The MCRA toolbox of models and data to support chemical mixture risk assessment

Cumulative veterinary drug and pesticide dietary exposure assessments: a global overview and Brazilian framework considerations

Pesticides and veterinary drugs are widely employed to support food production. Assessing potential risks associated with the dietary consumption of pesticide and veterinary drug residues is, however, essential. Potential risks depend on the toxicity degree of the analyzed residue and population exposure levels. Human populations are exposed to numerous chemical substances through different pathways with varying exposure times, leading to increased health risks when compared to exposure to individual chemicals. Cumulative exposure assessments usually assess combined exposures to multiple chemicals through multiple exposure pathways. In this sense, this comprehensive review aims to provide insights into cumulative dietary pesticide and veterinary drug residue exposures. The main methodologies, strategies, and legislation employed by international agencies to this end are discussed. A review concerning articles that apply existing methodologies and approaches, as well as the challenges in this context faced by Brazil is also presented. As this is a critical issue not only for Brazilian public health but also for the global community, regulatory agencies should prioritize formulating regulations that incorporate exposure assessments regarding the simultaneous presence of residues and contaminants in foodstuffs.

FoodEx2 Harmonization of the Food Consumption Database from the Italian IV SCAI Children's Survey

Estimating the habitual food and nutrient intakes of a population is based on dietary assessment methods that collect detailed information on food consumption. Establishing the list of foods to be used for collecting data in dietary surveys is central to standardizing data collection. Comparing foods across different data sources is always challenging. Nomenclatures, detail, and classification into broad food groups and sub-groups can vary considerably. The use of a common system for classifying and describing foods is an important prerequisite for analyzing data from different sources. At the European level, EFSA has addressed this need through the development and maintenance of the FoodEx2 classification system. The aim of this work is to present the FoodEx2 harmonization of foods, beverages, and food supplements consumed in the IV SCAI children's survey carried out in Italy. Classifying foods into representative food categories predefined at European level for intake and exposure assessment may lead to a loss of information. On the other hand, a major advantage is the comparability of data from different national databases. The FoodEx2 classification of the national food consumption database represented a step forward in the standardization of the data collection and registration. The large use of FoodEx2 categories at a high level of detail (core and extended terms) combined with the use of descriptors (facets) has minimized information loss and made the reference food categories at country level comparable with different food databases at national and international level.

Multilevel meta-analysis and dose-response analysis for bisphenol A (BPA) exposure on metabolic and neurobehavioral effects

Evidence suggests that oral exposure to bisphenol A (BPA) may result in adverse metabolic and neurobehavioral effects. The aim of the present meta-analysis is to examine this association based on systematically selected laboratory rodent studies published from 2012 to 2021 and sourced from Scopus, Web of Science, EmBase, and PubMed. Articles satisfying eligibility and inclusion criteria were included for the calculation of the summary standardised mean difference (SMD). Subgroup analysis and subsequent dose-response analysis were conducted if applicable. In total, 32 studies were analysed for 6 metabolic endpoints (cholesterol, triglycerides, insulin, glucose, leptin, and adiponectin) and 6 neurobehavioral endpoints (locomotor activity, exploratory, anxiety, depression, spatial learning and memory, non-spatial learning and memory). Summary SMDs implied that no significant effects were observed in endpoints considered. The dose was not determined as a significant moderator with regards to medium or high heterogeneity; however, there was significant impairment of spatial learning and memory at health-based guidance value ('HBGV') (0.05-9 mg (kg bw)-1 day-1) and 'High' (>9 mg (kg bw)-1 day-1) dose group. As a result, an indicative toxicological reference dose value of 0.034 mg (kg bw)-1 day-1 was proposed due to large variability. Potential harm to spatial learning and memory from BPA exposure requires further investigation. This study has provided some additional information on potential adverse metabolic and neurobehavioral effects of BPA from the perspective of meta-analysis which can inform the public, regulatory authorities, and policymakers.

PACEMweb: a tool for aggregate consumer exposure assessment

BACKGROUND

To ascertain the safe use of chemicals that are used in multiple consumer products, the aggregate human exposure, arising from combined use of multiple consumer products needs to be assessed.

OBJECTIVE

In this work the Probabilistic Aggregate Consumer Exposure Model (PACEM) is presented and discussed. PACEM is implemented in the publicly available web tool, PACEMweb, for aggregate consumer exposure assessment.

METHODS

PACEM uses a person-oriented simulation method that is based on realistic product usage information obtained in surveys from several European countries. PACEM evaluates aggregate exposure in a population considering individual use and co-use patterns as well as variation in product composition. Product usage data is included on personal care products (PCPs) and household cleaning products (HCPs).

RESULTS

PACEM has been implemented in a web tool that supports broad use in research as well as regulatory risk assessment. PACEM has been evaluated in a number of applications, testing and illustrating the advantage of the person-oriented modeling method. Also, PACEM assessments have been evaluated by comparing its results with biomonitoring information.

SIGNIFICANCE

PACEM enables the assessment of realistic aggregate exposure to chemicals in consumer products. It provides detailed insight into the distribution of exposure in a population as well as products that contribute the most to exposure. This allows for better informed decision making in the risk management of chemicals.

IMPACT

Realistic assessment of the total, aggregate exposure of consumers to chemicals in consumer products is necessary to guarantee the safe use of chemicals in these products. PACEMweb provides, for the first time, a publicly available tool to assist in realistic aggregate exposure assessment of consumers to chemicals in consumer products.

A case study of neurodevelopmental risks from combined exposures to lead, methyl-mercury, inorganic arsenic, polychlorinated biphenyls, polybrominated diphenyl ethers and fluoride

We performed a mixture risk assessment (MRA) case study of dietary exposure to the food contaminants lead, methylmercury, inorganic arsenic (iAs), fluoride, non-dioxin-like polychlorinated biphenyls (NDL-PCBs) and polybrominated diphenyl ethers (PBDEs), all substances associated with declines in cognitive abilities measured as IQ loss. Most of these chemicals are frequently measured in human biomonitoring studies. A component-based, personalised modified reference point index (mRPI) approach, in which we expressed the exposures and potencies of our chosen substances as lead equivalent values, was applied to perform a MRA for dietary exposures. We conducted the assessment for four different age groups (toddlers, children, adolescents, and women aged 18-45 years) in nine European countries. Populations in all countries considered exceeded combined tolerable levels at median exposure levels. NDL-PCBs in fish, other seafood and dairy, lead in grains and fruits, methylmercury in fish and other seafoods, and fluoride in water contributed most to the combined exposure. We identified uncertainties for the likelihood of co-exposure, assessment group membership, endpoint-specific reference values (ESRVs) based on epidemiological (lead, methylmercury, iAs, fluoride and NDL-PCBs) and animal data (PBDE), and exposure data. Those uncertainties lead to a complex pattern of under- and overestimations, which would require probabilistic modelling based on expert knowledge elicitation for integration of the identified uncertainties into an overall uncertainty estimate. In addition, the identified uncertainties could be used to refine future MRA for cognitive decline.

Modeling the occupational health risk of workers caused by environmental release during the production of PC components

Prefabricated construction is one of the solutions to the problem of balancing environmental improvements with the new buildings in the construction industry. Some work originally done on site is transferred to the front end, and the occupational health risks to industrial workers during the production of prefabricate concrete components are thus aggravated. This study aims to propose a framework to simulate the occupational health risks of workers in prefabricate concrete component plants from the perspective of risk identification, risk assessment, and risk control. Through the following 4 steps, including environmental release monitoring, diffusion and human inhalation mechanism analysis, occupational health risk evaluation, and full-path health risk simulation, this study maps physical entities to virtual reality. The proposed method tends to address the root causes behind occupational health risks, such as the lack of measurement, assessment and prevention criteria, and providing new ideas for theoretical research and innovative practice of HSE management and risk management in the construction industry.

A user-friendly tool to assess combined exposures to indoor air pollutants in public spaces of children

This manuscript describes the methodology for and early experience in the application of a screening tool to assess health risks from combined exposure to indoor air pollutants in public settings for children such as schools, kindergartens and day-care centres. The user-friendly tool incorporates tiers modified from those of the World Health Organization (WHO) framework for risk assessment of combined exposure to multiple chemicals and includes a spreadsheet for risk calculation as well as a supporting toxicological database of guidance values and points of departure (PODs) for inhalation for selected effects. Supporting resources on exposure assessment include a screening questionnaire to identify optimum sampling strategies and standardized analytical methods. The approach to assessment of combined exposure within the screening tool, including decision rules, assumptions and limitations/uncertainties is addressed, as is the nature of health-effects and reference/toxicity values prioritized for inclusion in the associated toxicological database. Results of early experience in application illustrate how the screening tool contributes as an important component in strategies to assess and manage indoor air pollution in public settings for children.

MRA Toolbox v. 1.0: a web-based toolbox for predicting mixture toxicity of chemical substances in chemical products

The chemical risk assessment paradigm is shifting from “substance-based” to “product/mixture-based” and from “animal testing” to “alternative testing” under chemical regulations. Organisms and the environment may be exposed to mixtures rather than a single substance. Conducting toxicity tests for all possible combinations is impractical due to the enormous combinatorial complexity. This study highlights the development and application case studies of Mixture Risk Assessment Toolbox, a novel web-based platform that supports mixture risk assessment through the use of different prediction models and public databases. This integrated framework provides new functional values for assessors to easily screen and compare the toxicity of mixture products using different computational techniques and find strategic solutions to reduce the mixture toxicity in the product development process. The toolbox (https://www.mratoolbox.org) includes four additive toxicity models: two conventional (Concentration Addition; and Independent Action) and two advanced (Generalized Concentration Addition; and Quantitative Structure–Activity Relationship-based Two-Stage Prediction) models. We demonstrated the multiple functions of the toolbox using three cases: (i) how it can be used to calculate the mixture toxicity, (ii) those for which safety data sheet (SDS) only indicating representative toxicity values (EC₅₀; and LC₅₀), and (iii) those comprising chemicals with low toxic effects.

Combined Exposure to Multiple Mycotoxins: An Example of Using a Tiered Approach in a Mixture Risk Assessment

Humans are exposed to mycotoxins on a regular basis. Exposure to a mixture of mycotoxins may, therefore, result in a combination of adverse effects, or trigger the same effects. This should be accounted for when assessing the combined risk of multiple mycotoxins. Here, we show the outcome of using different approaches in assessing the risks related to the combined exposure to mycotoxins. We performed a tiered approach using assessment groups with a common target organ (kidney, liver and haematologic system), or a common adverse effect (phenomenon) (reduced white blood cell count), to combine the exposure to mycotoxins. The combined exposure was calculated for the individuals in this assessment, using the Monte Carlo Risk Assessment (MCRA) tool. The risk related to this combined exposure was assessed using toxicological reference values, e.g., health based guidance values. We show that estimating the combined risk by adding the single compounds’ risk distributions slightly overestimates the combined risk in the 95th percentile, as compared to combining the exposures at an individual level. We also show that relative potency factors can be used to refine the mixture risk assessment, as compared to ratios of toxicological reference values with different effect sizes and assessment factors.

Dose Addition in the Induction of Craniofacial Malformations in Zebrafish Embryos Exposed to a Complex Mixture of Food-Relevant Chemicals with Dissimilar Modes of Action

BACKGROUND

Humans are exposed to combinations of chemicals. In cumulative risk assessment (CRA), regulatory bodies such as the European Food Safety Authority consider dose addition as a default and sufficiently conservative approach. The principle of dose addition was confirmed previously for inducing craniofacial malformations in zebrafish embryos in binary mixtures of chemicals with either similar or dissimilar modes of action (MOAs).

OBJECTIVES

In this study, we explored a workflow to select and experimentally test multiple compounds as a complex mixture with each of the compounds at or below its no observed adverse effect level (NOAEL), in the same zebrafish embryo model.

METHODS

Selection of candidate compounds that potentially induce craniofacial malformations was done using in silico methods-structural similarity, molecular docking, and quantitative structure-activity relationships-applied to a database of chemicals relevant for oral exposure in humans via food (EuroMix inventory, n=1,598). A final subselection was made manually to represent different regulatory fields (e.g., food additives, industrial chemicals, plant protection products), different chemical families, and different MOAs.

RESULTS

A final selection of eight compounds was examined in the zebrafish embryo model, and craniofacial malformations were observed in embryos exposed to each of the compounds, thus confirming the developmental toxicity as predicted by the in silico methods. When exposed to a mixture of the eight compounds, each at its NOAEL, substantial craniofacial malformations were observed; according to a dose-response analysis, even embryos exposed to a 7-fold dilution of this mixture still exhibited a slight abnormal phenotype. The cumulative effect of the compounds in the mixture was in accordance with dose addition (added doses of the individual compounds after adjustment for relative potencies), despite different MOAs of the compounds involved.

DISCUSSION

This case study of a complex mixture inducing craniofacial malformations in zebrafish embryos shows that dose addition can adequately predicted the cumulative effect of a mixture of multiple substances at low doses, irrespective of the (expected) MOA. The applied workflow may be useful as an approach for CRA in general. https://doi.org/10.1289/EHP9888.

Towards a qAOP framework for predictive toxicology - Linking data to decisions

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Chemical toxicity assessment depends on the quantification of kinetics and dynamics.

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Quantitative AOPs (qAOPs) are toxicodynamic models based on Adverse Outcome Pathways.

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Existing e-resources could form the basis of an e-infrastructure for qAOP modelling.

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Best practices for qAOP development, assessment and application are needed.

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Three qAOP case studies are presented to illustrate a modelling workflow.

The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.

PBPK Modeling to Simulate the Fate of Compounds in Living Organisms

Pharmacokinetics study the fate of xenobiotics in a living organism. Physiologically based pharmacokinetic (PBPK) models provide realistic descriptions of xenobiotics' absorption, distribution, metabolism, and excretion processes. They model the body as a set of homogeneous compartments representing organs, and their parameters refer to anatomical, physiological, biochemical, and physicochemical entities. They offer a quantitative mechanistic framework to understand and simulate the time-course of the concentration of a substance in various organs and body fluids. These models are well suited for performing extrapolations inherent to toxicology and pharmacology (e.g., between species or doses) and for integrating data obtained from various sources (e.g., in vitro or in vivo experiments, structure-activity models). In this chapter, we describe the practical development and basic use of a PBPK model from model building to model simulations, through implementation with an easily accessible free software.

Guidance Document on Scientific criteria for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals

This guidance document provides harmonised and flexible methodologies to apply scientific criteria and prioritisation methods for grouping chemicals into assessment groups for human risk assessment of combined exposure to multiple chemicals. In the context of EFSA's risk assessments, the problem formulation step defines the chemicals to be assessed in the terms of reference usually through regulatory criteria often set by risk managers based on legislative requirements. Scientific criteria such as hazard-driven criteria can be used to group these chemicals into assessment groups. In this guidance document, a framework is proposed to apply hazard-driven criteria for grouping of chemicals into assessment groups using mechanistic information on toxicity as the gold standard where available (i.e. common mode of action or adverse outcome pathway) through a structured weight of evidence approach. However, when such mechanistic data are not available, grouping may be performed using a common adverse outcome. Toxicokinetic data can also be useful for grouping, particularly when metabolism information is available for a class of compounds and common toxicologically relevant metabolites are shared. In addition, prioritisation methods provide means to identify low-priority chemicals and reduce the number of chemicals in an assessment group. Prioritisation methods include combined risk-based approaches, risk-based approaches for single chemicals and exposure-driven approaches. Case studies have been provided to illustrate the practical application of hazard-driven criteria and the use of prioritisation methods for grouping of chemicals in assessment groups. Recommendations for future work are discussed.

Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview

Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward.

Risk assessment approaches for evaluating cumulative exposures to multiple pesticide residues in agro-products using seasonal vegetable monitoring data from Hainan, China: a case study

Risks from combined exposure to multiple chemicals in food have prompted a growing concern for their effect on human health. Risk management of chemical mixtures should be based on developing and harmonizing methodologies to scientifically evaluate their cumulative adverse effects. In this study, a simplified tiered approach of cumulative exposure assessment is described along with a case study of vegetables in China's Hainan province during 2012-2014. This case study could be a reference for the Chinese National Risk Assessment Programs for vegetable and fruit products. In the proposed assessment approach, Tier 1 acts as a screening tier to categorize and evaluate chemicals under a conservative scenario, and it prioritizes the pesticides of most concern. Tier 2 refines the grouping of substances from Tier 1 and normalizes the toxic potency of the chemicals to sum the exposure of chemical mixtures in a given assessment group. Tier 3 applies the refined exposure model and the input parameter distribution to create probabilistic models using Monte Carlo simulation. This approach will be helpful in the cumulative exposure assessment where data on pesticide residues are sufficient, but the individual dietary consumption is inadequate.

A targeted transcriptomics approach for the determination of mixture effects of pesticides

While real-life exposure occurs to complex chemical mixtures, toxicological risk assessment mostly focuses on individual compounds. There is an increasing demand for in vitro tools and strategies for mixture toxicity analysis. Based on a previously established set of hepatotoxicity marker genes, we analyzed mixture effects of non-cytotoxic concentrations of different pesticides in exposure-relevant binary mixtures in human HepaRG hepatocarcinoma cells using targeted transcriptomics. An approach for mixture analysis at the level of a complex endpoint such as a transcript pattern is presented, including mixture design based on relative transcriptomic potencies and similarities. From a mechanistic point of view, goal of the study was to evaluate combinations of chemicals with varying degrees of similarity in order to determine whether differences in mechanisms of action lead to different mixtures effects. Using a model deviation ratio-based approach for assessing mixture effects, it was revealed that most data points are consistent with the assumption of dose addition. A tendency for synergistic effects was only observed at high concentrations of some combinations of the test compounds azoxystrobin, cyproconazole, difenoconazole, propiconazole and thiacloprid, which may not be representative of human real-life exposure. In summary, the findings of our study suggest that, for the pesticide mixtures investigated, risk assessment based on the general assumption of dose addition can be considered sufficiently protective for consumers. The way of data analysis presented in this paper can pave the way for a more comprehensive use of multi-gene expression data in experimental studies related to mixture toxicity.

An eight-compound mixture but not corresponding concentrations of individual chemicals induces triglyceride accumulation in human liver cells

In real life, organisms are exposed to complex mixtures of chemicals at low concentration levels, whereas research on toxicological effects is mostly focused on single compounds at comparably high doses. Mixture effects deviating from the assumption of additivity, especially synergistic effects, are of concern. In an adverse outcome pathway (AOP)-guided manner, we analyzed the accumulation of triglycerides in human HepaRG liver cells by a mixture of eight steatotic chemicals (amiodarone, benzoic acid, cyproconazole, flusilazole, imazalil, prochloraz, propiconazole and tebuconazole), each present below its individual effect concentration at 1-3 μM. Pronounced and significantly enhanced triglyceride accumulation was observed with the mixture, and similar effects were seen at the level of pregnane-X-receptor activation, a molecular initiating event leading to hepatic steatosis. Transcript pattern analysis indicated subtle pro-steatotic changes at low compound concentrations, which did not exert measurable effects on cellular triglycerides. Mathematical modeling of mixture effects indicated potentially more than additive behavior using a model for compounds with similar modes of action. The present data underline the usefulness of AOP-guided in vitro testing for the identification of mixture effects and highlight the need for further research on chemical mixtures and harmonization of data interpretation of mixture effects.

Quantitative in Vitro-to-in Vivo Extrapolation for Mixtures: A Case Study of Superfund Priority List Pesticides

In vitro cell-based toxicity testing methods generate large amounts of data informative for risk-based evaluations. To allow extrapolation of the quantitative outputs from cell-based tests to the equivalent exposure levels in humans, reverse toxicokinetic (RTK) modeling is used to conduct in vitro-to-in vivo extrapolation (IVIVE) from in vitro effective concentrations to in vivo oral dose equivalents. IVIVE modeling approaches for individual chemicals are well-established; however, the potential implications of chemical-to-chemical interactions in mixture settings on IVIVE remains largely unexplored. We hypothesized that chemical co-exposures could modulate both protein binding efficiency and hepatocyte clearance of the chemicals in a mixture, which would in turn affect the quantitative IVIVE toxicokinetic parameters. To test this hypothesis, we used 20 pesticides from the Agency for Toxic Substances and Disease Registry (ATSDR) Substance Priority List, both individually and as equimolar mixtures, and investigated the concentration-dependent effects of chemical interactions on in vitro toxicokinetic parameters. Plasma protein binding efficiency was determined by using ultracentrifugation, and hepatocyte clearance was estimated in suspensions of cryopreserved primary human hepatocytes. We found that for single chemicals, the protein binding efficiencies were similar at different test concentrations. In a mixture, however, both protein binding efficiency and hepatocyte clearance were affected. When IVIVE was conducted using mixture-derived toxicokinetic data, more conservative estimates of Activity-to-Exposure Ratios (AERs) were produced as compared to using data from single chemical experiments. Because humans are exposed to mixtures of chemicals, this study is significant as it demonstrates the importance of incorporating mixture-derived parameters into IVIVE for in vitro bioactivity data in order to accurately prioritize risks and facilitate science-based decision-making.

A generic PBTK model implemented in the MCRA platform: Predictive performance and uses in risk assessment of chemicals

Physiologically-based toxicokinetic (PBTK) models are important tools for in vitro to in vivo or inter-species extrapolations in health risk assessment of foodborne and non-foodborne chemicals. Here we present a generic PBTK model implemented in the EuroMix toolbox, MCRA 9 and predict internal kinetics of nine chemicals (three endocrine disrupters, three liver steatosis inducers, and three developmental toxicants), in data-rich and data-poor conditions, when increasingly complex levels of parametrization are applied. At the first stage, only QSAR models were used to determine substance-specific parameters, then some parameter values were refined by estimates from substance-specific or high-throughput in vitro experiments. At the last stage, elimination or absorption parameters were calibrated based on available in vivo kinetic data. The results illustrate that parametrization plays a capital role in the output of the PBTK model, as it can change how chemicals are prioritized based on internal concentration factors. In data-poor situations, estimates can be far from observed values. In many cases of chronic exposure, the PBTK model can be summarized by an external to internal dose factor, and interspecies concentration factors can be used to perform interspecies extrapolation. We finally discuss the implementation and use of the model in the MCRA risk assessment platform.

Recommendations for international harmonisation, implementation and further development of suitable scientific approaches regarding the assessment of mixture effects

Legal frameworks lay down requirements for risk assessment of combined exposure to multiple chemicals and their implementation where scientific methods are accepted by responsible authorities. In order to protect human health, an assessment of potential risks that might result from co-exposure to multiple chemical substances is requested by European legislation. Several approaches for risk assessment of mixtures of chemicals have been proposed, but none has been widely implemented in regulatory risk assessments, so far. EuroMix, an EU Horizon 2020 funded project, contributed to the improvement of internationally harmonised approaches for risk assessment of chemical mixtures. Based on in vitro and in silico tests, an integrated test strategy involving hazard and exposure assessment was developed and a web tool to conduct such assessments was provided. One further task within EuroMix was to make recommendations for international harmonisation, implementation and further development of suitable scientific approaches regarding the assessment of mixture effects. This paper briefly describes objectives and outcome of the EuroMix project as well as recent findings from OECD, WHO and EFSA addressing combined exposure to multiple chemicals. Building on this, five steps addressing further development needs and implementation of existing tools especially for risk managers and policy makers are proposed.

A retain and refine approach to cumulative risk assessment

Mixtures of substances to which humans are exposed may lead to cumulative exposure and health effects. To study their effects, it is first necessary to identify a cumulative assessment group (CAG) of substances for risk assessment or hazard testing. Excluding substances from consideration before there is sufficient evidence may underestimate the risk. Conversely, including everything and treating the inevitable uncertainties using conservative assumptions is inefficient and may overestimate the risk, with an unknown level of protection. An efficient, transparent strategy is described to retain a large group, quantifying the uncertainty of group membership and other uncertainties. Iterative refinement of the CAG then focuses on adding information for the substances with high probability of contributing significantly to the risk. Probabilities can be estimated using expert opinion or derived from data on substance properties. An example is presented with 100 pesticides, in which the retain step identified a single substance to target refinement. Using an updated hazard characterisation for this substance reduced the mean exposure estimate from 0.43 to 0.28 μg kg-bw^-1 day^-1 and reduced the 99.99th percentile exposure from 24.9 to 5.1 μg kg-bw^-1 day^-1. Other retained substances contributed little to the risk estimates, even after accounting for uncertainty.