Testing the Applicability of the Safe-by-Design Concept: A Theoretical Case Study Using Polymer Nanoclay Composites for Coffee Capsules

The production and use of engineered nanomaterials and nano-enabled products is increasing, enabling innovations in many application areas, e.g., in the sector of food contact materials. However, nanosafety-relevant information for chemical risk assessment is still scarce, leading to a high level of uncertainty and making the early integration of safety to the innovation process indispensable. This study analyzed the strengths, weaknesses, and applicability of the nano-specific Safe-by-Design (SbD) concept using nanoclay-containing polymer coffee capsules as a theoretical case study. In addition, a material flow analysis was conducted to identify exposure pathways and potential risks, and a multi-stakeholder approach was applied to discursively discuss challenges when attempting to combine safety and innovation at an early stage. The results indicate that the SbD concept is generally welcomed by all stakeholders, but there is a lack of clear rules on the transfer of information between the actors involved. Furthermore, a voluntary, practical application usually requires in-depth knowledge of nanotechnology and often additional financial efforts. Therefore, incentives need to be created, as there is currently no obvious added value from a company’s point of view. The SbD concept should be further developed, standardized, and integrated into existing legal frameworks to be implemented effectively.

Role of epidemiology in risk assessment: a case study of five ortho-phthalates

Background The association between environmental chemical exposures and chronic diseases is of increasing concern. Chemical risk assessment relies heavily on pre-market toxicity testing to identify safe levels of exposure, often known as reference doses (RfD), expected to be protective of human health. Although some RfDs have been reassessed in light of new hazard information, it is not a common practice. Continuous surveillance of animal and human data, both in terms of exposures and associated health outcomes, could provide valuable information to risk assessors and regulators. Using ortho-phthalates as case study, we asked whether RfDs deduced from male reproductive toxicity studies and set by traditional regulatory toxicology approaches sufficiently protect the population for other health outcomes. Methods We searched for epidemiological studies on benzyl butyl phthalate (BBP), diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), dicyclohexyl phthalate (DCHP), and bis(2-ethylhexyl) phthalate (DEHP). Data were extracted from studies where any of the five chemicals or their metabolites were measured and showed a statistically significant association with a health outcome; 38 studies met the criteria. We estimated intake for each phthalate from urinary metabolite concentration and compared estimated intake ranges associated with health endpoints to each phthalate’s RfD. Result For DBP, DIBP, and BBP, the estimated intake ranges significantly associated with health endpoints were all below their individual RfDs. For DEHP, the intake range included associations at levels both below and above its RfD. For DCHP, no relevant studies could be identified. The significantly affected endpoints revealed by our analysis include metabolic, neurodevelopmental and behavioral disorders, obesity, and changes in hormone levels. Most of these conditions are not routinely evaluated in animal testing employed in regulatory toxicology. Conclusion We conclude that for DBP, DIBP, BBP, and DEHP current RfDs estimated based on male reproductive toxicity may not be sufficiently protective of other health effects. Thus, a new approach is needed where post-market exposures, epidemiological and clinical data are systematically reviewed to ensure adequate health protection.

ELIXIR and Toxicology: a community in development

Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities.

Weight of Evidence for the Microplastic Vector Effect in the Context of Chemical Risk Assessment

The concern that in nature, ingestion of microplastic (MP) increases exposure of organisms to plastic-associated chemicals (the ‘MP vector effect’) plays an important role in the current picture of the risks of microplastic for the environment and human health. An increasing number of studies on this topic have been conducted using a wide variety of approaches and techniques. At present, the MP vector effect is usually framed as ‘complex’, ‘under debate’ or ‘controversial’. Studies that critically discuss the approaches and techniques used to study the MP vector effect, and that provide suggestions for the harmonization needed to advance this debate, are scarce. Furthermore, only a few studies have strived at interpreting study outcomes in the light of environmentally relevant conditions. This constitutes a major research gap, because these are the conditions that are most relevant when informing risk assessment and management decisions. Based on a review of 61 publications, we propose evaluation criteria and guidance for MP vector studies and discuss current study designs using these criteria. The criteria are designed such that studies, which fulfil them, will be relevant to inform risk assessment. By critically reviewing the existing literature in the light of these criteria, a weight of evidence assessment is provided. We demonstrate that several studies did not meet the standards for their conclusions on the MP vector effect to stand, whereas others provided overwhelming evidence that the vector effect is unlikely to affect chemical risks under present natural conditions.

Carcinogenic and non-carcinogenic health risk assessment of air pollutant in a steel industry

Background: Chemical risk assessment is one of the major strategies that can help prioritize hazardous pollutants and decide on appropriate control measures. Objective: This study aim was evaluating carcinogenic and non-carcinogenic effects of chemical and fume compounds in a steel industry in South Iran. Methods: This study conducted in one of the steel industry with 1600 workers. After sampling the inhalation air of workers exposed to various chemicals, the method provided by risk assessment information system (RAIS) was used to assess cancer carcinogenic and non-Carcinogenic risk based on the findings. Results: Asbestos with the content of 1.5×10-10, chromium 1.36×10-2, and lead 5.38×10-5 definitive cancer and definite cancer are in the category of minor cancer effects, respectively. In calculating the non-cancer risk, the risk factor for Quotient Hazard Non-cancer (HQ) in hydrogen sulfide, chromium, and manganese were 3.08×102, 5.71×10-2, and 9.13×102 respectively, indicating non-cancer risk in them. Conclusion: Based on the values provided by the environmental protection agency, it is observed that some pollutants in the steel industry during the study period will increase the risk of cancer and non-cancerous diseases for steel industry workers. Therefore, considering appropriate engineering and management controls can help prevent these effects. Keywords: Carcinogenic risk, Chemical contaminants, Non-carcinogenic risk.

Construction of Mode of Action for Cadmium-Induced Renal Tubular Dysfunction Based on a Toxicity Pathway-Oriented Approach

Although it is recognized that cadmium (Cd) causes renal tubular dysfunction, the mechanism of Cd-induced nephrotoxicity is not yet fully understood. Mode of action (MOA) is a developing tool for chemical risk assessment. To establish the mechanistic MOA of Cd-induced renal tubular dysfunction, the Comparative Toxicogenomics Database (CTD) was used to obtain genomics data of Cd-induced nephrotoxicity, and Ingenuity® Pathway Analysis (IPA) software was applied for bioinformatics analysis. Based on the perturbed toxicity pathways during the process of Cd-induced nephrotoxicity, we established the MOA of Cd-induced renal tubular dysfunction and assessed its confidence with the tailored Bradford Hill criteria. Bioinformatics analysis showed that oxidative stress, DNA damage, cell cycle arrest, and cell death were the probable key events (KEs). Assessment of the overall MOA of Cd-induced renal tubular dysfunction indicated a moderate confidence, and there are still some evidence gaps to be filled by rational experimental designs.

AI for predicting chemical-effect associations at the universe level - deepFPlearn

A plethora of chemical substances is out there in our environment, and all living species, including us humans, are exposed to various mixtures of these. Our society is accustomed to developing, producing, using and dispersing a diverse and vast amount of chemicals with the original intention to improve our standard of living. However, many chemicals pose risks, for example of developing severe diseases, if they occur at the wrong time in the wrong place. For the majority of the chemicals these risks are not known. Chemical risk assessment and subsequent regulation of use requires efficient and systematic strategies, which are not available so far. Experimental methods, even those of high-throughput, are still lab based and therefore too slow to keep up with the pace of chemical innovation.Existing computational approaches, e.g. ML based, are powerful on specific chemical classes, or sub-problems, but not applicable on a large scale. Their main limitation is the lack of applicability to chemicals outside the training data and the availability of sufficient amounts of training data. Here, we present the ready-to-use and stand-alone program deepFPlearn that predicts the association between chemical structures and effects on the gene/pathway level using deep learning. We show good performance values for our trained models, and demonstrate that our program can predict meaningful associations of chemicals and effects beyond the training range due to the application of a sophisticated feature compression approach using a deep autoencoder. Further, it can be applied to hundreds of thousands of chemicals in seconds. We provide deepFPlearn as open source and flexible tool that can be easily retrained and customized to different application settings at https://github.com/yigbt/deepFPlearn.