Several reviews of synergisms and antagonisms in chemical mixtures have concluded that synergisms are relatively rare. However, these reviews focused on mixtures composed of specific groups of chemicals, such as pesticides or metals and on toxicity endpoints mostly relevant to ecotoxicology. Doubts remain whether these findings can be generalised. A systematic review not restricted to specific chemical mixtures and including mammalian and human toxicity endpoints is missing. We conducted a systematic review and quantitative reappraisal of 10 years' of experimental mixture studies to investigate the frequency and reliability of evaluations of mixture effects as synergistic or antagonistic. Unlike previous reviews, we did not limit our efforts to certain groups of chemicals or specific toxicity outcomes and covered mixture studies relevant to ecotoxicology and human/mammalian toxicology published between 2007 and 2017. We undertook searches for peer-reviewed articles in PubMed, Web of Science, Scopus, GreenFile, ScienceDirect and Toxline and included studies of controlled exposures of environmental chemical pollutants, defined as unintentional exposures leading to unintended effects. Studies with viruses, prions or therapeutic agents were excluded, as were records with missing details on chemicals' identities, toxicities, doses, or concentrations. To examine the internal validity of studies we developed a risk-of-bias tool tailored to mixture toxicology. For a subset of 388 entries that claimed synergisms or antagonisms, we conducted a quantitative reappraisal of authors' evaluations by deriving ratios of predicted and observed effective mixture doses (concentrations). Our searches produced an inventory of 1220 mixture experiments which we subjected to subgroup analyses. Approximately two thirds of studies did not incorporate more than 2 components. Most experiments relied on low-cost assays with readily quantifiable endpoints. Important toxicity outcomes of relevance for human risk assessment (e.g. carcinogenicity, genotoxicity, reproductive toxicity, immunotoxicity, neurotoxicity) were rarely addressed. The proportion of studies that declared additivity, synergism or antagonisms was approximately equal (one quarter each); the remaining quarter arrived at different evaluations. About half of the 1220 entries were rated as "definitely" or "probably" low risk of bias. Strikingly, relatively few claims of synergistic or antagonistic effects stood up to scrutiny in terms of deviations from expected additivity that exceed the boundaries of acceptable between-study variability. In most cases, the observed mixture doses were not more than two-fold higher or lower than the predicted additive doses. Twenty percent of the entries (N = 78) reported synergisms in excess of that degree of deviation. Our efforts of pinpointing specific factors that predispose to synergistic interactions confirmed previous concerns about the synergistic potential of combinations of triazine, azole and pyrethroid pesticides at environmentally relevant doses. New evidence of synergisms with endocrine disrupting chemicals and metal compounds such as chromium (VI) and nickel in combination with cadmium has emerged. These specific cases of synergisms apart, our results confirm the utility of default application of the dose (concentration) addition concept for predictive assessments of simultaneous exposures to multiple chemicals. However, this strategy must be complemented by an awareness of the synergistic potential of specific classes of chemicals. Our conclusions only apply to the chemical space captured in published mixture studies which is biased towards relatively well-researched chemicals. The final protocol was published on the open-access repository Zenodo and attributed the following digital object identifier, doi: https://doi.org//10.5281/zenodo.1319759 (https://zenodo.org/record/1319759#.XXIzdy7dsqM).

This paper summarizes current challenges, the potential use of novel scientific methodologies, and ways forward in the risk assessment and risk management of mixtures. Generally, methodologies to address mixtures have been agreed; however, there are still several data and methodological gaps to be addressed. New approach methodologies can support the filling of knowledge gaps on the toxicity and mode(s) of action of individual chemicals. (Bio)Monitoring, modeling, and better data sharing will support the derivation of more realistic co-exposure scenarios. As knowledge and data gaps often hamper an in-depth assessment of specific chemical mixtures, the option of taking account of possible mixture effects in single substance risk assessments is briefly discussed. To allow risk managers to take informed decisions, transparent documentation of assumptions and related uncertainties is recommended indicating the potential impact on the assessment. Considering the large number of possible combinations of chemicals in mixtures, prioritization is needed, so that actions first address mixtures of highest concern and chemicals that drive the mixture risk. As chemicals with different applications and regulated separately might lead to similar toxicological effects, it is important to consider chemical mixtures across legislative sectors.

• Human Biomonitoring (HBM) provides valuable insight into co-exposure to multiple chemicals. • HBM data can be interpreted in comparison to biomonitoring equivalents of health based guidance values. • Two generic physiologically based kinetic models were tested for deriving biomonitoring equivalents. • Uncertainties and limitations were identified and discussed. • The use of biomonitoring equivalents in assessing chemical mixtures was illustrated in a case study.

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

Regulatory human health risk assessment of chemicals ideally requires integration of toxicokinetic absorption, distribution, metabolism, and excretion where the respiratory system is a principal exposure route and threshold site for absorption. This study evaluated the permeability capacity of an in vitro human airway epithelium cell model (MucilAir™). Initially, definition of the in vitro method, including development of standard operating procedure confirmation of transferability and assurance of reproducible performance, was established in a preliminary phase involving two independent laboratories using six chemicals (propranolol, atenolol, nicotine, cadmium dichloride, cobalt chloride, and ammonium hexachloroplatinate). A follow-up investigation of method relevance, measuring relative permeability of 30 chemicals, in 1 laboratory is also reported. Absorption through the lung barrier model was determined as apparent permeability coefficient (P_app) following apical and basolateral exposure to nontoxic concentrations. P_app was calculated from chemical concentrations crossing the cell barrier at appropriate time intervals. Comparative permeability of nasal and bronchial epithelium is also reported. Overall, the results demonstrate that MucilAir is an effective barrier model for assessing the permeability of different classes of compounds across the human airway epithelium. Results indicate a generally higher permeability of the airway epithelium for organic compounds compared to inorganic chemicals, with a low-protein-mediated efflux as permeability mechanism. The in vitro test system provides a robust and transferable method for determination of pulmonary absorption, relevant to toxicokinetic modeling and integration into risk assessment of chemicals.