Regulatory Risk Assessment Of Chemicals Research Articles

Benchmark dose modeling for epidemiological dose-response assessment using prospective cohort studies.

Benchmark dose (BMD) methodology has been employed as a default dose-response modeling approach to determine the toxicity value of chemicals to support regulatory chemical risk assessment. Especially, a relatively standardized BMD analysis framework has been established for modeling toxicological data regarding the formats of input data, dose-response models, definitions of benchmark response, and model uncertainty consideration. However, the BMD approach has not been well developed for epidemiological data mainly because of the diverse designs of epidemiological studies and various formats of data reported in the literature. Although most of the epidemiological BMD analyses were developed to solve a particular question, the methods proposed in two recent studies are able to handle cohort and case-control studies using summary data with consideration of adjustments for confounders. Therefore, the purpose of the present study is to investigate and compare the "effective count"-based BMD modeling approach and adjusted relative risk (RR)-based BMD analysis approach to identify an appropriate BMD modeling framework that can be generalized for analyzing published data of prospective cohort studies for BMD analysis. The two methods were applied to the same set of studies that investigated the association between bladder and lung cancer and inorganic arsenic exposure for BMD estimation. The results suggest that estimated BMDs and BMDLs are relatively consistent; however, with the consideration of established common practice in BMD analysis, modeling adjusted RR values as continuous data for BMD estimation is a more generalizable approach harmonized with the BMD approach using toxicological data.

Developing human biomonitoring as a 21st century toolbox within the European exposure science strategy 2020-2030.

Human biomonitoring (HBM) is a crucial approach for exposure assessment, as emphasised in the European Commission's Chemicals Strategy for Sustainability (CSS). HBM can help to improve chemical policies in five major key areas: (1) assessing internal and aggregate exposure in different target populations; 2) assessing exposure to chemicals across life stages; (3) assessing combined exposure to multiple chemicals (mixtures); (4) bridging regulatory silos on aggregate exposure; and (5) enhancing the effectiveness of risk management measures. In this strategy paper we propose a vision and a strategy for the use of HBM in chemical regulations and public health policy in Europe and beyond. We outline six strategic objectives and a roadmap to further strengthen HBM approaches and increase their implementation in the regulatory risk assessment of chemicals to enhance our understanding of exposure and health impacts, enabling timely and targeted policy interventions and risk management. These strategic objectives are: 1) further development of sampling strategies and sample preparation; 2) further development of chemical-analytical HBM methods; 3) improving harmonisation throughout the HBM research life cycle; 4) further development of quality control / quality assurance throughout the HBM research life cycle; 5) obtain sustained funding and reinforcement by legislation; and 6) extend target-specific communication with scientists, policymakers, citizens and other stakeholders. HBM approaches are essential in risk assessment to address scientific, regulatory and societal challenges. HBM requires full and strong support from the scientific and regulatory domain to reach its full potential in public and occupational health assessment and in regulatory decision-making.

European stakeholders' workshop on new approach methodologies (NAMs) for developmental neurotoxicity (DNT) and their use in the regulatory risk assessment of chemicals

Characterization of potential chemical-induced developmental neurotoxicity (DNT) hazard is considered for risk assessment purposes by many regulatory sectors. To address challenging endpoints such as DNT, EFSA, in collaboration with the Organisation for Economic Co-Operation and Development (OECD), the Danish EPA and the US EPA, has been working toward the development of integrated approaches for testing and assessment (IATA) that rely on a combination of multiple layers of data (e.g. in vitro, in silico and non-mammalian in vivo models) that are supported by mechanistic knowledge organized according to the adverse outcome pathway (AOP) framework. This international effort culminated in the development of an OECD guidance on the use and interpretation of NAMs for DNT; this guidance is currently in an advanced draft status along the OECD process for approval and publication. This workshop was organized by EFSA to update European stakeholders on the progress and receive comments thereof. The workshop provided an overview of this international effort and represented an opportunity to discuss the current DNT testing paradigm and the regulatory hurdles for the implementation of DNT testing of chemicals by incorporation of a mechanistic understanding and inclusion in the regulatory process.

A Small-Scale Setup for Algal Toxicity Testing of Nanomaterials and Other Difficult Substances.

Ecotoxicity data is a requirement for pre- and post-market registration of chemicals by European and international regulations (e.g., REACH). The algal toxicity test is frequently used in regulatory risk assessment of chemicals. In order to achieve high reliability and reproducibility the development of standardized guidelines is vital. For algal toxicity testing, the guidelines require stable and uniform conditions of parameters such as pH, temperature, carbon dioxide levels and light intensity. Nanomaterials and other so-called difficult substances can interfere with light causing a large variation in results obtained hampering their regulatory acceptance. To address these challenges, we have developed LEVITATT (LED Vertical Illumination Table for Algal Toxicity Tests). The setup utilizes LED illumination from below allowing for a homogenous light distribution and temperature control while also minimizing intra-sample shading. The setup optimizes the sample volume for biomass quantification and does at the same time ensure a sufficient influx of CO2 to support exponential growth of the algae. Additionally, the material of the test containers can be tailored to minimize adsorption and volatilization. When testing colored substances or particle suspensions, the use of LED lights also allows for increasing the light intensity without additional heat generation. The compact design and minimal equipment requirements increase the possibilities for implementation of the LEVITATT in a wide range of laboratories. While compliant with standardized ISO and OECD guidelines for algal toxicity testing, LEVITATT also showed a lower inter-sample variability for two reference substances (3,5-Dicholorophenol and K2Cr2O7) and three nanomaterials (ZnO, CeO2, and BaSO4) compared to Erlenmeyer flasks and microtiter plates.

Three-Tiered Risk Assessment for Engineered Nanomaterials. A Use Case for the Semiconductor Industry

Safety of engineered nanomaterials is a new scientific field, which draws increasing attention in the literature. Among the challenges the field is facing are the insufficient amount and quality of nanotoxicological data and the ambiguity in the metrics describing the exposure. This results in substantial difficulties in the actual quantification of risk in terms of exposure limits, which is a cornerstone of the regulatory chemical risk assessment. While there is no golden standard for risk assessment and management several pragmatic systems have come into being. All of these employ some form of categorization and grouping of materials into hazard groups. This paper outlines the risk assessment approach developed within the H2020 project NanoStreeM, which is based on a combination of categorical and quantitative risk assessment tools implemented in a 3-tier system. The approach includes the use of existing tools, such as ART, Consexpo and NanoSafer, in combination with the ISO standard ISO/TS 12901-2:2014 and field measurements. The paper outlines the experience with these tools for risk assessment of typical exposure scenarios present in semiconductor manufacturing.

Introducing WikiPathways as a Data-Source to Support Adverse Outcome Pathways for Regulatory Risk Assessment of Chemicals and Nanomaterials.

A paradigm shift is taking place in risk assessment to replace animal models, reduce the number of economic resources, and refine the methodologies to test the growing number of chemicals and nanomaterials. Therefore, approaches such as transcriptomics, proteomics, and metabolomics have become valuable tools in toxicological research, and are finding their way into regulatory toxicity. One promising framework to bridge the gap between the molecular-level measurements and risk assessment is the concept of adverse outcome pathways (AOPs). These pathways comprise mechanistic knowledge and connect biological events from a molecular level toward an adverse effect outcome after exposure to a chemical. However, the implementation of omics-based approaches in the AOPs and their acceptance by the risk assessment community is still a challenge. Because the existing modules in the main repository for AOPs, the AOP Knowledge Base (AOP-KB), do not currently allow the integration of omics technologies, additional tools are required for omics-based data analysis and visualization. Here we show how WikiPathways can serve as a supportive tool to make omics data interoperable with the AOP-Wiki, part of the AOP-KB. Manual matching of key events (KEs) indicated that 67% could be linked with molecular pathways. Automatic connection through linkage of identifiers between the databases showed that only 30% of AOP-Wiki chemicals were found on WikiPathways. More loose linkage through gene names in KE and Key Event Relationships descriptions gave an overlap of 70 and 71%, respectively. This shows many opportunities to create more direct connections, for example with extended ontology annotations, improving its interoperability. This interoperability allows the needed integration of omics data linked to the molecular pathways with AOPs. A new AOP Portal on WikiPathways is presented to allow the community of AOP developers to collaborate and populate the molecular pathways that underlie the KEs of AOP-Wiki. We conclude that the integration of WikiPathways and AOP-Wiki will improve risk assessment because omics data will be linked directly to KEs and therefore allow the comprehensive understanding and description of AOPs. To make this assessment reproducible and valid, major changes are needed in both WikiPathways and AOP-Wiki.

Quality of epidemiological studies: Procedural rules for uncertain science for policy, a case study on bisphenol-A

This paper proposes a method for in-depth mapping of heterogeneity in expert judgment, in the evaluation of the quality of epidemiological studies used in regulatory chemical risk assessment. Whereas consensus in scientific advisory groups provides legitimation for subsequent political action, it can also have unintended effects on the quality of regulatory risk assessment.Based on empirical testing of our method, called Qualichem_epi, with ten experts and two epidemiological case studies about bisphenol A (BPA)’s effects on human health, we have shown that expert judgment plays an essential role in managing uncertainty and deciding what “quality” of a study actually means. We found substantial heterogeneity of scientists’ judgments about the quality of epidemiological studies, even if the same criteria were used for the assessment. This heterogeneity is not present anymore in reports produced by expert groups, where results are presented under the collective signature of all the scientists involved. We argue that flattening heterogeneity can be an important problem when it is not the result of true scientific agreement but only a secondary effect of consensus-based working procedures of agencies that experts have to follow.Qualichem_epi provides an easy to understand color-based picture of both majority and minority opinions in a scientific advisory group. We suggest that it could be used on a regular basis for communicating quality assessments of epidemiological studies in regulatory chemical risk assessment.

Evaluation of FOCUS surface water pesticide concentration predictions and risk assessment of field-measured pesticide mixtures-a crop-based approach under Mediterranean conditions.

FOCUS models are used in the European regulatory risk assessment (RA) to predict individual pesticide concentrations in edge-of-field surface waters. The scenarios used in higher tier FOCUS simulations were mainly based on Central/North European, and work is needed to underpin the validity of simulated exposure profiles for Mediterranean agroecosystems. In addition, the RA of chemicals are traditionally evaluated on the basis of single substances although freshwater life is generally exposed to a multitude of pesticides. In the present study, we monitored 19 pesticides in surface waters of five locations in the Portuguese 'Lezíria do Tejo' agricultural area. FOCUS step 3 simulations were performed for the South European scenarios to estimate predicted environmental concentrations (PECs). We verified that 44% of the PECs underestimated the measured environmental concentrations (MEC) of the pesticides, showing a non-compliance with the field data. Risk was assessed by comparing the environmental quality standards (EQS) and regulatory acceptable concentrations with their respective MECs. Risk of mixtures was demonstrated in 100% of the samples with insecticides accounting for 60% of the total risk identified. The overall link between the RA and the actual situation in the field must be considerably strengthened, and field studies on pesticide exposure and effects should be carried out to assist the improvement of predictive approaches used for regulatory purposes.

Combining web-based tools for transparent evaluation of data for risk assessment: developmental effects of bisphenol A on the mammary gland as a case study.

Different tools have been developed that facilitate systematic and transparent evaluation and handling of toxicity data in the risk assessment process. The present paper sets out to explore the combined use of two web-based tools for study evaluation and identification of reliable data relevant to health risk assessment. For this purpose, a case study was performed using in vivo toxicity studies investigating low-dose effects of bisphenol A on mammary gland development. The reliability of the mammary gland studies was evaluated using the Science in Risk Assessment and Policy (SciRAP) criteria for toxicity studies. The Health Assessment Workspace Collaborative (HAWC) was used for characterizing and visualizing the mammary gland data in terms of type of effects investigated and reported, and the distribution of these effects within the dose interval. It was then investigated whether there was any relationship between study reliability and the type of effects reported and/or their distribution in the dose interval. The combination of the SciRAP and HAWC tools allowed for transparent evaluation and visualization of the studies investigating developmental effects of BPA on the mammary gland. The use of these tools showed that there were no apparent differences in the type of effects and their distribution in the dose interval between the five studies assessed as most reliable and the whole data set. Combining the SciRAP and HAWC tools was found to be a useful approach for evaluating in vivo toxicity studies and identifying reliable and sensitive information relevant to regulatory risk assessment of chemicals. Copyright © 2016 John Wiley & Sons, Ltd.

State of the art in the application of QSAR techniques for predicting mixture toxicity in environmental risk assessment

The focus of regulatory chemical risk assessment has been mainly placed on single chemicals rather than mixtures. However, living organisms and the environment might be exposed to mixtures of chemicals. Many scientific studies have revealed that mixture toxicity can arise from the combined effects of components present at levels below their individual no-effect concentrations. Predictive approaches will be essential for estimating mixture toxicity, as the number of possible mixtures is extremely large. Although predictive models are virtually indispensable for estimating mixture toxicity for both scientific and regulatory purposes, risk assessors encounter substantial difficulties in using conventional models, mainly due to the lack of information on the modes of toxic action of the mixture constituents. Alternative models that use different information instead of the modes of action thus need to be developed. The objective of this study is to investigate the state of the art in predictive models based on quantitative structure–activity relationship techniques for estimating the toxicity of mixture components, and to identify future challenges hindering more reliable mixture risk assessment for environmental risk assessment. Alternative models need to be developed not only to overcome the limitations of conventional models, but also to improve their performance.

A systematic review of methods of uncertainty analysis and their applications in the assessment of chemical exposures, effects, and risks

Methods of uncertainty analysis are being included increasingly in regulatory chemical risk assessment. Although best practices have been established by several safety agencies in Europe and the United States, they exist only in the grey literature – there has been no comprehensive analysis of the scientific, peer-reviewed literature on these methods. We therefore conducted a systematic review of the recent peer-reviewed literature (2007–2013) on uncertainty analysis relevant to chemical risks. The main objective was to determine whether current methods are robust enough for regulatory use, because the methods used to protect public health must meet the most stringent scientific standards. Based on 297 papers, we concluded that the peer-reviewed literature is much more critical about the disadvantages of those methods, compared to the grey literature. Furthermore, uncertainty analyses can be influenced significantly by subjective expert judgment. As a suggested improvement, we developed guidelines for transparent reporting of uncertainty assessment results.

Bridging the gap between academic research and regulatory health risk assessment of Endocrine Disrupting Chemicals.

Regulatory risk assessment is traditionally based primarily on toxicity studies conducted according to standardized and internationally validated test guidelines. However, health risk assessment of endocrine disrupting chemicals (EDCs) is argued to rely on the efficient integration of findings from academic research. The aim of this review was to provide an overview of current developments to facilitate the use of academic research in regulatory risk assessment of chemicals and how certain aspects of study design and reporting are particularly important for the risk assessment process. By bridging the gap between academic research and regulatory health risk assessment of EDCs, scientific uncertainty in risk assessment conclusions can be reduced, allowing for better targeted policy decisions for chemical risk reduction.

Chemistry-wide association studies (CWAS) to determine joint toxicity effects of co-occurring chemical features

Individual structural alerts often fail to accurately predict chemical toxicity as they tend to overlook the moderating effects of other co-occurring alerts. Features are said to have statistical interaction effects when one changes or modulates the effect of another on the target property. Here we introduce Chemistry-Wide Association Study (CWAS; by analogy with GWAS in genomics) to systematically elicit the individual and interaction effects of chemical features on the target property. A mutagenicity dataset of 5,439 compounds was used in this proof-of-concept study. We utilized QSAR models built with random forest and ISIDA fragment descriptors to select the most important chemical features and identify pairs of features with significant interaction effects. These interacting feature pairs revealed how subtle structural changes affect mutagenicity (e.g., ortho-substitution reduces mutagenicity caused by nitroarene moiety). We also found that feature pairs can be integrated into more specific structural alerts with fewer false positives. We believe the interaction effects uncovered by CWAS are useful for refining structural alerts and enhancing model interpretation, enabling more effective design of safe chemical substances and leading to the improved regulatory chemical risk assessment.

The OSIRIS Weight of Evidence approach: ITS for skin sensitisation

Within the EU FP6 project OSIRIS approaches to Integrated Testing Strategies (ITSs) were developed, with the aim to facilitate the use of non-test and non-animal testing information in regulatory risk assessment of chemicals. This paper describes an analytical Weight-of-Evidence (WoE) approach to an ITS for the endpoint of skin sensitisation. It specifically addresses the European chemicals legislation REACH, but the concept is readily applicable to ITS and WoE procedures in other regulatory frameworks, and for other toxicological endpoints. Bayesian statistics are applied to estimate the reliability of a conclusion on the sensitisation potential of a chemical, combining evidence from different information sources such as QSAR model predictions, in vitro and in vivo test results. The methodology allows for adaptation of the weight of individual information sources to account for the different levels of reliability of the individual ITS components. The calculated reliability of the WoE conclusion gives an objective, transparent and reproducible measure to decide if the information requirements for data evaluation are satisfied. Furthermore, in case the WoE is not sufficient, it gives the possibility to evaluate a priori if and how it will be possible to fulfil the information requirements with additional tests and/or model predictions.

Guidance: P21: The UK interdepartmental group on health risks from chemicals: Providing guidance for regulatory chemical risk assessment

The Interdepartmental Group on Health Risks from Chemicals (IGHRC) comprises participants from UK government departments, agencies and research councils with an interest in the assessment of potential human health risks from exposure to chemicals. The aim of the IGHRC is to reduce uncertainties and inconsistencies in the assessment of risks across regulatory sectors including direct exposure of workers in their jobs, of the general public from use of the chemical in a medicine or consumer product, and indirect exposure from environmental contamination. The IGHRC seeks to stimulate the development of new and improved approaches to the assessment of risks to human health from chemicals through the sharing of experiences and the development and publication of transparent reports and guidance documents. Since 1999, 14 reports 1 have been published by the IGHRC and its predecessor, the Risk Assessment and Toxicology Steering Committee (RATSC), addressing a wide range of issues relevant to chemical risk assessment and human health. The most recent of these are Guidelines on Route-to-Route Extrapolation of Toxicity Data, which provides guidance on the extrapolation of toxicity data obtained from one route to other routes of exposure, and Chemical Mixtures: a Framework for Assessing Risks to Human Health, which provides a stepwise approach for the risk assessment of chemical mixtures. IGHRC also organises regular workshops and training courses for member departments and agencies on subject areas including epidemiology, exposure assessment and risk communication. The IGHRC Committees have developed a new three-year work programme encompassing production of published reports, and will in the future provide more training opportunities open to non-IGHRC participants. Details of the programme, along with the outputs and achievements of previous phases, are described in Final Report for Phase 2 and Future Plan for Phase 3. New training courses and reports will include the development of new techniques relevant to REACH.

Task-based Dermal Exposure Models for Regulatory Risk Assessment

The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of new measurements of dermal exposure together with detailed contextual information. This article describes the development of a set of generic task-based models capable of predicting potential dermal exposure to both solids and liquids in a wide range of situations. To facilitate modelling of the wide variety of dermal exposure situations six separate models were made for groupings of exposure scenarios called Dermal Exposure Operation units (DEO units). These task-based groupings cluster exposure scenarios with regard to the expected routes of dermal exposure and the expected influence of exposure determinants. Within these groupings linear mixed effect models were used to estimate the influence of various exposure determinants and to estimate components of variance. The models predict median potential dermal exposure rates for the hands and the rest of the body from the values of relevant exposure determinants. These rates are expressed as mg or microl product per minute. Using these median potential dermal exposure rates and an accompanying geometric standard deviation allows a range of exposure percentiles to be calculated.

Default Values for Assessment of Potential Dermal Exposure of the Hands to Industrial Chemicals in the Scope of Regulatory Risk Assessments

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 cm(2)); (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.

OMNIITOX concept model supports characterisation modelling for life cycle impact assessment

Goal Scope Background The main focus in OMNIITOX is on characterisation models for toxicological impacts in a life cycle assessment (LCA) context. The OMNIITOX information system (OMNIITOX IS) is being developed primarily to facilitate characterisation modelling and calculation of characterisation factors to provide users with information necessary for environmental management and control of industrial systems. The modelling and implementation of operational characterisation models on eco and human toxic impacts requires the use of data and modelling approaches often originating from regulatory chemical risk assessment (RA) related disciplines. Hence, there is a need for a concept model for the data and modelling approaches that can be interchanged between these different contexts of natural system model approaches. Methods. The concept modelling methodology applied in the OMNIITOX project is built on database design principles and ontological principles in a consensus based and iterative process by participants from the LCA, RA and environmental informatics disciplines. Results. The developed OMNIITOX concept model focuses on the core concepts of substance, nature framework, load, indicator, and mechanism, with supplementary concepts to support these core concepts. They refer to the modelled cause, effect, and the relation between them, which are aspects inherent in all models used in the disciplines within the scope of OMNIITOX. This structure provides a possibility to compare the models on a fundamental level and a language to communicate information between the disciplines and to assess the possibility of transparently reusing data and modelling approaches of various levels of detail and complexity.

Improved use of workplace exposure data in the regulatory risk assessment of chemicals within Europe.

The process of risk assessment for human health demands the availability of soundly based effects and exposure information. However, many of the available data, particularly those which seek to describe human exposures to chemicals, are of varying quality and scope. Changing public and regulatory expectations increasingly demand that the outcomes of risk assessments are seen to have duly accounted for these data, in order that their conclusions can be viewed as valid. The challenge for risk assessors, therefore, is how the different grades of data should be integrated within the overall process. A series of core values are identified that govern the relationships and the influence that different types of exposure data have within European Union (EU) regulatory risk assessment for chemicals. Building on these values, an approach is presented for evaluating workplace exposure information in the context of how such data might be used within the EU process for assessing the risks to human health of new and existing substances. The implications of adopting the approach for regulatory risk assessment within the EU and its consequent impact on current occupational hygiene practice are discussed.