Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects.

Chemical points of departure (PODs) for critical health effects are crucial for evaluating and managing human health risks and impacts from exposure. However, PODs are unavailable for most chemicals in commerce due to a lack of in vivo toxicity data. We therefore developed a two-stage machine learning (ML) framework to predict human-equivalent PODs for oral exposure to organic chemicals based on chemical structure. Utilizing ML-based predictions for structural/physical/chemical/toxicological properties from OPERA 2.9 as features (Stage 1), ML models using random forest regression were trained with human-equivalent PODs derived from in vivo data sets for general noncancer effects (n = 1,791) and reproductive/developmental effects (n = 2,228), with robust cross-validation for feature selection and estimating generalization errors (Stage 2). These two-stage models accurately predicted PODs for both effect categories with cross-validation-based root-mean-squared errors less than an order of magnitude. We then applied one or both models to 34,046 chemicals expected to be in the environment, revealing several thousand chemicals of moderate concern and several hundred chemicals of high concern for health effects at estimated median population exposure levels. Further application can expand by orders of magnitude the coverage of organic chemicals that can be evaluated for their human health risks and impacts.

Public views of animal testing and alternatives in chemical risk assessment.

Next-Generation Risk Assessment (NGRA) aims to implement New Approach Methodologies (NAMs) into risk assessment and to rely on new in vivo testing in animals only as a last resort. However, various technical and regulatory hurdles impede their regulatory implementation. Assumptions about the public's expectations could act as barriers to the acceptance of NAMs. This study aimed at investigating public views of animal testing and potential alternatives, namely in vitro and in silico testing. An online survey was conducted (N = 965). The results suggest that people make trade-offs, as they experience negative affect regarding in vivo testing, which partly might explain their openness regarding certain alternatives. In vitro tests were attributed the highest ability to determine harmful effects of chemicals for different endpoints, followed by in vivo and in silico tests. Our results further showed that many people accept chemicals to be only tested with alternatives, with highest acceptance for household consumer products, food contact material or building materials and less accepting for medicines and foods. This article addresses potential challenges that might arise from public perceptions and thus, contributes to the bottom-up initiatives to overcome the hurdles to the implementation of NAMs in regulatory risk assessment.

The new normal chemical landscape: the future of risk assessment toward optimum consumer safety.

The further optimization of consumer safety through risk assessment of chemicals present in food will require adaptability and flexibility to utilize the accelerating developments in safety science and technology. New Approach Methodologies (NAMs) are gaining traction as a systematic approach to support informed decision making in chemical risk assessment. The vision is to be able to predict risk more accurately, rapidly and efficiently. The opportunity exists now to use these approaches which requires a strategy to translate the science into future regulatory implementation. Here we discuss new insights obtained from three recent workshops on how to translate the science into future regulatory implementation. To assist the UK in this endeavor, the Food Standards Agency (FSA) and the scientific advisory committee on chemical toxicity (COT) have been developing a roadmap. In addition, we discuss how these new insights fit into the bigger picture of the new chemical landscape for better consumer safety and the importance of international harmonization.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment.

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Intuitive toxicology in the 21st century-Bridging the perspectives of the public and risk assessors in Europe.

Three decades ago, several articles on the subjectivity in chemical risk judgments (i.e., labeled "intuitive toxicology") measured the divide between the public and toxicologists with different backgrounds regarding the validity of predicting health effects based on in vivo studies. Similar divides with impacts on societal discourse and chemical risk assessment practices might exist concerning alternative toxicity testing methods (i.e., in vitro and in silico). However, studies to date have focused either on the public's views of in vivo or stem cell testing or on experts' views of in vivo testing and potential alternatives (i.e., toxicologists and medical students), which do not allow for a direct investigation of potential divides. To fill this knowledge gap, we conducted two online surveys, involving members of the German-speaking public in Switzerland and European human health risk assessors, respectively. This article presents the results of these two surveys regarding the divide in the public's and risk assessors' perspectives on risk assessment based on in vivo, in vitro, and in silico testing. Particularly, the survey with the risk assessors highlights that, beyond scientific and regulatory barriers, alternatives to in vivo testing may encounter individual hurdles, such as higher uncertainty associated with them. Understanding and addressing these hurdles will be crucial to facilitate the integration of new approach methodologies into chemical risk assessment practices as well as a successful transition toward next-generation risk assessment, bringing us closer to a fit-for-purpose and more efficient regulatory landscape.

Human biomonitoring and toxicokinetics as key building blocks for next generation risk assessment.

Human health risk assessment is historically built upon animal testing, often following Organisation for Economic Co-operation and Development (OECD) test guidelines and exposure assessments. Using combinations of human relevant in vitro models, chemical analysis and computational (in silico) approaches bring advantages compared to animal studies. These include a greater focus on the human species and on molecular mechanisms and kinetics, identification of Adverse Outcome Pathways and downstream Key Events as well as the possibility of addressing susceptible populations and additional endpoints. Much of the advancement and progress made in the Next Generation Risk Assessment (NGRA) have been primarily focused on new approach methodologies (NAMs) and physiologically based kinetic (PBK) modelling without incorporating human biomonitoring (HBM). The integration of toxicokinetics (TK) and PBK modelling is an essential component of NGRA. PBK models are essential for describing in quantitative terms the TK processes with a focus on the effective dose at the expected target site. Furthermore, the need for PBK models is amplified by the increasing scientific and regulatory interest in aggregate and cumulative exposure as well as interactions of chemicals in mixtures. Since incorporating HBM data strengthens approaches and reduces uncertainties in risk assessment, here we elaborate on the integrated use of TK, PBK modelling and HBM in chemical risk assessment highlighting opportunities as well as challenges and limitations. Examples are provided where HBM and TK/PBK modelling can be used in both exposure assessment and hazard characterization shifting from external exposure and animal dose/response assays to animal-free, internal exposure-based NGRA.

Chemical Variations Induced by Ozonization of 5% Glucose Solution and Evaluation of Generated Compounds.

The most commonly studied method of administering ozone therapy is systemic ozone therapy. However, there may be situations where this method is not feasible due to technical issues, such as poor vein condition or anemia. As an alternative method, pre-ozonized solutions, such as 0.9% saline solution, have been investigated for their ease of preparation and administration. However, concerns have been raised regarding the formation of chlorine compounds. Currently, there is no available literature on the treatment potential of pre-ozonized glucose solution. The objective of this study is to compare and evaluate the chemical changes induced by ozonization of a 5% glucose solution and determine if any toxic compounds are produced. Our findings indicate that the chemical alterations following ozone infusion are quantitatively minimal and pose a negligible risk in terms of safety.

Integrating emerging science to improve estimates of risk to wildlife from chemical exposure: What are the challenges?

Many jurisdictions require ecological risk assessments for terrestrial wildlife (i.e., terrestrial vertebrates) to assess potential adverse effects from exposure to anthropogenic chemicals. This occurs, for example, at contaminated sites and when new pesticides are proposed, and it occurs for chemicals that are in production and/or proposed for wide-scale use. However, guidance to evaluate such risks has not changed markedly in decades, despite the availability of new scientific tools to do so. In 2019, the Wildlife Toxicology World Interest Group of the Society of Environmental Toxicology and Chemistry (SETAC) initiated a virtual workshop that included a special session coincident with the annual SETAC North America meeting and which focused on the prospect of improving risk assessments for wildlife and improving their use in implementing chemical regulations. Work groups continued the work and investigated the utility of integrating emerging science and novel methods for improving problem formulation (WG1), exposure (WG2), toxicology (WG3), and risk characterization (WG4). Here we provide a summary of that workshop and the follow-up work, the regulations that drive risk assessment, and the key focus areas identified to advance the ability to predict risks of chemicals to wildlife. Integr Environ Assess Manag 2024;20:645-657. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

The role of trust in the use of artificial intelligence for chemical risk assessment.

Risk assessment of chemicals is a time-consuming process and needs to be optimized to ensure all chemicals are timely evaluated and regulated. This transition could be stimulated by valuable applications of in silico Artificial Intelligence (AI)/Machine Learning (ML) models. However, implementation of AI/ML models in risk assessment is lagging behind. Most AI/ML models are considered 'black boxes' that lack mechanistical explainability, causing risk assessors to have insufficient trust in their predictions. Here, we explore 'trust' as an essential factor towards regulatory acceptance of AI/ML models. We provide an overview of the elements of trust, including technical and beyond-technical aspects, and highlight elements that are considered most important to build trust by risk assessors. The results provide recommendations for risk assessors and computational modelers for future development of AI/ML models, including: 1) Keep models simple and interpretable; 2) Offer transparency in the data and data curation; 3) Clearly define and communicate the scope/intended purpose; 4) Define adoption criteria; 5) Make models accessible and user-friendly; 6) Demonstrate the added value in practical settings; and 7) Engage in interdisciplinary settings. These recommendations should ideally be acknowledged in future developments to stimulate trust and acceptance of AI/ML models for regulatory purposes.

The upcoming European Soil Monitoring Law: An effective instrument for the protection of terrestrial ecosystems?

Soils are a precious resource consistently placed under several threats and urgently in need of protection within a regulatory framework at the European level. Soils are central to the provision of environmental services as well as human existence on earth. The need to protect soil has been identified by several recent European strategies and fortunately, a specific European regulation for soil protection is on the way-the European Soil Monitoring Law (formerly: Soil Health Law). However, efforts need to ensure that the upcoming Soil Monitoring Law closes gaps between existing regulations for chemicals and acknowledges current European strategies for environmental protection and sustainability. This brief communication started from a fruitful discussion among SETAC Global Soils Interest Group members on a recent public consultation on the newly proposed Soil Monitoring Law of the European Commission and highlights critical points focusing on the chemical pollution of soils. We emphasize urgent needs such as the essential definition of a "healthy state" of soils; the implementation of a suitable set of indicators and quality standards for the description of physical, chemical, and biological states of soils; the enforcement of the "polluter-pays" principle; and the establishment of a Europe-wide monitoring program. Results from monitoring need to be fed back into regulatory frameworks, including the regulation of chemicals. Guidance documents for the risk assessment of chemicals are outdated and need to be updated. Finally, actions need to be taken to foster healthy soils, stop biodiversity decline, and ensure the functioning of ecosystem services for future generations. Integr Environ Assess Manag 2024;20:316-321. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Assessment of persistent organic pollutants in killer whales (Orcinus orca) of the Canadian Arctic: Implications for subsistence consumption and conservation strategies.

Killer whales (Orcinus orca) historically restricted to certain Arctic regions due to extensive sea ice have recently been documented farther north and for longer durations in the Canadian Arctic. These apex predators accumulate high levels of persistent organic pollutants (POPs). The objective of this study was to evaluate the concentrations and profiles of POPs in killer whales of the Canadian Arctic, thus determining potential risks for Inuit communities if consumed. Biopsies were collected from 33 killer whales across areas of the Canadian Arctic between 2009 and 2021. Significant variability in POP concentrations was observed among whales. The cumulative POP concentrations ranged from 12 to >2270 mg/kg lw, representing ∼200-fold increase from the least to the most contaminated individual. The rank order of concentrations of the top five contaminant classes was ∑DDT, ∑PCB, ∑CHL, ∑Toxaphene, and Dieldrin. Several emerging Arctic contaminants were detected, including chlorpyrifos, endosulfan, pentachloroanisole, and polychlorinated naphthalenes, although at relatively lower concentrations than legacy POPs. Considering the elevated blubber POP levels in killer whales, recommended daily consumption thresholds, established based on human tolerable daily intake (TDI) values, were notably restricted for ∑PCB (<0.14 g), ∑DDT (<6.9 g), ∑CHL (<13 g), dieldrin (<8 g) and heptachlor epoxide (<5 g). Killer whales in the Canadian Arctic exhibited higher POP concentrations than other commonly hunted species such as polar bears, ringed seals, and Arctic char. We acknowledge that a more holistic risk assessment of diet is required to assess the cumulative impacts of contaminant mixtures as well as nutritional quality of tissues commonly consumed by northern communities.

A control banding method for chemical risk assessment in occupational settings in France.

Background: This study describes a method whose aim is to help companies assess the chemical occupational risks related to labeled products and industrial chemical emissions. The method is intended to be used by industrial hygienists at the scale of one company. Both inhalation and cutaneous exposure routes are taken into account. Methods: The method relies on a control-banding scheme. A work situation is described by exposure parameters such as the process or the local exhaust ventilation and by the hazard of the product. Each possible value of the parameters is associated with a "band," which is associated with an integer value. The multiplication of these values results in a score, which represents a priority for intervention. The higher the score, the more the situation warrants investigation for implementing prevention measures, such as chemical substitution and the addition of local exhaust ventilation. To simplify communication, the priority is associated with a colored priority band: red for "very high priority," orange for "high priority," and green for "moderate priority." The priority bands are computed for all work situations performed in a company. Results: An example of the use of this method is described in a French façade insulation company. Conclusion: A tool named Seirich was developed to implement this method and promote good practices for helping industrial hygienists in the prioritization of interventions for reducing chemical risk in France.

Identifying factors that inhibit or facilitate on-site implementation of chemical risk assessment at small and medium-sized companies.

The introduction and implementation of chemical risk assessment is difficult, especially at small and medium-sized manufacturing and construction companies. This study aimed to identify the factors that inhibit or facilitate such assessment. Twelve individuals in charge of risk assessment at one medium-sized client company and eight small and medium-sized contract companies and responsible for innovation in the manufacturing and construction industries were interviewed. The interview transcripts were analyzed via text mining using KH Corder ver. 3 and a co-occurrence network was used to identify the keywords' connections and each factor in consideration of the interviews. Six factors inhibited or facilitated risk assessment: (1) education on hazardous work in the workplace, (2) improvement suggestions and reduction measures from client and staff, (3) cooperation between employees and contractors in the workplace, (4) thoroughly explanation of SDS content for better understanding, (5) risk awareness based on accident examples, and (6) difficulties imagining the hazards of chemical substances. Factors (1), (2), (3), and (5) were positive, facilitating factors; (4) and (6) were negative, inhibiting factors. This study highlights that it is necessary to educate workers about chemical substance risks using safety data sheets and accident examples in chemical risk assessment.

Quantitative assessment of human health risks from chemical pollution in the uMsunduzi River, South Africa.

A quantitative chemical risk assessment was performed using published data as well as data from the official monitoring programme for the uMsunduzi River in KwaZulu-Natal, South Africa. The chemicals assessed were organochlorinated pesticides (OCPs), pharmaceuticals and personal care products (PPCPs), heavy metals, and nitrates and phosphates. The water from uMsunduzi River is used locally without treatment. Consequently, the exposure routes investigated were via ingestion during domestic drinking and incidental ingestion during recreational activities, which were swimming and non-competitive canoeing, for both adults and children. For the individual chemicals, non-carcinogenic risks using the hazard quotient (HQ) and carcinogenic risks using the cancer risk (CR) were quantified. It was found that the exposed population is likely to experience non-carcinogenic effects from pesticides and phosphates, but not from PPCPs, heavy metals and nitrates. This study also found that the carcinogenic risks for OCPs were higher than the tolerable limit of 10-5, while for lead the risk was below the tolerable limit. Some of the activities that potentially contribute to chemicals onto the uMsunduzi River are subsistence farming, small plantations, illegal dumping, industries, and broken sewers. The findings of this study may act as the technical foundation for the introduction of pollution reduction measures within the catchment, including public education.

Background radiation and cancer risks: A major intellectual confrontation within the domain of radiation genetics with multiple converging biological disciplines.

This paper assesses the judgments of leading radiation geneticists and cancer risk assessment scientists from the mid-1950s to mid-1970s that background radiation has a significant effect on human genetic disease and cancer incidence. This assumption was adopted by the National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Genetics Panel for genetic diseases and subsequently applied to cancer risk assessment by other leading individuals/advisory groups (e.g., International Commission on Radiation Protection-ICRP). These recommendations assumed that a sizeable proportion of human mutations originated from background radiation due to cumulative exposure over prolonged reproductive periods and the linear nature of the dose-response. This paper shows that the assumption that background radiation is a significant cause of spontaneous mutation, genetic diseases, and cancer incidence is not supported by experimental and epidemiological findings, and discredits erroneous risk assessments that improperly influenced the recommendations of national and international advisory committees, risk assessment policies, and beliefs worldwide.

Implementing comprehensive machine learning models of multispecies toxicity assessment to improve regulation of organic compounds.

Machine learning has made significant progress in assessing the risk associated with hazardous chemicals. However, most models were constructed by randomly selecting one algorithm and one toxicity endpoint towards single species, which may cause biased regulation of chemicals. In the present study, we implemented comprehensive prediction models involving multiple advanced machine learning and end-to-end deep learning to assess the aquatic toxicity of chemicals. The generated optimal models accurately unravel the quantitative structure-toxicity relationships, with the correlation coefficients of all training sets from 0.59 to 0.81 and of the test sets from 0.56 to 0.83. For each chemical, its ecological risk was determined from the toxicity information towards multiple species. The results also revealed the toxicity mechanism of chemicals was species sensitivity, and the high-level organisms were faced with more serious side effects from hazardous substances. The proposed approach was finally applied to screen over 16,000 compounds and identify high-risk chemicals. We believe that the current approach can provide a useful tool for predicting the toxicity of diverse organic chemicals and help regulatory authorities make more reasonable decisions.

OECD harmonised template 201: Structuring and reporting mechanistic information to foster the integration of new approach methodologies for hazard and risk assessment of chemicals.

In the European Union, the Chemicals Strategy for Sustainability (CSS) highlights the need to enhance the identification and assessment of substances of concern while reducing animal testing, thus fostering the development and use of New Approach Methodologies (NAMs) such as in silico, in vitro and in chemico. In the United States, the Tox21 strategy aims at shifting toxicological assessments away from traditional animal studies towards target-specific, mechanism-based and biological observations mainly obtained by using NAMs. Many other jurisdictions around the world are also increasing the use of NAMs. Hence, the provision of dedicated non-animal toxicological data and reporting formats as a basis for chemical risk assessment is necessary. Harmonising data reporting is crucial when aiming at re-using and sharing data for chemical risk assessment across jurisdictions. The OECD has developed a series of OECD Harmonised Templates (OHT), which are standard data formats designed for reporting information used for the risk assessment of chemicals relevant to their intrinsic properties, including effects on human health (e.g., toxicokinetics, skin sensitisation, repeated dose toxicity) and the environment (e.g., toxicity to test species and wildlife, biodegradation in soil, metabolism of residues in crops). The objective of this paper is to demonstrate the applicability of the OHT standard format for reporting information under various chemical risk assessment regimes, and to provide users with practical guidance on the use of OHT 201, in particular to report test results on intermediate effects and mechanistic information.

Understanding the limitations and application of occupational exposure models in a REACH context.

Exposure modeling plays a significant role for regulatory organizations, companies, and professionals involved in assessing and managing occupational health risks in workplaces. One context in which occupational exposure models are particularly relevant is the REACH Regulation in the European Union (Regulation (EC) No 1907/2006). This commentary describes the models for the occupational inhalation exposure assessment of chemicals within the REACH framework, their theoretical background, applications, and limitations, as well as the latest developments and priorities for model improvement. Summing up the debate, despite its relevance and importance in the context of REACH not being in question, occupational exposure modeling needs to be improved in many respects. There is a need to reach a wide consensus on several key issues (e.g., the theoretical background and the reliability of modeling tools), to consolidate and monitor model performance and regulatory acceptance, and to align practices and policies regarding exposure modeling.

Risk assessment of chemicals and their mixtures are hindered by scarcity and inconsistencies between different environmental exposure limits.

In chemical risk assessment, measured or modelled environmental concentrations are compared to environmental exposure limits (EELs), such as Predicted No Effect Concentrations (PNECs) or hazardous concentrations for 5% of species (HC05s) derived from species sensitivity distributions (SSDs). However, for many chemicals the EELs include large uncertainties or, in the worst case, the necessary data for their estimation are completely missing. This makes the assessment of chemical risks and any subsequent implementation of management strategies challenging. In this study we analyzed the uncertainty of EELs and its impact on chemical risk assessment. First, we compared three individual EEL datasets, two primarily based on experimental data and one based on computational predictions. The comparison demonstrates large disagreements between EEL data sources, with experimentally derived EELs differing by more than seven orders of magnitude. In a case-study, based on the predicted emissions of 2005 chemicals, we showed that these uncertainties lead to significantly different risk assessment outcomes, including large differences in the magnitude of the total risk, risk driver identification, and the ranking of use categories as risk contributors. We also show that the large data-gaps in EEL datasets cannot be covered by commonly used computational approaches (QSARs). We conclude that an expanded framework for interpreting risk characterization outcomes is needed. We also argue that the large data-gaps present in ecotoxicological data need to be addressed in order to achieve the European zero pollution vision as the growing emphasis on ambient exposures will further increase the demand for accurate and well-established EELs.

Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line.

Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B1, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B1, benzo[a]pyrene, cyclosporin A: from 0.2048 µM to 50 µM; rotenone: from 0.04096 to 10 µM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.