A Framework for Algae Modeling in Regulatory Risk Assessment.

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

Mechanistic Effect Modeling of Earthworms in the Context of Pesticide Risk Assessment: Synthesis of the FORESEE Workshop.

Earthworms are important ecosystem engineers, and assessment of the risk of plant protection products toward them is part of the European environmental risk assessment (ERA). In the current ERA scheme, exposure and effects are represented simplistically and are not well integrated, resulting in uncertainty when the results are applied to ecosystems. Modeling offers a powerful tool to integrate the effects observed in lower tier laboratory studies with the environmental conditions under which exposure is expected in the field. This paper provides a summary of the (In)Field Organism Risk modEling by coupling Soil Exposure and Effect (FORESEE) Workshop held 28-30 January 2020 in Düsseldorf, Germany. This workshop focused on toxicokinetic-toxicodynamic (TKTD) and population modeling of earthworms in the context of ERA. The goal was to bring together scientists from different stakeholder groups to discuss the current state of soil invertebrate modeling and to explore how earthworm modeling could be applied to risk assessments, in particular how the different model outputs can be used in the tiered ERA approach. In support of these goals, the workshop aimed at addressing the requirements and concerns of the different stakeholder groups to support further model development. The modeling approach included 4 submodules to cover the most relevant processes for earthworm risk assessment: environment, behavior (feeding, vertical movement), TKTD, and population. Four workgroups examined different aspects of the model with relevance for risk assessment, earthworm ecology, uptake routes, and cross-species extrapolation and model testing. Here, we present the perspectives of each workgroup and highlight how the collaborative effort of participants from multidisciplinary backgrounds helped to establish common ground. In addition, we provide a list of recommendations for how earthworm TKTD modeling could address some of the uncertainties in current risk assessments for plant protection products. Integr Environ Assess Manag 2021;17:352-363. © 2020 SETAC.

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.

Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment.

An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from in vitro to in vivo, and to extrapolate across species. Finally, we identify best practices for modeling and model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of qAOP models and ultimately their use in regulatory applications. Environ Toxicol Chem 2019;38:1850-1865. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

How to Evaluate the Quality of Toxicokinetic-Toxicodynamic Models in the Context of Environmental Risk Assessment.

Environmental risk assessment (ERA) of chemicals relies on the combination of exposure and effects assessment. Exposure concentrations are commonly estimated using mechanistic fate models, but the effects side is restricted to descriptive statistical treatment of toxicity data. Mechanistic effect models are gaining interest in a regulatory context, which has also sparked discussions on model quality and good modeling practice. Proposals for good modeling practice of effect models currently focus very much on population and community models, whereas effects models also exist at the individual level, falling into the category of toxicokinetic-toxicodynamic (TKTD) models. In contrast to the higher-level models, TKTD models are usually completely parameterized by fitting them to experimental data. In fact, one of their explicit aims is to replace descriptive methods for data analysis. Furthermore, the construction of these models does not fit into an orderly modeling cycle, given that most TKTD models have been under continuous development for decades and are being applied by many different research groups, for many different purposes. These aspects have considerable consequences for the application of frameworks for model evaluation. For example, classical sensitivity analysis becomes rather meaningless when all model parameters are fitted to a data set. We illustrate these issues with the General Unified Threshold model for Survival (GUTS), relate them to the quality issues for currently used models in ERA, and provide recommendations for the evaluation of TKTD models and their analyses. Integr Environ Assess Manag 2018;14:604-614. ©2018 SETAC.

A standardized tritrophic small-scale system (TriCosm) for the assessment of stressor-induced effects on aquatic community dynamics.

Chemical impacts on the environment are routinely assessed in single-species tests. They are employed to measure direct effects on nontarget organisms, but indirect effects on ecological interactions can only be detected in multispecies tests. Micro- and mesocosms are more complex and environmentally realistic, yet they are less frequently used for environmental risk assessment because resource demand is high, whereas repeatability and statistical power are often low. Test systems fulfilling regulatory needs (i.e., standardization, repeatability, and replication) and the assessment of impacts on species interactions and indirect effects are lacking. In the present study we describe the development of the TriCosm, a repeatable aquatic multispecies test with 3 trophic levels and increased statistical power. High repeatability of community dynamics of 3 interacting aquatic populations (algae, Ceriodaphnia, and Hydra) was found with an average coefficient of variation of 19.5% and the ability to determine small effect sizes. The TriCosm combines benefits of both single-species tests (fulfillment of regulatory requirements) and complex multispecies tests (ecological relevance) and can be used, for instance, at an intermediate tier in environmental risk assessment. Furthermore, comparatively quickly generated population and community toxicity data can be useful for the development and testing of mechanistic effect models. Environ Toxicol Chem 2018;37:1051-1060. © 2017 SETAC.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments.

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC.

Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS).

The General Unified Threshold model of Survival (GUTS) provides a consistent mathematical framework for survival analysis. However, the calibration of GUTS models is computationally challenging. We present a novel algorithm and its fast implementation in our R package, GUTS, that help to overcome these challenges. We show a step-by-step application example consisting of model calibration and uncertainty estimation as well as making probabilistic predictions and validating the model with new data. Using self-defined wrapper functions, we show how to produce informative text printouts and plots without effort, for the inexperienced as well as the advanced user. The complete ready-to-run script is available as supplemental material. We expect that our software facilitates novel re-analysis of existing survival data as well as asking new research questions in a wide range of sciences. In particular the ability to quickly quantify stressor thresholds in conjunction with dynamic compensating processes, and their uncertainty, is an improvement that complements current survival analysis methods.

Using toxicokinetic-toxicodynamic modeling as an acute risk assessment refinement approach in vertebrate ecological risk assessment.

Recent guidance identified toxicokinetic-toxicodynamic (TK-TD) modeling as a relevant approach for risk assessment refinement. Yet, its added value compared to other refinement options is not detailed, and how to conduct the modeling appropriately is not explained. This case study addresses these issues through 2 examples of individual-level risk assessment for 2 hypothetical plant protection products: 1) evaluating the risk for small granivorous birds and small omnivorous mammals of a single application, as a seed treatment in winter cereals, and 2) evaluating the risk for fish after a pulsed treatment in the edge-of-field zone. Using acute test data, we conducted the first tier risk assessment as defined in the European Food Safety Authority (EFSA) guidance. When first tier risk assessment highlighted a concern, refinement options were discussed. Cases where the use of models should be preferred over other existing refinement approaches were highlighted. We then practically conducted the risk assessment refinement by using 2 different models as examples. In example 1, a TK model accounting for toxicokinetics and relevant feeding patterns in the skylark and in the wood mouse was used to predict internal doses of the hypothetical active ingredient in individuals, based on relevant feeding patterns in an in-crop situation, and identify the residue levels leading to mortality. In example 2, a TK-TD model accounting for toxicokinetics, toxicodynamics, and relevant exposure patterns in the fathead minnow was used to predict the time-course of fish survival for relevant FOCUS SW exposure scenarios and identify which scenarios might lead to mortality. Models were calibrated using available standard data and implemented to simulate the time-course of internal dose of active ingredient or survival for different exposure scenarios. Simulation results were discussed and used to derive the risk assessment refinement endpoints used for decision. Finally, we compared the "classical" risk assessment approach with the model-based approach. These comparisons showed that TK and TK-TD models can bring more realism to the risk assessment through the possibility to study realistic exposure scenarios and to simulate relevant mechanisms of effects (including delayed toxicity and recovery). Noticeably, using TK-TD models is currently the most relevant way to directly connect realistic exposure patterns to effects. We conclude with recommendations on how to properly use TK and TK-TD model in acute risk assessment for vertebrates.

Nanopesticides: guiding principles for regulatory evaluation of environmental risks.

Nanopesticides or nano plant protection products represent an emerging technological development that, in relation to pesticide use, could offer a range of benefits including increased efficacy, durability, and a reduction in the amounts of active ingredients that need to be used. A number of formulation types have been suggested including emulsions (e.g., nanoemulsions), nanocapsules (e.g., with polymers), and products containing pristine engineered nanoparticles, such as metals, metal oxides, and nanoclays. The increasing interest in the use of nanopesticides raises questions as to how to assess the environmental risk of these materials for regulatory purposes. Here, the current approaches for environmental risk assessment of pesticides are reviewed and the question of whether these approaches are fit for purpose for use on nanopesticides is addressed. Potential adaptations to existing environmental risk assessment tests and procedures for use with nanopesticides are discussed, addressing aspects such as analysis and characterization, environmental fate and exposure assessment, uptake by biota, ecotoxicity, and risk assessment of nanopesticides in aquatic and terrestrial ecosystems. Throughout, the main focus is on assessing whether the presence of the nanoformulation introduces potential differences relative to the conventional active ingredients. The proposed changes in the test methodology, research priorities, and recommendations would facilitate the development of regulatory approaches and a regulatory framework for nanopesticides.

Highly time-variable exposure to chemicals--toward an assessment strategy.

Organisms in the environment experience fluctuating, pulsed, or intermittent exposure to pollutants. Accounting for effects of such exposures is an important challenge for environmental risk assessment, particularly given the simplified design of standard ecotoxicity tests. Dynamic simulation using toxicokinetic-toxicodynamic (TK-TD) models describes the processes that link exposure with effects in an organism and provides a basis for extrapolation to a range of exposure scenarios. In so doing, TK-TD modeling makes the risk assessment more robust and aids use and interpretation of experimental data. Toxicokinetic-toxicodynamic models are well-developed for predicting survival of individual organisms and are increasingly applied to sublethal endpoints. In the latter case particularly, linkage to individual-based models (IBMs) allows extrapolation to population level as well as accounting for differences in effects of toxicant exposure at different stages in the life cycle. Extrapolation between species remains an important constraint because there is currently no systematic understanding of species traits that cause differences in the relevant processes. Toxicokinetic-toxicodynamic models allow interrogation of exposure profiles to determine intrinsic toxicity potential rather than using absolute maximum concentrations or time-weighted averages as surrogates. A decision scheme is proposed to guide selection of risk assessment approaches using dose extrapolation based on Haber's Law, TK-TD models, and/or IBMs depending on the nature of toxic effect and timing in relation to life history.

Environmental risk assessment of fluctuating diazinon concentrations in an urban and agricultural catchment using toxicokinetic-toxicodynamic modeling.

Temporally resolved environmental risk assessment of fluctuating concentrations of micropollutants is presented. We separated the prediction of toxicity over time from the extrapolation from one to many species and from acute to sublethal effects. A toxicokinetic-toxicodynamic (TKTD) model predicted toxicity caused by fluctuating concentrations of diazinon, measured by time-resolved sampling over 108 days from three locations in a stream network, representing urban, agricultural and mixed land use. We calculated extrapolation factors to quantify variation in toxicity among species and effect types based on available toxicity data, while correcting for different test durations with the TKTD model. Sampling from the distribution of extrapolation factors and prediction of time-resolved toxicity with the TKTD model facilitated subsequent calculation of the risk of undesired toxic events. Approximately one-fifth of aquatic organisms were at risk and fluctuating concentrations were more toxic than their averages. Contribution of urban and agricultural sources of diazinon to the overall risk varied. Thus using fixed concentrations as water quality criteria appears overly simplistic because it ignores the temporal dimension of toxicity. However, the improved prediction of toxicity for fluctuating concentrations may be small compared to uncertainty due to limited diversity of toxicity data to base the extrapolation factors on.

Framework for traits-based assessment in ecotoxicology.

A key challenge in ecotoxicology is to assess the potential risks of chemicals to the wide range of species in the environment on the basis of laboratory toxicity data derived from a limited number of species. These species are then assumed to be suitable surrogates for a wider class of related taxa. For example, Daphnia spp. are used as the indicator species for freshwater aquatic invertebrates. Extrapolation from these datasets to natural communities poses a challenge because the extent to which test species are representative of their various taxonomic groups is often largely unknown, and different taxonomic groups and chemicals are variously represented in the available datasets. Moreover, it has been recognized that physiological and ecological factors can each be powerful determinants of vulnerability to chemical stress, thus differentially influencing toxicant effects at the population and community level. Recently it was proposed that detailed study of species traits might eventually permit better understanding, and thus prediction, of the potential for adverse effects of chemicals to a wider range of organisms than those amenable for study in the laboratory. This line of inquiry stems in part from the ecology literature, in which species traits are being used for improved understanding of how communities are constructed, as well as how communities might respond to, and recover from, disturbance (see other articles in this issue). In the present work, we develop a framework for the application of traits-based assessment. The framework is based on the population vulnerability conceptual model of Van Straalen in which vulnerability is determined by traits that can be grouped into 3 major categories, i.e., external exposure, intrinsic sensitivity, and population sustainability. Within each of these major categories, we evaluate specific traits as well as how they could contribute to the assessment of the potential effects of a toxicant on an organism. We then develop an example considering bioavailability to explore how traits could be used mechanistically to estimate vulnerability. A preliminary inventory of traits for use in ecotoxicology is included; this also identifies the availability of data to quantify those traits, in addition to an indication of the strength of linkage between the trait and the affected process. Finally, we propose a way forward for the further development of traits-based approaches in ecotoxicology.

Advantages of toxicokinetic and toxicodynamic modelling in aquatic ecotoxicology and risk assessment.

Toxicokinetic-toxicodynamic (TK-TD) models simulate the processes that lead to toxicity at the level of organisms over time. These dynamic simulation models quantify toxicity, but more importantly they also provide a conceptual framework to better understand the causes for variability in different species' sensitivity to the same compound as well as causes for different toxicity of different compounds to the same species. Thus TK-TD models bring advantages for very diverse ecotoxicological questions as they can address two major challenges: the large number of species that are potentially affected and the large number of chemicals of concern. The first important benefit of TK-TD models is the role that they can play to formalize established knowledge about toxicity of compounds, sensitivity of organisms, organism recovery times and carry-over toxicity. The second important aspect of TK-TD models is their ability to simulate temporal aspects of toxicity which makes them excellent extrapolation tools for risk assessment of fluctuating or pulsed exposures to pollutants. We provide a general introduction to the concept of TK-TD modelling for environmental scientists and discuss opportunities as well as current limitations.