Metabolism, variability and risk assessment

Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies

The merging of physiology and toxicokinetics, or pharmacokinetics, with computational modeling to characterize dosimetry has led to major advances for both the chemical and pharmaceutical research arenas. Driven by the mutual need to estimate internal exposures where in vivo data generation was simply not possible, the application of toxicokinetic modeling has grown exponentially in the past 30 years. In toxicology the need has been the derivation of quantitative estimates of toxicokinetic and toxicodynamic variability to evaluate the suitability of the tenfold uncertainty factor employed in risk assessment decision-making. Consideration of a host of physiologic, ontogenetic, genetic, and exposure factors are all required for comprehensive characterization. Fortunately, the underlying framework of physiologically based toxicokinetic models can accommodate these inputs, in addition to being amenable to capturing time-varying dynamics. Meanwhile, international interest in advancing new approach methodologies has fueled the generation of in vitro toxicity and toxicokinetic data that can be applied in in vitro-in vivo extrapolation approaches to provide human-specific risk-based information for historically data-poor chemicals. This review will provide a brief introduction to the structure and evolution of toxicokinetic and physiologically based toxicokinetic models as they advanced to incorporate variability and a wide range of complex exposure scenarios. This will be followed by a state of the science update describing current and emerging experimental and modeling strategies for population and life-stage variability, including the increasing application of in vitro-in vivo extrapolation with physiologically based toxicokinetic models in pharmaceutical and chemical safety research. The review will conclude with case study examples demonstrating novel applications of physiologically based toxicokinetic modeling and an update on its applications for regulatory decision-making. Physiologically based toxicokinetic modeling provides a sound framework for variability evaluation in chemical risk assessment.

Establishing allometric relationships between microsomal protein and cytochrome P450 content with body weight in vertebrate species

Data from in vitro studies are routinely used to estimate in vivo hepatic clearance of chemicals and this information is needed to parameterise physiologically based kinetic models. Such clearance data can be obtained from laboratory experiments using liver microsomes, hepatocytes, precision-cut liver slices or recombinant enzymes. Irrespective of the selected test system, scaling factors are required to convert the in vitro measured intrinsic clearance to a whole liver intrinsic clearance. Scaling factors such as the hepatic microsomal protein per gram of liver and/or the amount of cytochrome P450 per hepatocyte provide a means to calculate the whole liver intrinsic clearance. Here, a database from the peer-reviewed literature has been developed and provides quantitative metrics on microsomal protein (MP) and cytochrome P450 contents in vertebrate orders namely amphibians, mammals, birds, fish and reptiles. This database allows to address allometric relationships between body weight and MP content, and body weight and cytochrome P450 content. A total of 85 and 74 vertebrate species were included to assess the relationships between log10 body weight versus log10 MP, and between log10 body weight and log10 cytochrome P450 content, respectively. The resulting slopes range from 0.76 to 1.45 in a range of vertebrate species. Such data-driven allometric relationships can be used to estimate the MP content necessary for in vitro to in vivo extrapolation of in vitro clearance data. Future work includes applications of these relationships for different vertebrate taxa using quantitative in vitro to in vivo extrapolation models coupled to physiologically based kinetic models using chemicals of relevance as case studies including pesticides, contaminants and feed additives.

Cytochrome P450 isoforms contribution, plasma protein binding, toxicokinetics of enniatin A in rats and in vivo clearance prediction in humans

Emerging mycotoxins, such as enniatin A (ENNA), are becoming a worldwide concern owing to their presence in different types of food and feed. However, comprehensive toxicokinetic data that links intake, exposure and toxicological effects of ENNA has not been elucidated yet. Therefore, the present study investigated the in vitro (rat and human) and in vivo (rat) toxicokinetic properties of ENNA. Towards this, an easily applicable and sensitive bioanalytical method was developed and validated for the estimation of ENNA in rat plasma. ENNA exhibited high plasma protein binding (99%), high hepatic clearance and mainly underwent metabolism via CYP3A4 (74%). The in-house predicted hepatic clearance (54 mL/min/kg) and observed in vivo rat clearance (55 mL/min/kg) were comparable. The predicted in vivo human hepatic clearance was 18 mL/min/kg. ENNA underwent slow absorption (T_max = 4 h) and rapid elimination following oral administration to rats. The absolute oral bioavailability was 47%. The toxicokinetic findings for ENNA from this study will help in designing and interpreting toxicological studies in rats. Besides, these findings could be used in physiologically based toxicokinetic (PBTK) model development for exposure predictions and risk assessment for ENNA in humans.

A Computational Understanding of Inter-Individual Variability in CYP2D6 Activity to Investigate the Impact of Missense Mutations on Ochratoxin A Metabolism

Cytochrome P-450 (CYP) enzymes have a key role in the metabolism of xenobiotics of food origin, and their highly polymorphic nature concurs with the diverse inter-individual variability in the toxicokinetics (TK) and toxicodynamics (TD) of food chemicals. Ochratoxin A is a well-known mycotoxin which contaminates a large variety of food and is associated with food safety concerns. It is a minor substrate of CYP2D6, although the effects of CYP2D6 polymorphisms on its metabolism may be overlooked. Insights on this aspect would provide a useful mechanistic basis for a more science-based hazard assessment, particularly to integrate inter-individual differences in CYP2D6 metabolism. This work presents a molecular modelling approach for the analysis of mechanistic features with regard to the metabolic capacity of CYP2D6 variants to oxidise a number of substrates. The outcomes highlighted that a low-frequency CYP2D6 variant (CYP2D6*110) is likely to enhance ochratoxin A oxidation with possible consequences on TK and TD. It is therefore recommended to further analyse such TK and TD consequences. Generally speaking, we propose the identification of mechanistic features and parameters that could provide a semi-quantitative means to discriminate ligands based on the likelihood to undergo transformation by CYP2D6 variants. This would support the development of a fit-for-purpose pipeline which can be extended to a tool allowing for the bulk analysis of a large number of compounds. Such a tool would ultimately include inter-phenotypic differences of polymorphic xenobiotic-metabolising enzymes in the hazard assessment and risk characterisation of food chemicals.

EFSA Panel on Plant Protection Products and their Residues (EFSA PPR Panel), Hernandez‐Jerez AF, Adriaanse P, Aldrich A, Berny P, Coja T, Duquesne S, Focks A, Marinovich M, Millet M, Pelkonen O, Pieper S, Tiktak A, Topping CJ, Widenfalk A, Wilks M, Wolterink G, Gundert‐Remy U, Louisse J, Rudaz S, Testai E, Lostia A, Dorne J, Parra Morte JM. Scientific Opinion of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on testing and interpretation of comparative in vitro metabolism studies

EFSA asked the Panel on Plant Protection Products and their residues to deliver a Scientific Opinion on testing and interpretation of comparative in vitro metabolism studies for both new active substances and existing ones. The main aim of comparative in vitro metabolism studies of pesticide active substances is to evaluate whether all significant metabolites formed in the human in vitro test system, as a surrogate of the in vivo situation, are also present at comparable level in animal species tested in toxicological studies and, therefore, if their potential toxicity has been appropriately covered by animal studies. The studies may also help to decide which animal model, with regard to a particular compound, is the most relevant for humans. In the experimental strategy, primary hepatocytes in suspension or culture are recommended since hepatocytes are considered the most representative in vitro system for prediction of in vivo metabolites. The experimental design of 3 × 3 × 3 (concentrations, time points, technical replicates, on pooled hepatocytes) will maximise the chance to identify unique (UHM) and disproportionate (DHM) human metabolites. When DHM and UHM are being assessed, test item-related radioactivity recovery and metabolite profile are the most important parameters. Subsequently, structural characterisation of the assigned metabolites is performed with appropriate analytical techniques. In toxicological assessment of metabolites, the uncertainty factor approach is the first alternative to testing option, followed by new approach methodologies (QSAR, read-across, in vitro methods), and only if these fail, in vivo animal toxicity studies may be performed. Knowledge of in vitro metabolites in human and animal hepatocytes would enable toxicological evaluation of all metabolites of concern, and, furthermore, add useful pieces of information for detection and evaluation of metabolites in different matrices (crops, livestock, environment), improve biomonitoring efforts via better toxicokinetic understanding, and ultimately, develop regulatory schemes employing physiologically based or physiology-mimicking in silico and/or in vitro test systems to anticipate the exposure of humans to potentially hazardous substances in plant protection products.

Human variability in polymorphic CYP2D6 metabolism: Implications for the risk assessment of chemicals in food and emerging designer drugs

The major human cytochrome P450 CYP2D6 isoform enzyme plays important roles in the liver and in the brain with regards to xenobiotic metabolism. Xenobiotics as CYP2D6 substrates include a whole range of pharmaceuticals, pesticides and plant alkaloids to cite but a few. In addition, a number of endogenous compounds have been shown to be substrates of CYP2D6 including trace amines in the brain such as tyramine and 5-methoxytryptamine as well as anandamide and progesterone. Because of the polymorphic nature of CYP2D6, considerable inter-phenotypic and inter-ethnic differences in the pharmaco/toxicokinetics (PK/TK) and metabolism of CYP2D6 substrates exist with potential consequences on the pharmacology and toxicity of chemicals. Here, large extensive literature searches have been performed to collect PK data from published human studies for a wide range of pharmaceutical probe substrates and investigate human variability in CYP2D6 metabolism. The computed kinetic parameters resulted in the largest open source database, quantifying inter-phenotypic differences for the kinetics of CYP2D6 probe substrates in Caucasian and Asian populations, to date. The database is available in supplementary material (CYPD6 DB) and EFSA knowledge junction (DOI to added). Subsequently, meta-analyses using a hierarchical Bayesian model for markers of chronic oral exposure (oral clearance, area under the plasma concentration time curve) and acute oral exposure (maximum plasma concentration (Cmax) provided estimates of inter-phenotypic differences and CYP2D6-related uncertainty factors (UFs) for chemical risk assessment in Caucasian and Asian populations classified as ultra-rapid (UM), extensive (EMs), intermediate (IMs) and poor metabolisers (PMs). The model allowed the integration of inter-individual (i.e. inter-phenotypic and inter-ethnic), inter-compound and inter-study variability together with uncertainty in each PK parameter. Key findings include 1. Higher frequencies of PMs in Caucasian populations compared to Asian populations (>8% vs 1-2%) for which EM and IM were the most frequent phenotype. 2. Large inter-phenotypic differences in PK parameters for Caucasian EMs (coefficients of variation (CV) > 50%) compared with Caucasian PMs and Asian EMs and IMs (i.e CV < 40%). 3. Inter-phenotypic PK differences between EMs and PMs in Caucasian populations increase with the quantitative contribution of CYP2D6 for the metabolism (fm) for a range of substrates (fm_CYP2D6 range: 20-95% of dose) (range: 1-54) to a much larger extent than those for Asian populations (range: 1-4). 4. Exponential meta-regressions between Fm_CYP2D6 in EMs and inter-phenotypic differences were also shown to differ between Caucasian and Asian populations as well as CYP2D6-related UFs. Finally, implications of these results for the risk assessment of food chemicals and emerging designer drugs of public health concern, as CYP2D6 substrates, are highlighted and include the integration of in vitro metabolism data and CYP2D6-variability distributions for the development of quantitative in vitro in vivo extrapolation models.

Impact of Estrogen Withdrawal and Replacement in Female Mice along the Intestinal Tract. Comparison of E2 Replacement with the Effect of a Mixture of Low Dose Pollutants

Postmenopausal women represent a vulnerable population towards endocrine disruptors due to hormonal deficit. We previously demonstrated that chronic exposure of ovariectomized C57Bl6/J mice fed a high-fat, high-sucrose diet to a low-dose mixture of chemicals with one dioxin, one polychlorobiphenyl, one phthalate, and bisphenol A triggered metabolic alterations in the liver but the intestine was not explored. Yet, the gastrointestinal tract is the main route by which pollutants enter the body. In the present study, we investigated the metabolic consequences of ovarian withdrawal and E2 replacement on the various gut segments along with investigating the impact of the mixture of pollutants. We showed that genes encoding estrogen receptors (Esr1, Gper1 not Esr2), xenobiotic processing genes (e.g., Cyp3a11, Cyp2b10), and genes related to gut homeostasis in the jejunum (e.g., Cd36, Got2, Mmp7) and to bile acid biosynthesis in the gut (e.g., Fgf15, Slc10a2) and liver (e.g., Abcb11, Slc10a1) were under estrogen regulation. Exposure to pollutants mimicked some of the effects of E2 replacement, particularly in the ileum (e.g., Esr1, Nr1c1) suggesting that the mixture had estrogen-mimetic activities. The present findings have important implications for the understanding of estrogen-dependent metabolic alterations with regards to situations of loss of estrogens as observed after menopause.

Endocrine disrupting chemicals and metabolic disorders in the liver: What if we also looked at the female side?

Endocrine disrupting chemicals (EDCs) are linked to the worldwide epidemic incidence of metabolic disorders and fatty liver diseases, which affects quality of life and represents a high economic cost to society. Energy homeostasis exhibits strong sexual dimorphic traits, and metabolic organs respond to EDCs depending on sex, such as the liver, which orchestrates both drug elimination and glucose and lipid metabolism. In addition, fatty liver diseases show a strong sexual bias, which in part could also originate from sex differences observed in gut microbiota. The aim of this review is to highlight significant differences in endocrine and metabolic aspects of the liver, between males and females throughout development and into adulthood. It is also to illustrate how the male and female liver differently cope with exposure to various EDCs such as bisphenols, phthalates and persistent organic chemicals in order to draw attention to the need to include both sexes in experimental studies. Interesting data come from analyses of the composition and diversity of the gut microbiota in males exposed to the mentioned EDCs showing significant correlations with hepatic lipid accumulation and metabolic disorders but information on females is lacking or incomplete. As industrialization increases, the list of anthropogenic chemicals to which humans will be exposed will also likely increase. In addition to strengthening existing regulations, encouraging populations to protect themselves and promoting the substitution of harmful chemicals with safe products, innovative strategies based on sex differences in the gut microbiota and in the gut-liver axis could be optimistic outlook.

Exposure to pollutants altered glucocorticoid signaling and clock gene expression in female mice. Evidence of tissue- and sex-specificity

Environmental pollutants suspected of disrupting the endocrine system are considered etiologic factors in the epidemic of metabolic disorders. As regulation of energy metabolism relies on the integrated action of a large number of hormones, we hypothesized that certain chemicals could trigger changes in glucocorticoid signaling. To this end, we exposed C57Bl6/J female and male mice between 5 and 20 weeks of age to a mixture of 2,3,7,8- tetrachlorodibenzo-p-dioxin (20 pg/kg body weight/day [bw/d]), polychlorobiphenyl 153 (200 ng/kg bw/d), di-[2-ethylhexyl]-phthalate (500 μg/kg bw/d) and bisphenol A (40 μg/kg bw/d). In female mice fed a standard diet (ST), we observed a decrease in plasma levels of leptin as well as a reduced expression of corticoid receptors Nr3c1 and Nr3c2, of leptin and of various canonical genes related to the circadian clock machinery in visceral (VAT) but not subcutaneous (SAT) adipose tissue. However, Nr3c1 and Nr3c2 mRNA levels did not change in high-fat-fed females exposed to pollutants. In ST-fed males, pollutants caused the same decrease of Nr3c1 mRNA levels in VAT observed in ST-fed females but levels of Nr3c2 and other clock-related genes found to be down-regulated in female VAT were enhanced in male SAT and not affected in male VAT. The expression of corticoid receptors was not affected in the livers of both sexes in response to pollutants. In summary, exposure to a mixture of pollutants at doses lower than the no-observed adverse effect levels (NoAELs) resulted in sex-dependent glucocorticoid signaling disturbances and clock-related gene expression modifications in the adipose tissue of ST-fed mice.

Adipose Tissue and Endocrine-Disrupting Chemicals: Does Sex Matter?

Obesity and metabolic-related diseases, among which diabetes, are prominent public health challenges of the 21st century. It is now well acknowledged that pollutants are a part of the equation, especially endocrine-disrupting chemicals (EDCs) that interfere with the hormonal aspect. The aim of the review is to focus on adipose tissue, a central regulator of energy balance and metabolic homeostasis, and to highlight the significant differences in the endocrine and metabolic aspects of adipose tissue between males and females which likely underlie the differences of the response to exposure to EDCs between the sexes. Moreover, the study also presents an overview of several mechanisms of action by which pollutants could cause adipose tissue dysfunction. Indeed, a better understanding of the mechanism by which environmental chemicals target adipose tissue and cause metabolic disturbances, and how these mechanisms interact and sex specificities are essential for developing mitigating and sex-specific strategies against metabolic diseases of chemical origin. In particular, considering that a scenario without pollutant exposure is not a realistic option in our current societies, attenuating the deleterious effects of exposure to pollutants by acting on the gut-adipose tissue axis may constitute a new direction of research.

Plasma protein binding, metabolism, reaction phenotyping and toxicokinetic studies of fenarimol after oral and intravenous administration in rats

Fenarimol (FNL), an organic chlorinated fungicide, is widely used in agriculture for protection from fungal spores and fungi. Despite being an endocrine disruptor, no toxicokinetic data is reported for this fungicide. In the present work, we determined the plasma protein binding, metabolic pathways and toxicokinetics of FNL in rats. In vitro binding of FNL to rat and human plasma proteins was ∼90%, suggesting that FNL is a highly protein bound fungicide. The predicted in vivo hepatic clearance of FNL in rats and humans was estimated to be 36.71 and 14.39 mL/min/kg, respectively, indicating it to be an intermediate clearance compound. Reaction phenotyping assay showed that CYP3A4 mainly contributed to the overall metabolism of FNL. The oral toxicokinetic study of FNL in rats at no observed adverse effect level dose (1 mg/kg) showed maximum plasma concentration (C _max) of 33.97 ± 4.45 ng/mL at 1 h (T _max). The AUC_0-∞ obtained was 180.18 ± 17.76 h*ng/mL, whereas, the t _1/2 was ∼4.74 h. Following intravenous administration, FNL displayed a clearance of 42.48 mL/min/kg which was close to the predicted in vivo hepatic clearance. The absolute oral bioavailability of FNL at 1 mg/kg dose in rats was 45.25%. FNL at 10 mg/kg oral dose exhibited non-linear toxicokinetics with greater than dose-proportional increase in the systemic exposure (AUC_0-∞ 8270.53 ± 1798.59 h*ng/mL).

Estrogen withdrawal and replacement differentially target liver and adipose tissues in female mice fed a high-fat high-sucrose diet: impact of a chronic exposure to a low-dose pollutant mixture☆

Postmenopausal women may be at particular risk when exposed to chemicals especially endocrine disruptors because of hormonal deficit. To get more insight, ovariectomized C57Bl6/J mice fed a high-fat high-sucrose diet were chronically exposed from 5 to 20 weeks of age to a low-dose mixture of chemicals with one dioxin, one polychlorobiphenyl, one phthalate and bisphenol A. Part of the mice received as well E2 implants to explore the potential estrogenic dependency of the metabolic alterations. With this model, estrogen loss resulted in glucose but not lipid metabolism impairment, and E2 replacement normalized the enhanced body and fat pad weight, and the glucose intolerance and insulin resistance linked to ovariectomy. It also altered cholesterol metabolism in the liver concurrently with enhanced estrogen receptor Esr1 mRNA level. In addition, fat depots responded differently to estrogen withdrawal (e.g., selective mRNA enhancement of adipogenesis markers in subcutaneous and of inflammation in visceral fat pads) and replacement challenges. Importantly, the pollutant mixture impacted lipid deposition and mRNA expression of several genes related to lipid metabolism but not Esr1 in the liver. Adiponectin levels were altered as well. In addition, the mRNA abundance of the various estrogen receptors was regionally impacted in fat tissues. Besides, xenobiotic processing genes did not change in response to the pollutant mixture in the liver. The present findings bring new light on estrogen-dependent metabolic alterations with regards to situations of loss of estrogens as observed after menopause.

Arctic marine fish 'biotransformation toxicity' model for ecological risk assessment

Oil and gas exploration and marine transport in the Arctic region have put the focus on the ecological risk of the possibly exposed organisms. In the present study, the impacts of sea ice, extreme light regime, various polar region-specific physiological characteristics in polar cod (Boreogadus saida) and their effects on xenobiotic distribution and metabolism are studied. A Bayesian belief network is used to model individual fish toxicity. The enzyme activity in the fish liver and other pertinent organs is used as a proxy for cellular damage and repair and is subsequently linked to toxicity in polar cod. Seasonal baseline variation in enzyme production is also taken into consideration. The model estimates the probability of exposure concentration to cause cytotoxicity and circumvents the need to use the traditionally obtained No Observed Effect Concentration (NOEC). Instead, it uses biotransformation enzyme activity as a basis to estimate the probability of individual cell damages.

Chronic exposure to a pollutant mixture at low doses led to tissue-specific metabolic alterations in male mice fed standard and high-fat high-sucrose diet

Excessive consumption of industrialized food and beverages is a major etiologic factor in the epidemics of obesity and associated metabolic diseases because these products are rich in fat and sugar. In addition, they contain food contact materials and environmental pollutants identified as metabolism disrupting chemicals. To evaluate the metabolic impact of these dietary threats (individually or combined), we used a male mouse model of chronic exposure to a mixture of low-dose archetypal food-contaminating chemicals that was added in standard or high-fat, high-sucrose (HFHS) diet. Specifically, the mixture contained bisphenol A, diethylhexylphthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxine and polychlorinated biphenyl 153. Exposure lasted from 5 to 20 weeks of age. Metabolic exploration was conducted setting the basis of candidate gene expression mRNA analyses in liver, jejunum and adipose tissue depots from 20 week-old mice. Strong metabolic deleterious effects of the HFHS diet were demonstrated in line with obesity-associated metabolic features and insulin resistance. Pollutant exposure resulted in significant changes on plasma triglyceride levels and on the expression levels of genes mainly encoding xenobiotic processing in jejunum; estrogen receptors, regulators of lipoprotein lipase and inflammatory markers in jejunum and adipose tissues as well as adipogenesis markers. Importantly, the impact of pollutants was principally evidenced under standard diet. In addition, depending on nutritional conditions and on the metabolic tissue considered, the impact of pollutants could mimic or oppose the HFHS effects. Collectively, the present study extends the cocktail effect concept of a low-dosed pollutant mixture and originally points to tissue-specificity responsiveness especially in jejunum and adipose tissues.

Subchronic toxicity evaluation of leaves from rabbiteye blueberry (Vaccinium virgatum Aiton) in rats

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Blueberry leaf may contain multiple compounds with beneficial effects, but limited about the safety.

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Powdered blueberry leaf has no toxic event at oral dose of daily 500, 1000 and 2500 mg/kg for 90 days in SD rats.

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No significant changes in food consumption, body weight gain and organ weights.

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A daily dose up to 2,500 mg/kg body weight in both the sexes rats may indicate a NOAEL.

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An acceptable daily intake of blueberry leaf powder for humans is calculated to be 25 mg in dry weight per kg body weight.

Blueberry leaf may contain multiple compounds with beneficial effects. We conducted a 90-day toxicity study in rats to evaluate the safety of consuming the leaves of rabbiteye blueberry (Vaccinium virgatum Aiton; RB species). Powdered leaves were administered daily by oral gavage at doses of 500, 1000, and 2500 mg/kg body weight to male and female Sprague-Dawley rats for 90 days. Treatment did not result in death or changes in the behavior and external appearance of the animals. No alterations were observed in hematological and serum chemical parameters, urinalysis, food consumption, body weight gain, or absolute and relative organ weights at the end of the treatment period, with the exception of some leukocyte percentages in male rats treated with 500 and 1000 mg/kg blueberry leaf powder. The findings indicate that rabbiteye blueberry leaf is safe for consumption and should be investigated as a candidate functional food.

SAR for gastro-intestinal absorption and blood-brain barrier permeation of pesticides

The CORAL software has been applied to the development of classification models for pesticides relative to two pharmacokinetic properties in humans: (i) gastro-intestinal absorption; and (ii) blood-brain barrier permeation. These models were built up using categorical data on pesticide absorption and brain permeation split into training, invisible training, calibration and external validation sets using Monte Carlo simulations. The models were assessed using several random splits into the training and validation sets. Optimal SMILES-based descriptors sensitive to the presence of different chemical elements and types of covalent bonds have been used to build up models. The range of Matthews correlation coefficient for suggested models is 0.64-0.75. The perspectives of studied approach as a tool to build up models for pharmacokinetic properties of chemicals is discussed. The models are built up according to OECD principles.

Diagnosis, monitoring and prevention of exposure-related non-communicable diseases in the living and working environment: DiMoPEx-project is designed to determine the impacts of environmental exposure on human health

The WHO has ranked environmental hazardous exposures in the living and working environment among the top risk factors for chronic disease mortality. Worldwide, about 40 million people die each year from noncommunicable diseases (NCDs) including cancer, diabetes, and chronic cardiovascular, neurological and lung diseases. The exposure to ambient pollution in the living and working environment is exacerbated by individual susceptibilities and lifestyle-driven factors to produce complex and complicated NCD etiologies. Research addressing the links between environmental exposure and disease prevalence is key for prevention of the pandemic increase in NCD morbidity and mortality. However, the long latency, the chronic course of some diseases and the necessity to address cumulative exposures over very long periods does mean that it is often difficult to identify causal environmental exposures. EU-funded COST Action DiMoPEx is developing new concepts for a better understanding of health-environment (including gene-environment) interactions in the etiology of NCDs. The overarching idea is to teach and train scientists and physicians to learn how to include efficient and valid exposure assessments in their research and in their clinical practice in current and future cooperative projects. DiMoPEx partners have identified some of the emerging research needs, which include the lack of evidence-based exposure data and the need for human-equivalent animal models mirroring human lifespan and low-dose cumulative exposures. Utilizing an interdisciplinary approach incorporating seven working groups, DiMoPEx will focus on aspects of air pollution with particulate matter including dust and fibers and on exposure to low doses of solvents and sensitizing agents. Biomarkers of early exposure and their associated effects as indicators of disease-derived information will be tested and standardized within individual projects. Risks arising from some NCDs, like pneumoconioses, cancers and allergies, are predictable and preventable. Consequently, preventative action could lead to decreasing disease morbidity and mortality for many of the NCDs that are of major public concern. DiMoPEx plans to catalyze and stimulate interaction of scientists with policy-makers in attacking these exposure-related diseases.

CORAL: QSAR models for carcinogenicity of organic compounds for male and female rats

Quantitative structure - activity relationships (QSARs) for carcinogenicity (rats, TD₅₀) have been built up using the CORAL software. Different molecular features, which are extracted from simplified molecular input-line entry system (SMILES) serve as the basis for building up a model. Correlation weights for the molecular features are calculated by means of the Monte Carlo optimization. Using the numerical data on the correlation weights, one can calculate a model of carcinogenicity as a mathematical function of descriptors, which are sum of the corresponding correlation weights. In other words, the correlation weights provide the maximal correlation coefficient between the descriptor and carcinogenicity, for the training set. This correlation was assessed via external validation set. Finally, lists of molecular alerts in aspects of carcinogenicity for male rats and for female rats were compared and their differences were discussed.

Evidence for estrogeno-mimetic effects of a mixture of low-dose pollutants in a model of ovariectomized mice

We recently hypothesized that a mixture of low-dosed dioxin, polychlorobiphenyl, phthalate and bisphenol may induce estrogeno-mimetic activities in a model of lifelong-exposed female mice. Herein, we evaluated the impact of this mixture in estrogen deficiency conditions. Based on the protective effects of estrogens against metabolic disorders, we reasoned that exposure to pollutants should attenuate the deleterious metabolic effects induced by ovariectomy. In line with the hypothesis, exposure to pollutants was found to reduce the impact of ovariectomy on glucose intolerance and insulin resistance, to enhance the expression levels of the hepatic estrogen receptor α and to attenuate the ovariectomy-induced enhancement of the chemokine MCP-1/CCL2 considered as an indicator of estrogen signalling. Because of the very low doses of pollutants used in mixture, these findings may have strong implications in terms of understanding the potential role of environmental contaminants in the development of metabolic diseases, specifically in females during menopausal transition.

Worldwide Regulations of Standard Values of Pesticides for Human Health Risk Control: A Review

Abstract: The impact of pesticide residues on human health is a worldwide problem, as human exposure to pesticides can occur through ingestion, inhalation, and dermal contact. Regulatory jurisdictions have promulgated the standard values for pesticides in residential soil, air, drinking water, and agricultural commodity for years. Until now, more than 19,400 pesticide soil regulatory guidance values (RGVs) and 5400 pesticide drinking water maximum concentration levels (MCLs) have been regulated by 54 and 102 nations, respectively. Over 90 nations have provided pesticide agricultural commodity maximum residue limits (MRLs) for at least one of the 12 most commonly consumed agricultural foods. A total of 22 pesticides have been regulated with more than 100 soil RGVs, and 25 pesticides have more than 100 drinking water MCLs. This research indicates that those RGVs and MCLs for an individual pesticide could vary over seven (DDT drinking water MCLs), eight (Lindane soil RGVs), or even nine (Dieldrin soil RGVs) orders of magnitude. Human health risk uncertainty bounds and the implied total exposure mass burden model were applied to analyze the most commonly regulated and used pesticides for human health risk control. For the top 27 commonly regulated pesticides in soil, there are at least 300 RGVs (8% of the total) that are above all of the computed upper bounds for human health risk uncertainty. For the top 29 most-commonly regulated pesticides in drinking water, at least 172 drinking water MCLs (5% of the total) exceed the computed upper bounds for human health risk uncertainty; while for the 14 most widely used pesticides, there are at least 310 computed implied dose limits (28.0% of the total) that are above the acceptable daily intake values. The results show that some worldwide standard values were not derived conservatively enough to avoid human health risk by the pesticides, and that some values were not computed comprehensively by considering all major human exposure pathways.

Aquatic ecotoxicological models and their applicability in Arctic regions

Dose-response modeling is one of the most important steps of ecological risk assessment. It requires concentration-effects relationships for the species under consideration. There are very limited studies and experimental data available for the Arctic aquatic species. Lack of toxicity data hinders obtaining dose-response relationships for lethal (LC50 values), sub-lethal and carcinogenic effects. Gaps in toxicity data could be filled using a variety of in-silico ecotoxicological methods. This paper reviews the suitability of such methods for the Arctic scenario. Mechanistic approaches like toxicokinetic and toxicodynamic analysis are found to be better suited for interspecies extrapolation than statistical methods, such as Quantitative Structure-Activity Relationships/Quantitative Structure Activity-Activity Relationship, ICE, and other empirical models, such as Haber's law and Ostwald's equation. A novel approach is proposed where the effects of the toxicant exposure are quantified based on the probability of cellular damage and metabolites interactions. This approach recommends modeling cellular damage using a toxicodynamic model and physiology or metabolites interactions using a toxicokinetic model. Together, these models provide more reliable estimates of toxicity in the Arctic aquatic species, which will assist in conducting ecological risk assessment of Arctic environment.

Endocrine disrupting chemicals in mixture and obesity, diabetes and related metabolic disorders

Obesity and associated metabolic disorders represent a major societal challenge in health and quality of life with large psychological consequences in addition to physical disabilities. They are also one of the leading causes of morbidity and mortality. Although, different etiologic factors including excessive food intake and reduced physical activity have been well identified, they cannot explain the kinetics of epidemic evolution of obesity and diabetes with prevalence rates reaching pandemic proportions. Interestingly, convincing data have shown that environmental pollutants, specifically those endowed with endocrine disrupting activities, could contribute to the etiology of these multifactorial metabolic disorders. Within this review, we will recapitulate characteristics of endocrine disruption. We will demonstrate that metabolic disorders could originate from endocrine disruption with a particular focus on convincing data from the literature. Eventually, we will present how handling an original mouse model of chronic exposition to a mixture of pollutants allowed demonstrating that a mixture of pollutants each at doses beyond their active dose could induce substantial deleterious effects on several metabolic end-points. This proof-of-concept study, as well as other studies on mixtures of pollutants, stresses the needs for revisiting the current threshold model used in risk assessment which does not take into account potential effects of mixtures containing pollutants at environmental doses, e.g., the real life exposure. Certainly, more studies are necessary to better determine the nature of the chemicals to which humans are exposed and at which level, and their health impact. As well, research studies on substitute products are essential to identify harmless molecules.

The application of new HARD-descriptor available from the CORAL software to building up NOAEL models

Continuous QSAR models have been developed and validated for the prediction of no-observed-adverse-effect (NOAEL) in rats, using training and test sets from the Fraunhofer RepDose® database and EFSA's Chemical Hazards Database: OpenFoodTox. This paper demonstrates that the HARD index, as an integrated attribute of SMILES, improves the prediction power of NOAEL values using the continuous QSAR models and Monte Carlo simulations. The HARD-index is a line of eleven symbols, which represents the presence, or absence of eight chemical elements (nitrogen, oxygen, sulfur, phosphorus, fluorine, chlorine, bromine, and iodine) and different kinds of chemical bonds (double bond, triple bond, and stereo chemical bond). Optimal molecular descriptors calculated with the Monte Carlo technique (maximization of correlation coefficient between the descriptor and endpoint) give satisfactory predictive models for NOAEL. Optimal molecular descriptors calculated in this way with the Monte Carlo technique (maximization of correlation coefficient between the descriptor and endpoint) give amongst the best results available in the literature. The models are built up in accordance with OECD principles.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

Uncertainty and variability in human exposure limits - a chemical-specific approach for ciprofloxacin and methotrexate

Human exposure limits (HELs) for chemicals with a toxicological threshold are traditionally derived using default assessment factors that account for variations in exposure duration, species sensitivity and individual sensitivity. The present paper elaborates a probabilistic approach for human hazard characterization and the derivation of HELs. It extends the framework for evaluating and expressing uncertainty in hazard characterization recently proposed by WHO-IPCS, i.e. by the incorporation of chemical-specific data on human variability in toxicokinetics. The incorporation of human variability in toxicodynamics was based on the variation between adverse outcome pathways (AOPs). Furthermore, sources of interindividual variability and uncertainty are propagated separately throughout the derivation process. The outcome is a two-dimensional human dose distribution that quantifies the population fraction exceeding a pre-selected critical effect level with an estimate of the associated uncertainty. This enables policy makers to set separate standards for the fraction of the population to be protected and the confidence level of the assessment. The main sources of uncertainty in the human dose distribution can be identified in order to plan new research for reducing uncertainty. Additionally, the approach enables quantification of the relative risk for specific subpopulations. The approach is demonstrated for two pharmaceuticals, i.e. the antibiotic ciprofloxacin and the antineoplastic methotrexate. For both substances, the probabilistic HEL is mainly influenced by uncertainty originating from: (1) the point of departure (PoD), (2) extrapolation from sub-acute to chronic toxicity and (3) interspecies extrapolation. However, when assessing the tails of the two-dimensional human dose distributions, i.e. the section relevant for the derivation of human exposure limits, interindividual variability in toxicodynamics also becomes important.

Prediction of human population responses to toxic compounds by a collaborative competition

The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.

Metabolic outcome of female mice exposed to a mixture of low-dose pollutants in a diet-induced obesity model

Pollutants are suspected to contribute to the etiology of obesity and related metabolic disorders. Apart from occupational exposure which concerns a subset of chemicals, humans are mostly exposed to a large variety of chemicals, all life-long and at low doses. Food ingestion is a major route of exposure and it is suggested that pollutants have a worsened impact when combined with a high-fat diet. In the experimental studies described herein, we aimed to add further evidence on the metabolic impact of food pollutants using a recently set up model in which mice are life-long fed a high-fat/high-sucrose diet (HFSD) with/without common food pollutants shown to exhibit metabolic disrupting activities. Specifically, this mixture comprised bisphenol A, dioxin, polychlorobiphenyl PCB153, and phthalate and was added in HFSD at doses resulting in mice exposure at the Tolerable Daily Intake dose range for each pollutant. We herein focused on the 7-week-old females which exhibited early signs of obesity upon HFSD feeding. We observed no signs of toxicity and no additional weight gain following exposure to the mixture but alleviated HFSD-induced glucose intolerance in the absence of alteration of gluconeogenesis and steatosis. It suggested that the observed metabolic improvement was more likely due to effects on muscle and/or adipose tissues rather than on the liver. Consistently, female mice exhibited enhanced lean/fat mass ratio and skeletal muscle insulin sensitivity. Moreover, expression levels of inflammatory markers were reduced in adipose tissue at 7 but enhanced at 12 weeks of age in agreement with the inverse alterations of glucose tolerance observed at these ages upon pollutant exposure in the HFSD-fed females. Collectively, these data suggest apparent biphasic effects of pollutants upon HFSD feeding along with obesity development. These effects were not observed in males and may depend on interactions between diet and pollutants.

Emerging approaches in predictive toxicology

Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described.

Exploiting monitoring data in environmental exposure modelling and risk assessment of pharmaceuticals

In order to establish the environmental impact of an active pharmaceutical ingredient (API), good information on the level of exposure in surface waters is needed. Exposure concentrations are typically estimated using information on the usage of an API as well as removal rates in the patient, the wastewater system and in surface waters. These input data are often highly variable and difficult to obtain, so model estimates often do not agree with measurements made in the field. In this paper we present an approach which uses inverse modelling to estimate overall removal rates of pharmaceuticals at the catchment scale using a hydrological model as well as prescription and monitoring data for a few representative sites for a country or region. These overall removal rates are then used to model exposure across the broader landscape. Evaluation of this approach for APIs in surface waters across England and Wales showed good agreement between modelled exposure distributions and available monitoring data. The use of the approach, alongside estimates of predicted no-effect concentrations for the 12 study compounds, to assess risk of the APIs across the UK landscape, indicated that, for most of the compounds, risks to aquatic life were low. However, ibuprofen was predicted to pose an unacceptable risk in 49.5% of the river reaches studied. For diclofenac, predicted exposure concentrations were also compared to the Environmental Quality Standard previously proposed by the European Commission and 4.5% of river reaches were predicted to exceed this concentration. While the current study focused on pharmaceuticals, the approach could also be valuable in assessing the risks of other 'down the drain' chemicals and could help inform our understanding of the important dissipation processes for pharmaceuticals in the pathway from the patient to ecological receptors.

Incorporating population variability and susceptible subpopulations into dosimetry for high-throughput toxicity testing

Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assessment context. Previously, we employed in vitro hepatic metabolic clearance and plasma protein binding data with in vitro in vivo extrapolation (IVIVE) modeling to estimate oral equivalent doses, or daily oral chemical doses required to achieve steady-state blood concentrations (Css) equivalent to media concentrations having a defined effect in an in vitro HTS assay. In this study, hepatic clearance rates of selected ToxCast chemicals were measured in vitro for 13 cytochrome P450 and five uridine 5'-diphospho-glucuronysyltransferase isozymes using recombinantly expressed enzymes. The isozyme-specific clearance rates were then incorporated into an IVIVE model that captures known differences in isozyme expression across several life stages and ethnic populations. Comparison of the median Css for a healthy population against the median or the upper 95th percentile for more sensitive populations revealed differences of 1.3- to 4.3-fold or 3.1- to 13.1-fold, respectively. Such values may be used to derive chemical-specific human toxicokinetic adjustment factors. The IVIVE model was also used to estimate subpopulation-specific oral equivalent doses that were directly compared with subpopulation-specific exposure estimates. This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability. Incorporation of these values with dosimetry and in vitro bioactivities provides a viable approach that could be employed within a high-throughput risk assessment framework.

Addressing human variability in next-generation human health risk assessments of environmental chemicals

BACKGROUND

Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment.

OBJECTIVE

Our goal was to explore how next-generation human health risk assessments may better characterize variability in the context of the conceptual framework for the source-to-outcome continuum.

METHODS

This review was informed by a National Research Council workshop titled "Biological Factors that Underlie Individual Susceptibility to Environmental Stressors and Their Implications for Decision-Making." We considered current experimental and in silico approaches, and emerging data streams (such as genetically defined human cells lines, genetically diverse rodent models, human omic profiling, and genome-wide association studies) that are providing new types of information and models relevant for assessing interindividual variability for application to human health risk assessments of environmental chemicals.

DISCUSSION

One challenge for characterizing variability is the wide range of sources of inherent biological variability (e.g., genetic and epigenetic variants) among individuals. A second challenge is that each particular pair of health outcomes and chemical exposures involves combinations of these sources, which may be further compounded by extrinsic factors (e.g., diet, psychosocial stressors, other exogenous chemical exposures). A third challenge is that different decision contexts present distinct needs regarding the identification-and extent of characterization-of interindividual variability in the human population.

CONCLUSIONS

Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing interindividual variability in a range of decision-making contexts.

Tools and perspectives for assessing chemical mixtures and multiple stressors

The present paper summarizes the most important insights and findings of the EU NoMiracle project with a focus on (1) risk assessment of chemical mixtures, (2) combinations of chemical and natural stressors, and (3) the receptor-oriented approach in cumulative risk assessment. The project aimed at integration of methods for human and ecological risk assessment. A mechanistically based model, considering uptake and toxicity as a processes in time, has demonstrated considerable potential for predicting mixture effects in ecotoxicology, but requires the measurement of toxicity endpoints at different moments in time. Within a novel framework for risk assessment of chemical mixtures, the importance of environmental factors on toxicokinetic processes is highlighted. A new paradigm for applying personal characteristics that determine individual exposure and sensitivity in human risk assessment is suggested. The results are discussed in the light of recent developments in risk assessment of mixtures and multiple stressors.

Wind of change challenges toxicological regulators

BACKGROUND

In biomedical research, the past two decades have seen the advent of in vitro model systems based on stem cells, humanized cell lines, and engineered organotypic tissues, as well as numerous cellular assays based on primarily established tumor-derived cell lines and their genetically modified derivatives.

OBJECTIVE

There are high hopes that these systems might replace the need for animal testing in regulatory toxicology. However, despite increasing pressure in recent years to reduce animal testing, regulators are still reluctant to adopt in vitro approaches on a large scale. It thus seems appropriate to consider how we could realistically perform regulatory toxicity testing using in vitro assays only.

DISCUSSION AND CONCLUSION

Here, we suggest an in vitro-only approach for regulatory testing that will benefit consumers, industry, and regulators alike.