyrethroid insecticide cypermethrin on the life cycle of Enchytraeus crypticus. We developed an original experimental design to collect the data required for the calibration of a DEB-TKTD model for this species. E. crypticus presented a slow initial growth phase that has been successfully simulated with the addition of a size-dependent food limitation for juveniles in the DEB model. The DEB-TKTD model simulations successfully agreed with the data for all endpoints and treatments over time. The highlighted physiological mode of action (pMoA) for cypermethrin was an increase of the growth energy cost. The threshold for effects on survival was estimated at 73.14 mg kg^- 1, and the threshold for effects on energy budget (i.e., sublethal effects) at 19.21 mg kg^- 1. This study demonstrates that DEB-TKTD models can be successfully applied to E. crypticus as a representative soil species, and may improve the ecological risk assessment for terrestrial ecosystems, and our mechanistic understanding of chemical effects on non-target species.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

The application and limitations of exposure multiplication factors in sublethal effect modelling

Thanks to growing interest and research in the field, toxicokinetic–toxicodynamic (TKTD) models are close to realising their potential in environmental risk assessment (ERA) of chemicals such as plant protection products. A fundamental application is to find a multiplicative scale factor which—when applied to an exposure profile—results in some specified effect relative to a control. The approach is similar to applying assessment factors to experimental results, common in regulatory frameworks. It also relies on the same core assumption: that increasing the scaling always produces more extreme effects. Unlike experimental approaches, TKTD models offer an opportunity to interrogate this assumption in a mathematically rigorous manner. For four well-known TKTD models we seek to prove that the approach guarantees a unique scale factor for any percentage effect. Somewhat surprisingly, certain model configurations may have multiple scale factors which result in the same percentage effect. These cases require a more cautious regulatory approach and generate open biological and mathematical questions. We provide examples of the violations and suggest how to deal with them. Mathematical proofs provide the strongest possible backing for TKTD modelling approaches in ERA, since the applicability of the models can be determined exactly.

Modelling the effects of variability in feeding rate on growth - a vital step for DEB-TKTD modelling

A major limitation of dietary toxicity studies on rodents is that food consumption often differs between treatments. The control treatment serves as a reference of how animals would have grown if not for the toxicant in their diet, but this comparison unavoidably conflates the effects of toxicity and feeding rate on body weight over time. A key advantage of toxicity models based on dynamic energy budget theory (DEB) is that chemical stress and food consumption are separate model inputs, so their effects on growth rate can be separated. To reduce data requirements, DEB convention is to derive a simplified feeding input, f, from food availability; its value ranges from zero (starvation) to one (food available ad libitum). Observed food consumption in dietary toxicity studies shows that, even in the control treatment, rats limit their food consumption, contradicting DEB assumptions regarding feeding rate. Relatively little work has focused on addressing this mismatch, but accurately modelling the effects of food intake on growth rate is essential for the effects of toxicity to be isolated. This can provide greater insight into the results of chronic toxicity studies and allows accurate extrapolation of toxic effects from laboratory data. Here we trial a new method for calculating f, based on the observed relationships between food consumption and body size in laboratory rats. We compare model results with those of the conventional DEB method and a previous effort to calculate f using observed food consumption data. Our results showed that the new method improved model accuracy while modelled reserve dynamics closely followed observed body fat percentage over time. The new method assumes that digestive efficiency increases with body size_. Verifying this relationship through data collection would strengthen the basis of DEB theory and support the case for its use in ecological risk assessment.

Considerations for using reproduction data in toxicokinetic-toxicodynamic modeling

Toxicokinetic-toxicodynamic (TKTD) modeling is essential to make sense of the time dependence of toxic effects, and to interpret and predict consequences of time-varying exposure. These advantages have been recognized in the regulatory arena, especially for environmental risk assessment of pesticides, where time-varying exposure is the norm. We critically evaluate the link between the modeled variables in TKTD models and the observations from laboratory ecotoxicity tests. For the endpoint reproduction, this link is far from trivial. The relevant TKTD models for sublethal effects are based on dynamic energy budget (DEB) theory, which specifies a continuous investment flux into reproduction. In contrast, experimental tests score egg or offspring release by the mother. The link between model and data is particularly troublesome when a species reproduces in discrete clutches and, even more so, when eggs are incubated in the mother's brood pouch (and release of neonates is scored in the test). This situation is quite common among aquatic invertebrates (e.g., cladocerans, amphipods, mysids), including many popular test species. In this discussion paper, we treat these and other issues with reproduction data, reflect on their potential impact on DEB-TKTD analysis, and provide preliminary recommendations to correct them. Both modelers and users of model results need to be aware of these complications, as ignoring them could easily lead to unnecessary failure of DEB-TKTD models during calibration, or when validating them against independent data for other exposure scenarios. Integr Environ Assess Manag 2022;18:479-487. © 2021 SETAC.

Assessing Stress Response in Lizards from Agroecosystems with Different Management Practices

Despite the importance of reptiles in agroecosystems, little is known about the effects of agricultural intensification and pesticide use on these animals. We compared antioxidant and haematological biomarkers in the wild Italian wall lizards Podarcis siculus from three olive groves representing a gradient of management intensity. Lizards from the conventional grove showed induced antioxidant defences relative to those from the organic field. However, this induction did not avoid the occurrence of oxidative stress in males from intensively managed olive groves, who showed TBARS levels 58%-133% higher than males from the other sites. Haematological responses also suggested increased stress in females from the intensively managed olive groves, with a heterophil-to-lymphocyte ratio 5.3 to 14.8-fold higher than in the other sites. The observed stress responses of lizards along the studied gradient of agricultural management suggest their potential usefulness as non-destructive biomarkers to environmental stressors associated with agricultural intensification.

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.

Evaluation of the combined effect of elevated temperature and cadmium toxicity on Daphnia magna using a simplified DEBtox model

Thermal discharge and heatwaves under climate change may increase water temperature. In this study, the individual and combined effect of elevated temperature and cadmium (Cd) toxicity on somatic growth and reproduction of Daphnia magna was evaluated using a simplified dynamic energy budget model (DEBtox). The model predicted that the maximum body length (L_m) would be shorter (3.705 mm) at an elevated temperature of 25 °C than at 20 °C (3.974 mm), whereas the maximum reproduction rate (R˙_m) would be higher at 25 °C (5.735) than at 20 °C (5.591). The somatic growth and reproduction of D. magna were significantly (p < 0.05) reduced with increasing Cd concentrations, and the reduction was greater at 25 than at 20 °C. Potentiation of Cd toxicity by elevated temperature was correctly simulated by assuming four toxicological modes of action influencing assimilation, somatic maintenance and growth, and reproduction. Overall, the population growth rate of D. magna was expected to decrease linearly with increasing Cd concentrations, and the decrease was expected to be higher at 25 than at 20 °C. These findings suggest a significant ecological risk of toxic metals at elevated temperature, with a mechanistic interpretation of the potentiation effect using a DEBtox modeling approach.

Exposure to low environmental copper concentrations does not affect survival and development in Atlantic cod (Gadus morhua) early life stages

In this study we investigated potential impacts of Cu exposure at low, environmentally relevant, concentrations on early live stages of Atlantic cod (Gadus morhua). Cod embryos and larvae were exposed to 0.5 μg/L (low), 2 μg/L (medium), and 6 μg/L (high) Cu from 4 to 17 days post fertilisation (dpf). Hatching success, mortality, oxygen consumption, biometric traits, and malformations were determined. A dynamic energy budget (DEB) model was applied to identify potential impacts on bioenergetics. A positive correlation was found between Cu exposure concentrations and Cu body burden in eggs, but not in larvae. The tested concentrations did not increase mortality in neither embryos nor larvae, or larvae deformations. Further, the DEB model did not indicate effects of the tested Cu concentrations.

(Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future

Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects of chemicals on aquatic species and ecosystems. This is primarily because of the increasing number of (unknown) chemical stressors and mixture effects present in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal, population, or community level. We performed a literature search to obtain a state-of-the-art overview of ecotoxicological tests available for assessing impacts of chemicals to aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level, and 78 tests at the population- community- and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests at the community- and ecosystem-level were almost missing for organisms other than microorganisms and algae. In addition, we provide an overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemical stressors to aquatic ecosystems.

Effects of marine mine tailing exposure on the development, growth, and lipid accumulation in Calanus finmarchicus

Marine tailing disposal (MTD) is sometimes practiced as an alternative to traditional mine tailing deposition on land. Environmental challenges connected to MTD include spreading of fine particulate matter in the water column and the potential release of metals and processing chemicals. This study investigated if tailing exposure affects the marine copepod Calanus finmarchicus, and whether effects are related to exposure to mineral particles or the presence of metals and/or processing chemicals in the tailings. We investigated the impacts of three different tailing compositions: calcium carbonate particles with and without processing chemicals and fine-grained tailings from a copper ore. Early life stages of C. finmarchicus were exposed over several developmental stages to low and high suspension concentrations for 15 days, and their development, oxygen consumption and biometry determined. The data was fitted in a dynamic energy budget (DEB) model to determine mechanisms underlying responses and to understand the primary modes of action related to mine tailing exposure. Results show that copepods exposed to tailings generally exhibited slower growth and accumulated less lipids. The presence of metals and processing chemicals did not influence these responses, suggesting that uptake of mineral particles was responsible for the observed effects. This was further supported by the applied DEB model, confirming that ingestion of tailing particles while feeding can result in less energy being available for growth and development.

One and multi-compartments toxico-kinetic modeling to understand metals' organotropism and fate in Gammarus fossarum

The use of freshwater invertebrates for biomonitoring has been increasing for several decades, but little is known about relations between external exposure concentration of metals and their biodistribution among different tissues. One and multi-compartments toxicokinetic (TK) models are powerful tools to formalize and predict how a contaminant is bioaccumulated. The aim of this study is to develop modeling approaches to improve knowledge on dynamic of accumulation and fate of Cd and Hg in gammarid's organs. Gammarids were exposed to dissolved metals (11.1 ± 1.2 µg.L^-1 of Cd or 0.27 ± 0.13 µg.L^-1 of Hg) before a depuration phase. At each sampling days, their organs (caeca, cephalon, intestine and remaining tissues) were separated by dissection before analyses. Results allowed us to determine that i) G.fossarum takes up Cd as efficiently as the mussel M.galloprovincialis, but eliminates it more rapidly, ii) organs which accumulate and depurate the most, in terms of concentrations, are caeca and intestine for both metals; iii) the one-compartment TK models is the most relevant for Hg, while the multi-compartments TK model allows a better fit to Cd data, demonstrating dynamic transfer of Cd among organs.

Role of Toxicokinetic and Toxicodynamic Parameters in Explaining the Sensitivity of Zebrafish Larvae to Four Metals

Given the persistence and toxic potencies of metal contaminants in ecosystems, animals, and human beings, they are considered to be hazardous global pollutants. While the lethality of metal toxicities (e.g., LC₅₀) can significantly vary, even within the same species, the underlying mechanisms are less well-understood. In this study, we developed a subcellular two-compartment toxicokinetic-toxicodynamic (TK-TD) model for zebrafish larvae when exposed to four metals (cadmium, lead, copper, and zinc) to reveal whether differences in metal toxicity (LC₅₀ values) were dominated by the TK or TD processes. Results showed that the subcellular TK and TD parameters of the four metals were significantly different, and the bioconcentration factor (BCF) value of copper was higher than those of the other metals. We also found that the TD parameter internal threshold concentration (C_IT) was significantly positively correlated to the LC₅₀ values (R² = 0.7), suggesting a dominant role of TD processes in metal toxicity. Furthermore, the combined parameter C_IT/BCF for a metal-sensitive fraction (BCF_MSF), which linked exposure to effects through the TK-TD approach, explained up to 89% of the variation in toxicity to the four metals. The present study suggests that the observed variation in toxicity of these four metals was mainly determined by TD processes but that TK processes should not be ignored, especially for copper.

What Is on the Outside Matters-Surface Charge and Dissolve Organic Matter Association Affect the Toxicity and Physiological Mode of Action of Polystyrene Nanoplastics to C. elegans

To better understand nanoplastic effects, the potential for surface functionalization and dissolve organic matter eco-corona formation to modify the mechanisms of action and toxicity of different nanoplastics needs to be established. Here, we assess how different surface charges modifying functionalization (postive (+ve) aminated; neutral unfunctionalized; negative (-ve) carboxylated) altered the toxicity of 50 and 60 nm polystyrene nanoplastics to the nematode Caenorhabditis elegans. The potency for effects on survival, growth, and reproduction reduced in the order +ve aminated > neutral unfunctionalized ≫ -ve carboxylated with toxicity >60-fold higher for the +ve than -ve charged forms. Toxicokinetic-toxicodynamic modeling (DEBtox) showed that the charge-related potency was primarily linked to differences in effect thresholds and dose-associated damage parameters, rather than to toxicokinetic parameters. This suggests that surface functionalization may change the nature of nanoplastic interactions with membrane and organelles leading to variations in toxicity. Eco-corona formation reduced the toxicity of all nanoplastics indicating that organic molecule associations may passivate surfaces. Between particles, eco-corona interactions resulting in more equivalent effects; however, even despite these changes, the order of potency of the charged forms was retained. These results have important implications for the development of future grouping approaches.

Robust Likelihood-Based Approach for Automated Optimization and Uncertainty Analysis of Toxicokinetic-Toxicodynamic Models

Toxicokinetic-toxicodynamic (TKTD) models offer a mechanistic understanding of individual-level toxicity over time and allow for meaningful extrapolations from laboratory tests to exposure conditions in the field. Thereby, they hold great potential for ecotoxicological studies, both in a regulatory context as well as for basic research. In contrast to mechanistic effect models at higher levels of biological organization, TKTD models can be, and generally are, parameterized by fitting them to data (results from toxicity tests). Fitting models comes with a range of statistical and numerical challenges, which may hamper the application of TKTD models in a practical setting. Especially in the context of environmental risk assessment, there is a need for robust and user-friendly software tools to automatically extract the best-fitting model parameters and quantify their uncertainty from any data set. The study presents a general outline for TKTD model analysis, rooted in likelihood-based ("frequentist") inference. The general outline is followed by a presentation of the specific algorithm that has been implemented into software for the robust and automated analysis of toxicity data for survival. However, the presented approach is more broadly applicable to low-dimensional problems. Integr Environ Assess Manag 2021;17:388-397. © 2020 SETAC.

Predicting Mixture Effects over Time with Toxicokinetic-Toxicodynamic Models (GUTS): Assumptions, Experimental Testing, and Predictive Power

Current methods to assess the impact of chemical mixtures on organisms ignore the temporal dimension. The General Unified Threshold model for Survival (GUTS) provides a framework for deriving toxicokinetic-toxicodynamic (TKTD) models, which account for effects of toxicant exposure on survival in time. Starting from the classic assumptions of independent action and concentration addition, we derive equations for the GUTS reduced (GUTS-RED) model corresponding to these mixture toxicity concepts and go on to demonstrate their application. Using experimental binary mixture studies with Enchytraeus crypticus and previously published data for Daphnia magna and Apis mellifera, we assessed the predictive power of the extended GUTS-RED framework for mixture assessment. The extended models accurately predicted the mixture effect. The GUTS parameters on single exposure data, mixture model calibration, and predictive power analyses on mixture exposure data offer novel diagnostic tools to inform on the chemical mode of action, specifically whether a similar or dissimilar form of damage is caused by mixture components. Finally, observed deviations from model predictions can identify interactions, e.g., synergism or antagonism, between chemicals in the mixture, which are not accounted for by the models. TKTD models, such as GUTS-RED, thus offer a framework to implement new mechanistic knowledge in mixture hazard assessments.

Sublethal effect modelling for environmental risk assessment of chemicals: Problem definition, model variants, application and challenges

Bioenergetic models, and specifically dynamic energy budget (DEB) theory, are gathering a great deal of interest as a tool to predict the effects of realistically variable exposure to toxicants over time on an individual animal. Here we use aquatic ecological risk assessment (ERA) as the context for a review of the different model variants within DEB and the closely related DEBkiss theory (incl. reserves, ageing, size & maturity, starvation). We propose a coherent and unifying naming scheme for all current major DEB variants, explore the implications of each model's underlying assumptions in terms of its capability and complexity and analyse differences between the models (endpoints, mathematical differences, physiological modes of action). The results imply a hierarchy of model complexity which could be used to guide the implementation of simplified model variants. We provide a decision tree to support matching the simplest suitable model to a given research or regulatory question. We detail which new insights can be gained by using DEB in toxicokinetic-toxicodynamic modelling, both generally and for the specific example of ERA, and highlight open questions. Specifically, we outline a moving time window approach to assess time-variable exposure concentrations and discuss how to account for cross-generational exposure. Where possible, we suggest valuable topics for experimental and theoretical research.

Modeling Sublethal Effects of Chemicals: Application of a Simplified Dynamic Energy Budget Model to Standard Ecotoxicity Data

To assess ecological risks from chemical exposure, we need tools to extrapolate from the sublethal effects observed in the laboratory under constant exposure to realistic time-varying exposures. Dynamic energy budget (DEB) theory offers a mechanistic modeling approach to describe the entire life history of a single organism and the effects of toxicant exposure. We use a simplified model, which can be wholly calibrated from standard chronic bioassay data. Case studies on standard test organisms (Americamysis bahia and Pimephales promelas) are presented to demonstrate the calibration procedure, and for the second case, data are available to pseudovalidate model performance. We use these results to highlight gaps and shortcomings in the current state of the science, and we discuss how these can be overcome to maximize the potential of DEB theory in ecological risk assessment.