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Physiologically-based pharmacokinetic (PBPK) modeling analysis does not stand on its own for regulatory purposes but is a robust tool to support drug/chemical safety assessment. While the development of PBPK models have grown steadily since their emergence, only a handful of models have been accepted to support regulatory purposes due to obstacles such as the lack of a standardized template for reporting PBPK analysis. Here, we expand the existing guidances designed for pharmaceutical applications by recommending additional elements that are relevant to environmental chemicals. This harmonized reporting template can be adopted and customized by public health agencies receiving PBPK model submission, and it can also serve as general guidance for submitting PBPK-related studies for publication in journals or other modeling sharing purposes. The current effort represents one of several ongoing collaborations among the PBPK modeling and risk assessment communities to promote, when appropriate, incorporating PBPK modeling to characterize the influence of pharmacokinetics on safety decisions made by regulatory agencies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Measuring adverse effects on honey bees and their colonies requires a suitable methodology. For example, due to the large number of bees in a hive and the foraging activity, measuring the mortality of individuals is a difficult task that has not yet been adequately addressed. Knowing the natural daily mortality rate of a bee colony would be of great benefit in assessing whether and to what extent external influences and stress factors affect mortality. More precise mortality data could in turn help refining specific protection goals for regulatory purpose. The European Food Safety Authority recently published a document that estimated such mortality rates based on a systematic literature review, but none of these rates were assessed from continuous monitoring of colonies. Currently, bee mortality is routinely evaluated with various types of dead bee traps that prevent deceased bees from being removed from the colony. Both the literature review and the dead bee traps are relevant to regulatory risk assessment, but in our opinion are not describing the total mortality. Bee counters capable of precisely determining daily loss rates meet the above points and combine them with generating automated and continuous monitoring data. Lately, the field has gained a lot of importance in research and technological advances offer new possibilities in regulatory risk assessment. We will highlight these possibilities and discuss their future application in practice. [ABSTRACT FROM AUTHOR]

There is a regulatory need for crop development dates to assess current default values used within chemical exposure assessments as well as to justify refinements within risk assessments. However, a readily available pan‐European crop phenology database covering key FOrum for the Co‐ordination of pesticide fate models and their USe (FOCUS) crops and scenarios to meet this need is not currently available. Therefore, we describe the development of a harmonized, pan‐European, CropLife Europe Crop Development Database (C2D2), that is fully aligned with this regulatory requirement utilizing efficacy trials data generated for regulatory submissions when registering plant protection products under Regulation (EU)1107/2009. Evaluation of C2D2 against an independent data set showed good agreement for equivalent time periods, crop growth stages, and geographical regions. We illustrate how this database can be used to evaluate existing default crop development dates mandated by regulatory agencies for use within exposure assessments. Despite the large data set compiled and the geographical coverage of C2D2, not all FOCUSsw/gw scenarios have sufficient data to facilitate comparison, with less significant scenarios, like FOCUSgw Porto, being underrepresented. For those scenarios with sufficient data, clear differences between C2D2 and crop development dates assumed in the FOCUS modeling framework (using the AppDate tool) are often indicated over many growth stages, suggesting that amendment of the existing representation of crop development within the risk assessment process may be required. C2D2 is freely available under a Creative Commons license to facilitate innovation in exposure science to allow for more accurate and realistic risk assessment leading to enhanced crop and environmental protection. Integr Environ Assess Manag 2024;20:1060–1074. © 2023 CropLife Europe (Corteva Agriscience) and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: A freely available, harmonized, pan‐European crop development database (CropLife Europe Crop Development Database [C2D2]) has been developed by CropLife Europe for use in regulatory chemical exposure assessments by collating and harmonizing efficacy trials data generated for regulatory submissions when registering plant protection products.C2D2 comprises a wide range of crops (combinable, root, vegetable, top fruit, soft fruit), spans two decades (2000–2020), and covers 30 countries facilitating comparison with current regulatory scenarios, which suggests that amendment of the existing representation of crop development may be required.Evaluation of C2D2 against an independent data set from Germany for equivalent time periods and crop growth stages showed good agreement, promoting its use in exposure science innovation to allow for more accurate and realistic risk assessment leading to enhanced crop and environmental protection.C2D2 holds significant opportunities for future development of crop models to improve estimates and timing of chemical exposure, not only for use in chemical fate and transport models but also for nontarget organism, for example, pollinators, effect, and risk assessment. [ABSTRACT FROM AUTHOR]

In this study, 129 exposure situations (ESs) with six or more measured inhalation exposures to dust from solids or vapour from liquids in occupational settings were compared with modelled European Centre of Ecotoxicology and Toxicology of Chemicals (ECETOC) targeted risk assessment tool, version 3 (TRAv3) estimates. The measurement data were extracted from previously published studies examining TRAv3 performance and pooled into a curated database. The comparison exercise focussed on the vapour exposure scenarios, as there were too few dust scenarios for a meaningful analysis of any required model corrections. A group of experts in the exposure modelling field retrieved and reviewed the input parameters used in these ESs. Where considered appropriate, modifications were applied to better match the input parameter definitions and the scope of applicability of the TRAv3. Differences and mean absolute error (MAE) were calculated between the log-transformed modelled exposure value and the 75th percentile of each measured data set and regression analysis was performed. The results indicated that the TRAv3 overestimated 80% of the measured data sets. Both over- and underestimations were mostly by factors 1–5. The calculated MAE for liquids was 0.7, indicating that on average the difference between the 75th percentile and the TRAv3 estimate was less than one order of magnitude. A multiple linear regression showed that some input parameters such as medium volatility, certain process categories (PROC), industrial setting, and the presence of local exhaust ventilation are associated with underestimations. The results of the regression analysis can be used by TRAv3 users to review the degree of over- or underestimation in their current exposure assessments, compared to the curated database. Although multiple linear regression is an appropriate methodology to characterize the TRAv3's performance, more data sets are still needed in view of some remaining data gaps. Nevertheless, the results of the current analysis are being used by ECETOC to further develop the tool as a suitably conservative screening tool for use in REACH chemical safety assessment of occupational exposure to chemicals. [ABSTRACT FROM AUTHOR]

The United States Environmental Protection Agency (EPA) regulates chemical manufacture, import, processing, distribution, use, and disposal under the 2016 amended Toxic Substances Control Act (TSCA) for the purposes of protecting the public and sensitive populations—including workers—from chemical exposure risk. The publication of several TSCA risk evaluations provided a unique opportunity to evaluate the evolving regulatory approach for assessing the dermal exposure pathway in occupational settings. In this analysis, the occupational dermal exposure assessment methods employed in several TSCA risk evaluations were assessed. Specifically, a methodology review was conducted for the occupational dermal scenarios of manufacturing and feedstock use in the risk evaluations of three chlorinated organic chemicals: trichloroethylene, carbon tetrachloride, and perchloroethylene. Additionally, alternative exposure estimates were generated using the exposure model IH SkinPermTM. The review and alternative exposure analyses indicate that the current TSCA modeling approach may generate total dermal absorbed doses for chlorinated chemical manufacturing and feedstock use scenarios that are 2- to 20-fold higher than those generated by IH SkinPerm. Best-practice recommendations developed in the methodology review support a tiered, integrated approach to dermal exposure assessment that emphasizes collecting qualitative data; employing validated, peer-reviewed models that align with current industrial practices; and gathering empirical sampling data where needed. Collaboration among industry, EPA, and other stakeholders to share information and develop a standard approach to exposure assessment under TSCA would improve the methodological rigor of, and increase confidence in, the risk evaluation results. [ABSTRACT FROM AUTHOR]

In this article, we have responded to the key statements in the article by Koivisto et al. (2022) that were incorrect and considered to be a biased critique on a subset of the exposure models used in Europe (i.e. ART and Stoffenmanager®) used for regulatory exposure assessment. We welcome scientific discussions on exposure modelling (as was done during the ISES Europe workshop) and criticism based on scientific evidence to contribute to the advancement of occupational exposure estimation tools. The tiered approach to risk assessment allows various exposure assessment models from screening tools (control/hazard banding) through to higher-tiered approaches. There is a place for every type of model, but we do need to recognize the cost and data requirements of highly bespoke assessments. That is why model developers have taken pragmatic approaches to develop tools for exposure assessments based on imperfect data. We encourage Koivisto et al. to focus on further scientifically robust work to develop mass-balance models and by independent external validations studies, compare these models with alternative model tools such as ART and Stoffenmanager®. [ABSTRACT FROM AUTHOR]

RIVM convened a workshop on the use of New Approach Methodologies (NAMs) for the ad hoc human health risk assessment of food and non-food products. Central to the workshop were two case studies of marketed products with a potential health concern: the botanical Tabernanthe iboga which is used to facilitate mental or spiritual insight or to (illegally) treat drug addiction and is associated with cardiotoxicity, and dermal creams containing female sex hormones, intended for use by perimenopausal women to reduce menopause symptoms without medical supervision. The workshop participants recognized that data from NAM approaches added valuable information for the ad hoc risk assessment of these products, although the available approaches were inadequate to derive health-based guidance values. Recommendations were provided on how to further enhance and implement NAM approaches in regulatory risk assessment, specifying both scientific and technical aspects as well as stakeholder engagement aspects. • New Approach Methodologies (NAMs) are growing, and new technologies move away from in vivo methods. • NAMs may be used for ad hoc risk assessment of borderline products. • Extrapolation from in silico and in vitro to in vivo is the major challenge using NAMs. • A NAM-based approach for risk assessment should be protective for sensitive groups. • The pathway of regulatory acceptance of NAMs involves several stages and different stakeholders. [ABSTRACT FROM AUTHOR]

The predominantly animal-centric approach of chemical safety assessment has increasingly come under pressure. Society is questioning overall performance, sustainability, continued relevance for human health risk assessment and ethics of this system, demanding a change of paradigm. At the same time, the scientific toolbox used for risk assessment is continuously enriched by the development of "New Approach Methodologies" (NAMs). While this term does not define the age or the state of readiness of the innovation, it covers a wide range of methods, including quantitative structure–activity relationship (QSAR) predictions, high-throughput screening (HTS) bioassays, omics applications, cell cultures, organoids, microphysiological systems (MPS), machine learning models and artificial intelligence (AI). In addition to promising faster and more efficient toxicity testing, NAMs have the potential to fundamentally transform today's regulatory work by allowing more human-relevant decision-making in terms of both hazard and exposure assessment. Yet, several obstacles hamper a broader application of NAMs in current regulatory risk assessment. Constraints in addressing repeated-dose toxicity, with particular reference to the chronic toxicity, and hesitance from relevant stakeholders, are major challenges for the implementation of NAMs in a broader context. Moreover, issues regarding predictivity, reproducibility and quantification need to be addressed and regulatory and legislative frameworks need to be adapted to NAMs. The conceptual perspective presented here has its focus on hazard assessment and is grounded on the main findings and conclusions from a symposium and workshop held in Berlin in November 2021. It intends to provide further insights into how NAMs can be gradually integrated into chemical risk assessment aimed at protection of human health, until eventually the current paradigm is replaced by an animal-free "Next Generation Risk Assessment" (NGRA). [ABSTRACT FROM AUTHOR]

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA. [ABSTRACT FROM AUTHOR]

In 2007, the U.S. National Research Council (NRC) published a groundbreaking report entitled Toxicity Testing in the 21st Century: A Vision and a Strategy. The purpose of this report was to develop a long-range strategic plan to update and advance the way environmental agents are tested for toxicity. The vision focused on the identification of critical perturbations of toxicity pathways that lead to adverse human health outcomes using modern scientific tools and technologies. This review describes how emerging scientific methods will move the NRC vision forward and improve the manner in which the potential health risks associated with exposure to environmental agents are assessed. The new paradigm for toxicity testing is compatible with the widely used four-stage risk assessment framework originally proposed by the NRC in 1983 in the so-called Red Book. The Nrf2 antioxidant pathway provides a detailed example of how relevant pathway perturbations will be identified within the context of the new NRC vision for the future of toxicity testing. The implications of the NRC vision for toxicity testing for regulatory risk assessment are also discussed. [ABSTRACT FROM AUTHOR]

Dermal exposure needs to be addressed in regulatory risk assessment of chemicals. The models used so far are based on very limited data. The EU project RISKOFDERM has gathered a large number of new measurements on dermal exposure to industrial chemicals in various work situations, together with information on possible determinants of exposure. These data and information, together with some non-RISKOFDERM data were used to derive default values for potential dermal exposure of the hands for so-called ‘TGD exposure scenarios’. TGD exposure scenarios have similar values for some very important determinant(s) of dermal exposure, such as amount of substance used. They form narrower bands within the so-called ‘RISKOFDERM scenarios’, which cluster exposure situations according to the same purpose of use of the products. The RISKOFDERM scenarios in turn are narrower bands within the so-called Dermal Exposure Operation units (DEO units) that were defined in the RISKOFDERM project to cluster situations with similar exposure processes and exposure routes. Default values for both reasonable worst case situations and typical situations were derived, both for single datasets and, where possible, for combined datasets that fit the same TGD exposure scenario. The following reasonable worst case potential hand exposures were derived from combined datasets: (i) loading and filling of large containers (or mixers) with large amounts (many litres) of liquids: 11 500 mg per scenario (14 mg cm−2 per scenario with surface of the hands assumed to be 820 cm2); (ii) careful mixing of small quantities (tens of grams in <1l): 4.1 mg per scenario (0.005 mg cm−2 per scenario); (iii) spreading of (viscous) liquids with a comb on a large surface area: 130 mg per scenario (0.16 mg cm−2 per scenario); (iv) brushing and rolling of (relatively viscous) liquid products on surfaces: 6500 mg per scenario (8 mg cm−2 per scenario) and (v) spraying large amounts of liquids (paints, cleaning products) on large areas: 12 000 mg per scenario (14 mg cm−2 per scenario). These default values are considered useful for estimating exposure for similar substances in similar situations with low uncertainty. Several other default values based on single datasets can also be used, but lead to estimates with a higher uncertainty, due to their more limited basis. Sufficient analogy in all described parameters of the scenario, including duration, is needed to enable proper use of the default values. The default values lead to similar estimates as the RISKOFDERM dermal exposure model that was based on the same datasets, but uses very different parameters. Both approaches are preferred over older general models, such as EASE, that are not based on data from actual dermal exposure situations. [ABSTRACT FROM AUTHOR]

Exposure assessors involved in regulatory risk assessments often need to estimate a reasonable worst-case full-shift exposure level from very limited exposure information. Full-shift exposure data of very high quality are rare. A full-shift value can also be calculated from (short term) task based values, either derived from measured data or from models. The most simple option is to use the task based exposure levels as the full-shift value. A second option is to calculate a time-weighted average (TWA), using (reasonable worst case) estimates of the duration and the exposure level of the relevant tasks. The third option is to use a Monte Carlo analysis with estimated input distributions for exposure level and duration of exposure. If an estimated distribution of respiratory volume is also included, this leads to a distribution of inhaled amounts. The 90th percentile of such a distribution is generally substantially lower than the fixed point estimates calculated using high end values for each parameter. This technique can thus prevent unnecessary conservative estimates in risk assessment. The output distribution can also be used as valuable input to the risk management process, because it provides information on probabilities of exposure levels, that can influence the cost-benefit analysis of the risk management process. Finally, the sensitivity analysis of Monte Carlo simulation can give guidance for further studies to increase the accuracy of the exposure assessment. [ABSTRACT FROM AUTHOR]

With the Green Deal the EU aims to achieve a circular economy, restore biodiversity and reduce environmental pollution. As a part of the Green Deal a 'one-substance one-assessment' (OS-OA) approach for chemicals has been proposed. The registration and risk assessment of chemicals on the European market is currently fragmented across different legal frameworks, dependent on the chemical's use. In this review, we analysed the five main European chemical registration frameworks and their risk assessment procedures for the freshwater environment, covering 1) medicines for human use, 2) veterinary medicines, 3) pesticides, 4) biocides and 5) industrial chemicals. Overall, the function of the current frameworks is similar, but important differences exist between the frameworks' environmental protection goals and risk assessment strategies. These differences result in inconsistent assessment outcomes for similar chemicals. Chemicals are also registered under multiple frameworks due to their multiple uses, and chemicals which are not approved under one framework are in some instances allowed on the market under other frameworks. In contrast, an OS-OA will require a uniform hazard assessment between all different frameworks. In addition, we show that across frameworks the industrial chemicals are the least hazardous for the freshwater environment (median PNEC of 2.60E-2 mg/L), whilst biocides are the most toxic following current regulatory assessment schemes (median PNEC of 1.82E-4 mg/L). Finally, in order to facilitate a successful move towards a OS-OA approach we recommend a) harmonisation of environmental protection goals and risk assessment strategies, b) that emission, use and production data should be made publicly available and that data sharing becomes a priority, and c) an alignment of the criteria used to classify problematic substances. • EU registration and assessment procedures for freshwater environments were analysed. • Chemicals can be registered under multiple frameworks due to their multiple uses. • Differences between frameworks result in incoherent assessments of similar chemicals. • Recommendations for a 'one substance – one assessment' approach are given. [ABSTRACT FROM AUTHOR]

Recent advances in understanding of biological mechanisms and adverse outcome pathways for many exposure-related diseases show that certain common mechanisms involve thresholds and nonlinearities in biological exposure concentration-response (C-R) functions. These range from ultrasensitive molecular switches in signaling pathways, to assembly and activation of inflammasomes, to rupture of lysosomes and pyroptosis of cells. Realistic dose-response modeling and risk analysis must confront the reality of nonlinear C-R functions. This paper reviews several challenges for traditional statistical regression modeling of C-R functions with thresholds and nonlinearities, together with methods for overcoming them. Statistically significantly positive exposure-response regression coefficients can arise from many non-causal sources such as model specification errors, incompletely controlled confounding, exposure estimation errors, attribution of interactions to factors, associations among explanatory variables, or coincident historical trends. If so, the unadjusted regression coefficients do not necessarily predict how or whether reducing exposure would reduce risk. We discuss statistical options for controlling for such threats, and advocate causal Bayesian networks and dynamic simulation models as potentially valuable complements to nonparametric regression modeling for assessing causally interpretable nonlinear C-R functions and understanding how time patterns of exposures affect risk. We conclude that these approaches are promising for extending the great advances made in statistical C-R modeling methods in recent decades to clarify how to design regulations that are more causally effective in protecting human health. • Many causal dose-response relationships involve thresholds and nonlinearities in signaling pathways and responses. • Realistic risk assessment must deal with nonlinear exposure concentration-response (C-R) functions. • This raises challenges for traditional statistical C-R modeling, including modeling confounding, errors, and interactions. • These challenges imply that regression coefficients may not predict how reducing exposure would reduce risk. • Causal Bayesian networks, dynamic simulation models, and nonparametric regression modeling can help. [ABSTRACT FROM AUTHOR]