Unified Threshold Model Of Survival Research Articles

The Importance of Including Variable Exposure Concentrations When Assessing Toxicity of Sediment-Associated Pharmaceuticals to an Amphipod.

Pharmaceuticals have been classified as an environmental concern due to their increasing consumption globally and potential environmental impact. We examined the toxicity of sediment-associated diclofenac and citalopram administered as both single compounds and in a mixture to the sediment-living amphipod Corophium volutator. This laboratory-based study addressed the following research questions: (1) What is the toxicity of sediment-associated diclofenac and citalopram to C. volutator? (2) Can the mixture effect be described with either of the two mixture models: concentration addition (CA) or independent action (IA)? (3) What is the importance of the choice of (i) exposure measure (start concentration, time-weighted average [TWA], full exposure profile) and (ii) effect model (concentration-response vs. the toxicokinetic-toxicodynamic model general unified threshold model for survival in its reduced form [GUTS-RED]) for the derived effect concentration values? Diclofenac was more toxic than citalopram to C. volutator as a single compound (10-day exposure). Diclofenac exposure to C. volutator provided median lethal concentrations (LC50s) within the same range (11 µg g-1 dry wt sediment) using concentration-response based on TWA and both GUTS-RED models. However, concentration-response based on measured start concentrations provided an approximately 90% higher LC50 (21.6 ± 2.0 µg g-1 dry wt sediment). For citalopram, concentration-response parameters were similar regardless of model or concentration used (LC50 85-97 µg g-1 dry wt sediment), however, GUTS-RED with the assumption of individual tolerance resulted in a lower LC50 (64.9 [55.3-74.8] µg g-1 dry wt sediment). The mixture of diclofenac and citalopram followed the CA quite closely, whereas the result was synergistic when using the IA prediction. In summary, concentration-response based on TWA and GUTS-RED provided similar and reasonably good fits compared to the data set. The implications are that GUTS-RED will provide a more flexible model, which, in principle, can extend beyond the experimental period and make predictions based on variable exposure profiles (toxicity at different time frames and at different variable exposure scenarios) compared to concentration-response, which provides contaminant toxicity at one point in time. Environ Toxicol Chem 2024;00:1-11. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Identifying and Predicting Delayed Mortality with Toxicokinetic-Toxicodynamic Models.

The prevalence of standardized toxicity testing in ecotoxicology has largely obscured the notion that toxicity is a function of time as well. The necessity of considering time is vividly demonstrated by observations of delayed mortality, that is, deaths continue to occur even when animals are no longer exposed to a toxicant. In this contribution, I explore to what extent toxicokinetic-toxicodynamic (TKTD) models from the framework of the General Unified Threshold model for Survival (GUTS) can capture delayed mortality, and to what extent this phenomenon can be predicted from short-term standard tests. I use a previously published data set for fluoroquinolones in Daphnia magna that shows strongly delayed mortality (using immobilization as a proxy for death). The model analysis shows that the GUTS stochastic death models can capture delayed mortality in the complete data set with a long recovery phase, but that the delayed effects would not have been predicted from a 2-day standard test. The study underlines the limited information content of standard acute test designs. Toxicokinetic-toxicodynamic modeling offers a handle on the time aspects of toxicity but cannot always be relied on to provide accurate extrapolations based on severely limited standard tests. The phenomenon of delayed toxicity requires more structured study to clarify its prevalence and impact; I discuss several avenues for further investigation. Environ Toxicol Chem 2024;43:1030-1035. © 2024 SETAC.

Mechanistic analysis of the sub chronic toxicity of La and Gd in Daphnia magna based on TKTD modelling and synchrotron X-ray fluorescence imaging.

The release of lanthanides (Ln) into the environment has increased in recent decades due to their expanding applications in society. Studying their toxicity in aquatic ecosystems is urgent and challenging, with contradictory evidence presented in the literature. This study compared the biodistribution of La and Gd in Daphnia magna exposed to sub-chronic conditions and developed the first Toxicokinetic-Toxicodynamic (TKTD) model for these lanthanides with this model crustacean. D. magna were initially exposed for 7 days to concentrations close to the LC50 of La (2.10 mg L-1) and Gd (1.70 mg L−1). After exposure, half of the live daphnids were introduced in a clean media to allow depuration over 24 h, while the other organisms were directly prepared for synchrotron imaging measurements. Synchrotron X-ray fluorescence analysis revealed that metal distribution in the organisms was similar for both La and Gd, predominantly localized in the intestinal tract, even after the depuration process. These results indicate that ingested metal can adversely affect organisms under sub-chronic exposure conditions, highlighting the importance of using nominal concentrations as a more suitable indicator of metal bioavailability for risk assessment. The General Unified Threshold Model of Survival (GUTS) TKTD framework, in its reduced form (GUTS-RED), was developed for La and Gd using dissolved and nominal concentrations. D. magna were exposed for 7 days to concentrations from 0.5 to 5 mg L−1 of La or Gd and mortality monitored daily. The mechanistic model revealed a faster toxicokinetics for La than Gd and a higher toxicity for Gd than La in the organism. This study confirmed, despite similar chemical properties, the variation in both toxicity and toxicokinetics between these two metals.

Mortality Pattern of Poecilus cupreus Beetles after Repeated Topical Exposure to Insecticide─Stochastic Death or Individual Tolerance?

The mortality of organisms exposed to toxicants has been attributed to either stochastic processes or individual tolerance (IT), leading to the stochastic death (SD) and IT models. While the IT model follows the principles of natural selection, the relevance of the SD model has been debated. To clarify why the idea of stochastic mortality has found its way into ecotoxicology, we investigated the mortality of Poecilus cupreus (Linnaeus, 1758) beetles from pesticide-treated oilseed rape (OSR) fields and unsprayed meadows, subjected to repeated insecticide treatments. We analyzed the mortality with the Kaplan-Meier estimator and general unified threshold model for survival (GUTS), which integrates SD and IT assumptions. The beetles were exposed three times, ca. monthly, to the same dose of Proteus 110 OD insecticide containing thiacloprid and deltamethrin, commonly used in the OSR fields. Kaplan-Meier analysis showed that the mortality of beetles from meadows was much higher after the first treatment than after the next two, indicating the IT model. Beetles from the OSR displayed approximately constant mortality after the first and second treatments, consistent with the SD model. GUTS analysis did not conclusively identify the better model, with the IT being marginally better for beetles from meadows and the SD better for beetles from OSR fields.

Generation of oxidative stress in freshwater oligochaete Tubifex tubifex due to exposure to aniline: time and concentration dependent toxicity assessment

ABSTRACT Our current study examines the significant impact of aniline on the fish feed freshwater benthic annelid, Tubifex tubifex, including mortality, changes in total protein concentration and antioxidant enzyme activity (catalase, superoxide dismutase, glutathione-s transferase and glutathione peroxidase), as well as the generation of oxidative stress (by assessing malondialdehyde concentration). The 96-hour LC50 value of aniline is 276.940 mg/L. The General Unified Threshold Model of Survival (GUTS) was used to validate the survival rate pattern of the test organism in response to aniline at the acute level, with the GUTS-SD model better correctly predicting the expected course of population death. During long-term bioassay antioxidant enzymes activities (superoxide dismutase, glutathione-s transferase and glutathione peroxidase) and oxidative stress biomarkers concentration (malondialdehyde concentration) is substantially enhanced while protein concentration and Catalase activity are markedly reduced during the bioassay. The stress and detrimental effects of aniline on Tubifex tubifex were examined in the current study, taking into account all biomarkers, by utilising the Integrated Biomarker Response index. The results show that exposure to toxicants like aniline has a detrimental effect on Tubifex tubifex's survival rate and general health.

Toxicokinetic-Toxicodynamic Model to Assess Thermal Stress.

Temperature is a crucial environmental factor affecting the distribution and performance of ectothermic organisms. This study introduces a new temperature damage model to interpret their thermal stress. Inspired by the ecotoxicological damage model in the General Unified Threshold model for Survival (GUTS) framework, the temperature damage model assumes that damage depends on the balance between temperature-dependent accumulation and constant repair. Mortality due to temperature stress is driven by the damage level exceeding a threshold. Model calibration showed a good agreement with the measured survival of Gammarus pulex exposed to different constant temperatures. Further, model simulations, including constant temperatures, daily temperature fluctuations, and heatwaves, demonstrated the model's ability to predict temperature effects for various environmental scenarios. With this, the present study contributes to the mechanistic understanding of temperature as a single stressor while facilitating the incorporation of temperature as an additional stressor alongside chemicals in mechanistic multistressor effect models.

A Toxicokinetic-Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data.

Toxicokinetic-toxicodynamic (TKTD) models simulate organismal uptake and elimination of a substance (TK) and its effects on the organism (TD). The Reduced General Unified Threshold model of Survival (GUTS-RED) is a TKTD modeling framework that is well established for aquatic risk assessment to simulate effects on survival. The TKTD models are applied in three steps: parameterization based on experimental data (calibration), comparing predictions with independent data (validation), and prediction of endpoints under environmental scenarios. Despite a clear understanding of the sensitivity of GUTS-RED predictions to the model parameters, the influence of the input data on the quality of GUTS-RED calibration and validation has not been systematically explored. We analyzed the performance of GUTS-RED calibration and validation based on a unique, comprehensive data set, covering different types of substances, exposure patterns, and aquatic animal species taxa that are regularly used for risk assessment of plant protection products. We developed a software code to automatically calibrate and validate GUTS-RED against survival measurements from 59 toxicity tests and to calculate selected model evaluation metrics. To assess whether specific survival data sets were better suited for calibration or validation, we applied a design in which all possible combinations of studies for the same species-substance combination are used for calibration and validation. We found that uncertainty of calibrated parameters was lower when the full range of effects (i.e., from high survival to high mortality) was covered by input data. Increasing the number of toxicity studies used for calibration further decreased parameter uncertainty. Including data from both acute and chronic studies as well as studies under pulsed and constant exposure in model calibrations improved model predictions on different types of validation data. Using our results, we derived a workflow, including recommendations for the sequence of modeling steps from the selection of input data to a final judgment on the suitability of GUTS-RED for the data set. Environ Toxicol Chem 2024;43:197-210. © 2023 Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

High sensitivity to dietary imidacloprid exposure in early life stages of Folsomia quadrioculata (Collembola) populations from contrasting climates

Survival of early life stages is critical for population growth. Understanding the vulnerability of these sensitive stages can therefore improve ecological risk predictions. The globally-used neonicotinoid insecticide imidacloprid does not degrade easily in soil and occurs at concentrations potentially toxic to non-target soil organisms, such as Collembola. Here, we studied the effects of dietary exposure to imidacloprid on the survival of juveniles in an arctic and a temperate population of Folsomia quadrioculata (Collembola), a commonly-occurring litter-dwelling species in the Northern Hemisphere. The exposure lasted from <24 h to 30 days since hatching at 15 °C. We assessed whether (1) the arctic population of the test species with faster development rates could be more vulnerable than the temperate population, (2) cumulative mortality could increase substantially with exposure time, and (3) the mortality risk experienced during the juvenile stage could be greater than that experienced by the adults. We found a strong concentration-dependent decline in survival in both populations, with small but significantly different LC50s, despite large differences in multiple life-history traits. Applying a General Unified Threshold model for Survival (GUTS) showed a low threshold for effects, slow damage dynamics, a 6–11-fold decrease in LC50 from 14 to 30 days of exposure, and saturation of damage at the three highest concentrations. In addition, exposure starting soon after hatching caused much more mortality than that starting in the adult stages. Our findings suggest that toxicity tests not emphasizing the neonate stages or not lasting long enough can underestimate the implications for populations of naturally abundant non-target organisms.

Behavioral toxicity, histopathological alterations and oxidative stress in Tubifex tubifex exposed to aromatic carboxylic acids- acetic acid and benzoic acid: A comparative time-dependent toxicity assessment

This study evaluated Acetic acid (AA) and Benzoic acid's (BA) acute and sublethal toxicity by observing mortality, behavioral responses, and changes in the levels of oxidative stress enzymes in Tubifex tubifex. Exposure-induced changes in antioxidant activity (Catalase, Superoxide dismutase), oxidative stress (Malondialdehyde concentrations), and histopathological alterations in the tubificid worms were also noted across exposure intervals. The 96 h LC50 values of AA and BA to T. tubifex were 74.99 and 37.15 mg/l, respectively. Severity in behavioral alterations (including increased mucus production, wrinkling, and reduction in clumping) and autotomy showed concentration-dependent trends for both toxicants. Although histopathological effects also showed marked degeneration in the alimentary and integumentary systems in highest exposure groups (worms exposed to 14.99 mg/l for AA and 7.42 mg/l for BA) for both toxicants. Antioxidant enzymes (catalase and superoxide dismutase) also showed a marked increase of up to 8-fold and 10-fold for the highest exposure group of AA and BA respectively. While species sensitivity distribution analysis revealed T. tubifex as most sensitive to AA and BA compared to other freshwater vertebrates and invertebrates, General Unified Threshold model of Survival (GUTS) predicted individual tolerance effects (GUTS-IT), with slower potential for toxicodynamic recovery, as a more likely pathway for population mortality. Study findings demonstrate BA with greater potential for ecological effects compared to AA within 24 h of exposure. Furthermore, ecological risks to critical detritus feeders like T. tubifex may have severe implications for ecosystem services and nutrient availability within freshwater habitats.

Hb or not hb - When and why accounting for background mortality in toxicological survival models matters?

Decisions in Environmental Risk Assessment (ERA) about impacts of chemical compounds on different species are based on critical effect indicators such as the 50% lethal concentration (LC50). Regulatory documents recommend concentration-response (or concentration-effect) model fitting on standard toxicity test data to get LC50 values. However, toxicokinetic-toxicodynamic (TKTD) models proved their efficiency to better exploit toxicity test data, at Tier-2 but also at Tier-1, delivering time-independent indicators. In particular, LC50 values can be obtained from the reduced General Unified Threshold model of Survival (GUTS-RED) with both variants, Stochastic Death and Individual Tolerance, that include parameter hb, the background mortality. Estimating hb during the fitting process or not depends on studies and fitting habits, while it may strongly influence the other GUTS-RED parameters, and consequently the LC50 estimate. We hypothesized that estimating hb from all data in all replicates over time should provide more precise LC50 estimates. We then explored how estimating hb impacted: (i) GUTS-RED model parameters; (ii) goodness-of-fit criteria (fitting plot, posterior predictive check, parameter correlations); (iii) LC50 accuracy and precision. We finally show that estimating hb does not impact the LC50 precision while providing more accurate and precise GUTS parameter estimates. Hence, estimating hb would lead to a more protective ERA.

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 zw and killing rate bw (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.

Explicit Consideration of Temperature Improves Predictions of Toxicokinetic-Toxicodynamic Models for Flupyradifurone and Imidacloprid in Gammarus pulex.

In the face of global climate change, where temperature fluctuations and the frequency of extreme weather events are increasing, it is needed to evaluate the impact of temperature on the ecological risk assessment of chemicals. Current state-of-the-art mechanistic effect models, such as toxicokinetic-toxicodynamic (TK-TD) models, often do not explicitly consider temperature as a modulating factor. This study implemented the effect of temperature in a widely used modeling framework, the General Unified Threshold model for Survival (GUTS). We tested the model using data from toxicokinetic and toxicity experiments with Gammarus pulex exposed to the insecticides imidacloprid and flupyradifurone. The experiments revealed increased TK rates with increasing temperature and increased toxicity under chronic exposures. Using the widely used Arrhenius equation, we could include the temperature influence into the modeling. By further testing of different model approaches, differences in the temperature scaling of TK and TD model parameters could be identified, urging further investigations of the underlying mechanisms. Finally, our results show that predictions of TK-TD models improve if we include the toxicity modulating effect of temperature explicitly.

Behavioral and physiological toxicity thresholds of a freshwater vertebrate (Heteropneustes fossilis) and invertebrate (Branchiura sowerbyi), exposed to zinc oxide nanoparticles (nZnO): A General Unified Threshold model of Survival (GUTS)

The toxic effects of Zinc oxide nanoparticles (nZnO) on Branchiura sowerbyi and Heteropneustes fossilis, was assessed in a 96-hour acute exposure regime using behavioral (including loss-of balance and clumping tendencies) and physiological (mucus secretion and oxygen consumption) endpoints. While the relationship between behavioral, physiological biomarkers, and exposure concentrations was assessed using correlation analysis, nZnO toxicity was further predicted using the General Unified Threshold model for Survival (GUTS). The time-dependent lethal limits for acute nZnO toxicity (LC50) on B. sowerbyi were estimated to be 0.668, 0.588, 0.448, and 0.400 mg/l, respectively, at 24, 48, 72, and 96 h whereas for H. fossilis the LC50 values are 0.954, 0.905, 0.874 and 0.838 mg/l. Threshold effect values i.e., LOEC (Lowest Observed Effect Concentration), NOEC (No Observed Effect Concentration), and MATC (Maximum Acceptable Toxicant Concentration) threshold effect values at 96 h were higher for fish compared to the oligochaete. For B. sowerbyi, the GUTS-SD (stochastic death) model is a better predictor of nanoparticle exposure effects compared to the GUTS-IT (individual tolerance) model, however in the case of H. fossilis, the reverse pattern was observed. Oxygen consumption rate was negatively correlated to mortality under acute exposure duration. The strong negative correlation between mortality and oxygen consumption strongly suggests a metabolic-toxicity pathway for nZnO exposure effects. The higher toxicity threshold values i.e., LOEC, NOEC, and MATC for fish compared to the oligochaete invertebrate indicates greater risks for invertebrates compared to vertebrates, with resultant implications for local habitat trophic relationships.

BeeGUTS-A Toxicokinetic-Toxicodynamic Model for the Interpretation and Integration of Acute and Chronic Honey Bee Tests.

Understanding the survival of honey bees after pesticide exposure is key for environmental risk assessment. Currently, effects on adult honey bees are assessed by Organisation for Economic Co‐operation and Development standardized guidelines, such as the acute and chronic oral exposure and acute contact exposure tests. The three different tests are interpreted individually, without consideration that the same compound is investigated in the same species, which should allow for an integrative assessment. In the present study we developed, calibrated, and validated a toxicokinetic–toxicodynamic model with 17 existing data sets on acute and chronic effects for honey bees. The model is based on the generalized unified threshold model for survival (GUTS), which is able to integrate the different exposure regimes, taking into account the physiology of the honey bee: the BeeGUTS model. The model is able to accurately describe the effects over time for all three exposure routes combined within one consistent framework. The model can also be used as a validity check for toxicity values used in honey bee risk assessment and to conduct effect assessments for real‐life exposure scenarios. This new integrative approach, moving from single‐point estimates of toxicity and exposure to a holistic link between exposure and effect, will allow for a higher confidence of honey bee toxicity assessment in the future. Environ Toxicol Chem 2022;41:2193–2201. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

How to analyse and account for interactions in mixture toxicity with toxicokinetic-toxicodynamic models

The assessment of chemical mixture toxicity is one of the major challenges in ecotoxicology. Chemicals can interact, leading to more or less effects than expected, commonly named synergism and antagonism respectively. The classic ad hoc approach for the assessment of mixture effects is based on dose-response curves at a single time point, and is limited to identifying a mixture interaction but cannot provide predictions for untested exposure durations, nor for scenarios where exposure varies in time. We here propose a new approach using toxicokinetic-toxicodynamic modelling: The General Unified Threshold model of Survival (GUTS) framework, recently extended for mixture toxicity assessment. We designed a dedicated mechanistic interaction module coupled with the GUTS mixture model to i) identify interactions, ii) test hypotheses to identify which chemical is likely responsible for the interaction, and finally iii) simulate and predict the effect of synergistic and antagonistic mixtures. We tested the modelling approach experimentally with two species (Enchytraeus crypticus and Mamestra brassicae) exposed to different potentially synergistic mixtures (composed of: prochloraz, imidacloprid, cypermethrin, azoxystrobin, chlorothalonil, and chlorpyrifos). Furthermore, we also tested the model with previously published experimental data on two other species (Bombus terrestris and Daphnia magna) exposed to pesticide mixtures (clothianidin, propiconazole, dimethoate, imidacloprid and thiacloprid) found to be synergistic or antagonistic with the classic approach. The results showed an accurate simulation of synergistic and antagonistic effects for the different tested species and mixtures. This modelling approach can identify interactions accounting for the entire time of exposure, and not only at one time point as in the classic approach, and provides predictions of the mixture effect for untested mixture exposure scenarios, including those with time-variable mixture composition.

Integrating Bioavailability of Metals in Fish Population Models.

Population models are increasingly being used to extrapolate individual-level effects of chemicals, including metals, to population-level effects. For metals, it is also important to take into account their bioavailability to correctly predict metal toxicity in natural waters. However, to our knowledge, no models exist that integrate metal bioavailability into population modeling. Therefore, our main aims were to 1) incorporate the bioavailability of copper (Cu) and zinc (Zn) into an individual-based model (IBM) of rainbow trout (Oncorhynchus mykiss), and 2) predict how survival-time concentration data translate to population-level effects. For each test water, reduced versions of the general unified threshold model of survival (GUTS-RED) were calibrated using the complete survival-time concentration data. The GUTS-RED individual tolerance (IT) showed the best fit in the different test waters. Little variation between the different test waters was found for 2 GUTS-RED-IT parameters. The GUTS-RED-IT parameter "median of distribution of thresholds" (mw ) showed a strong positive relation with the Ca2+ , Mg2+ , Na+ , and H+ ion activities. Therefore, mw formed the base of the calibrated GUTS bioavailability model (GUTS-BLM), which predicted 30-d x% lethal concentration (LCx) values within a 2-fold error. The GUTS-BLM was combined with an IBM, inSTREAM-Gen, into a GUTS-BLM-IBM. Assuming that juvenile survival was the only effect of Cu and Zn exposure, population-level effect concentrations were predicted to be 1.3 to 6.2 times higher than 30-d laboratory LCx values, with the larger differences being associated with higher interindividual variation of metal sensitivity. The proposed GUTS-BLM-IBM model can provide insight into metal bioavailability and effects at the population level and could be further improved by incorporating sublethal effects of Cu and Zn. Environ Toxicol Chem 2021;40:2764-2780. © 2021 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.

Development and Validation of a Mixture Toxicity Implementation in the Dynamic Energy Budget-Individual-Based Model: Effects of Copper and Zinc on Daphnia magna Populations.

Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (DEBtox) and the general unified threshold model for survival (GUTS) are well-established theoretical frameworks that describe sublethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long-term effects on populations. We used DEBtox and GUTS in an individual-based model (IBM) framework to predict both single and combined effects of copper and zinc on Daphnia magna populations. The model was calibrated based on standard chronic toxicity test results with the single substances. A mixture toxicity implementation based on the general independent action model for mixtures was developed and validated with data from a population experiment with copper and zinc mixtures. Population-level effects of exposure to individual metals were accurately predicted by DEB-IBM. The DEB-IBM framework also allowed us to identify the potential mechanisms underlying these observations. Under independent action the DEB-IBM was able to predict the population dynamics observed in populations exposed to the single metals and their mixtures (R2 > 65% in all treatments). Our modeling shows that it is possible to extrapolate from single-substance effects at the individual level to mixture toxicity effects at the population level, without the need for mixture toxicity data at the individual level from standard mixture toxicity tests. The application of such modeling techniques can increase the ecological realism in risk assessment. Environ Toxicol Chem 2021;40:513-527. © 2020 SETAC.

Improving Risk Assessment by Predicting the Survival of Field Gammarids Exposed to Dynamic Pesticide Mixtures.

Exposure assessment of pesticides has substantially improved over time, with methods that now include a combination of advanced analytical techniques and fate/transport models to evaluate their spatiotemporal distribution. However, the current regulatory environmental risk assessment considers thresholds from laboratory studies completed under standardized conditions that do not reflect environmental dynamics. Using the General Unified Threshold model for Survival (GUTS) model framework, we predicted the impact of time-varying pesticide exposures on the survival of gammarids in a small agricultural stream. The LP50 values were used as an additional metric for assessing risks (defined in GUTS as a multiplication factor applied to the concentration time series to induce 50% mortality by the end of exposure). Although real-case exposures to individual pesticides were predicted to produce little to no impact on survival, the LP50 values indicate acute (LP50 ≤ 100) and/or chronic (LP50 ≤ 10) toxicities for azoxystrobin, chlorpyrifos, diazinon, and imidacloprid, while risk to propiconazole exposure was considered very low (LP50 ≫ 100). Finally, the model was extended to reflect mixture toxicity via concentration addition. It predicted risks under acute and chronic exposures to organophosphates and neonicotinoids. Given that gammarids are simultaneously exposed to multiple chemicals and other stressors throughout their lifetime, a decline in survival probabilities due to chemical stress can likely influence their overall fitness. We recognize that some assumptions require validation, but our work included a level of realism that can assist risk managers when evaluating the cumulative consequences of chemical exposure.

Recommendations to address uncertainties in environmental risk assessment using toxicokinetic-toxicodynamic models

Providing reliable environmental quality standards (EQSs) is a challenging issue in environmental risk assessment (ERA). These EQSs are derived from toxicity endpoints estimated from dose-response models to identify and characterize the environmental hazard of chemical compounds released by human activities. These toxicity endpoints include the classical x% effect/lethal concentrations at a specific time t (EC/LC(x, t)) and the new multiplication factors applied to environmental exposure profiles leading to x% effect reduction at a specific time t (MF(x, t), or denoted LP(x, t) by the EFSA). However, classical dose-response models used to estimate toxicity endpoints have some weaknesses, such as their dependency on observation time points, which are likely to differ between species (e.g., experiment duration). Furthermore, real-world exposure profiles are rarely constant over time, which makes the use of classical dose-response models difficult and may prevent the derivation of MF(x, t). When dealing with survival or immobility toxicity test data, these issues can be overcome with the use of the general unified threshold model of survival (GUTS), a toxicokinetic-toxicodynamic (TKTD) model that provides an explicit framework to analyse both time- and concentration-dependent data sets as well as obtain a mechanistic derivation of EC/LC(x, t) and MF(x, t) regardless of x and at any time t of interest. In ERA, the assessment of a risk is inherently built upon probability distributions, such that the next critical step is to characterize the uncertainties of toxicity endpoints and, consequently, those of EQSs. With this perspective, we investigated the use of a Bayesian framework to obtain the uncertainties from the calibration process and to propagate them to model predictions, including LC(x, t) and MF(x, t) derivations. We also explored the mathematical properties of LC(x, t) and MF(x, t) as well as the impact of different experimental designs to provide some recommendations for a robust derivation of toxicity endpoints leading to reliable EQSs: avoid computing LC(x, t) and MF(x, t) for extreme x values (0 or 100%), where uncertainty is maximal; compute MF(x, t) after a long period of time to take depuration time into account and test survival under pulses with different periods of time between them.