Application of partition coefficient methods to predict tissue:plasma affinities in common farm animals: Influence of ionisation state.

Tissue affinities are conventionally determined from in vivo steady-state tissue and plasma or plasma-water chemical concentration data. In silico approaches were initially developed for preclinical species but standardly applied and tested in human physiologically-based kinetic (PBK) models. Recently, generic PBK models for farm animals have been made available and require partition coefficients as input parameters. In the current investigation, data for species-specific tissue compositions have been collected, and prediction of chemical distribution in various tissues of livestock species for cattle, chicken, sheep and swine have been performed. Overall, tissue composition was very similar across the four farm animal species. However, small differences were observed in moisture, fat and protein content in the various organs within each species. Such differences could be attributed to factors such as variations in age, breed, and weight of the animals and general conditions of the animal itself. With regards to the predictions of tissue:plasma partition coefficients, 80 %, 71 %, 77 % of the model predictions were within a factor 10 using the methods of Berezhkovskiy (2004), Rodgers and Rowland (2006) and Schmitt (2008). The method of Berezhkovskiy (2004) was often providing the most reliable predictions except for swine, where the method of Schmitt (2008) performed best. In addition, investigation of the impact of chemical classes on prediction performance, all methods had very similar reliability. Notwithstanding, no clear pattern regarding specific chemicals or tissues could be detected for the values predicted outside a 10-fold change in certain chemicals or specific tissues. This manuscript concludes with the need for future research, particularly focusing on lipophilicity and species differences in protein binding.

Application of a generic PBK model for beef cattle: Tissue/fluid correlations of paracetamol and NSAIDs.

Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) and paracetamol can be administered off-label to cattle. Since the use of these veterinary medicines in cattle may pose a public health risk after meat consumption, it is important to translate measured concentrations in urine and tissues into concentrations in meat for human consumption. A generic physiologically-based kinetic (PBK) model for cattle can enable this translation. In this work, a beef cattle PBK model was applied to calculate the relationships between concentrations in different bovine tissues and those were compared to measured concentrations in different matrices. Sixty-seven kidney samples, the corresponding urine and meat samples, and available 19 serum samples were analysed. Overall, 70% of the PBK model predictions are within a 2-fold factor and relationships for kidney/meat, urine/meat, and plasma/meat ratios were established. The conversions of measured kidney concentrations into meat concentrations were mostly within a factor two, while those based on plasma and urine were underpredicted. Based on these ratios, plasma and urine could be used as an appropriate surrogate matrix for a fast, simple in vivo sample screening test under field conditions, such as in local farms and slaughterhouses, to predict a maximum residue level exceedance in meat, reducing the number of test samples.

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.

Fipronil and fipronil sulfone in chicken: From in vitro experiments to in vivo PBK model predictions.

In 2017 a large-scale fipronil contamination in eggs occurred in several European countries. Fipronil and its metabolites have the potential to be transferred into the eggs of laying hens, thereby entering the human food chain. Here, first the metabolism of fipronil was measured in vitro using chicken liver S9. The results show that fipronil is mainly metabolised into fipronil sulfone and the clearance obtained in vitro was extrapolated to in vivo liver clearance. In a second step a physiologically based kinetic model was developed with a focus on fipronil and its major sulfone metabolite and the model outcome was compared to available in vivo data in eggs from the literature. The experimentally obtained clearance was used as model input to evaluate whether such an in vitro-based model can be used in an early phase of a contamination incident to predict the time-concentration curves. Overall, all model predictions were within a 10-fold difference and the estimated elimination half-life for fipronil equivalents was 14 days. In vitro experiments are definitely recommended compared to in vivo studies, since they provide a fast first insight into the behaviour of a chemical in an organism.

Human Variability in Carboxylesterases and carboxylesterase-related Uncertainty Factors for Chemical Risk Assessment.

Carboxylesterases (CES) are an important class of enzymes involved in the hydrolysis of a range of chemicals and show large inter-individual variability in vitro. An extensive literature search was performed to identify in vivo probe substrates for CES1 and CES2 together with their protein content and enzymatic activity. Human pharmacokinetic (PK) data on Cmax, clearance, and AUC were extracted from 89 publications and Bayesian meta-analysis was performed using a hierarchical model to derive CES-related variability distributions and related uncertainty factors (UF). The CES-related variability indicated that 97.5% of healthy adults are covered by the kinetic default UF (3.16), except for clopidogrel and dabigatran etexilate. Clopidogrel is metabolised for a small amount by the polymorphic CYP2C19, which can have an impact on the overall pharmacokinetics, while the variability seen for dabigatran etexilate might be due to differences in the absorption, since this can be influenced by food intake. The overall CES-related variability was moderate to high in vivo (

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 (fmCYP2D6 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 FmCYP2D6 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.

Metabolism and pharmacokinetics of pharmaceuticals in cats (Felix sylvestris catus) and implications for the risk assessment of feed additives and contaminants.

In animal health risk assessment, hazard characterisation of feed additives has been often using the default uncertainty factor (UF) of 100 to translate a no-observed-adverse-effect level in test species (rat, mouse, dog, rabbit) to a 'safe' level of chronic exposure in farm and companion animal species. Historically, both 10-fold factors have been further divided to include chemical-specific data in both dimensions when available. For cats (Felis Sylvestris catus), an extra default UF of 5 is applied due to the species' deficiency in particularly glucuronidation and glycine conjugation. This paper aims to assess the scientific basis and validity of the UF for inter-species differences in kinetics (4.0) and the extra UF applied for cats through a comparison of kinetic parameters between rats and cats for 30 substrates of phase I and phase II metabolism. When the parent compound undergoes glucuronidation the default factor of 4.0 is exceeded, with exceptions for zidovudine and S-carprofen. Compounds that were mainly renally excreted did not exceed the 4.0-fold default. Mixed results were obtained for chemicals which are metabolised by CYP3A in rats. When chemicals were administered intravenously the 4.0-fold default was not exceeded with the exception of clomipramine, lidocaine and alfentanil. The differences seen after oral administration might be due to differences in first-pass metabolism and bioavailability. Further work is needed to further characterise phase I, phase II enzymes and transporters in cats to support the development of databases and in silico models to support hazard characterisation of chemicals particularly for feed additives.

Human variability in isoform-specific UDP-glucuronosyltransferases: markers of acute and chronic exposure, polymorphisms and uncertainty factors.

UDP-glucuronosyltransferases (UGTs) are involved in phase II conjugation reactions of xenobiotics and differences in their isoform activities result in interindividual kinetic differences of UGT probe substrates. Here, extensive literature searches were performed to identify probe substrates (14) for various UGT isoforms (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT2B7 and UGT2B15) and frequencies of human polymorphisms. Chemical-specific pharmacokinetic data were collected in a database to quantify interindividual differences in markers of acute (Cmax) and chronic (area under the curve, clearance) exposure. Using this database, UGT-related uncertainty factors were derived and compared to the default factor (i.e. 3.16) allowing for interindividual differences in kinetics. Overall, results show that pharmacokinetic data are predominantly available for Caucasian populations and scarce for other populations of different geographical ancestry. Furthermore, the relationships between UGT polymorphisms and pharmacokinetic parameters are rarely addressed in the included studies. The data show that UGT-related uncertainty factors were mostly below the default toxicokinetic uncertainty factor of 3.16, with the exception of five probe substrates (1-OH-midazolam, ezetimibe, raltegravir, SN38 and trifluoperazine), with three of these substrates being metabolised by the polymorphic isoform 1A1. Data gaps and future work to integrate UGT-related variability distributions with in vitro data to develop quantitative in vitro-in vivo extrapolations in chemical risk assessment are discussed.

Ecological risks of imidacloprid to aquatic species in the Netherlands: Measured and estimated concentrations compared to species sensitivity distributions.

Recent declines of insects' biomass have been a major point of interest. While several causes, including use of neonicotinoids like imidacloprid, have been suggested, scientific underpinning is limited. The aim of our study was to assess the potential risk of imidacloprid for freshwater fauna in the Netherlands and to validate the SimpleBox model to allow application elsewhere. To this end, we compared imidacloprid concentrations estimated from emissions using the SimpleBox model to measurements obtained from monitoring databases and calculated the ecological risk based on measured concentrations for aquatic fauna. Imidacloprid concentration estimations were within the range measured, opening opportunities for application of SimpleBox to regions where measurements are limited. Aquatic insects were found to be most sensitive to imidacloprid while amphibians and fish are least sensitive to imidacloprid. In particular, the ecological risk of measured imidacloprid concentration in the Netherlands was 1%, implying that concentrations frequently exceed levels that are lethal in short-term experiments. Hence, based on lab toxicity data, the present study suggests that imidacloprid concentrations can be high enough to explain insect decline observed in the same areas.

Human variability in influx and efflux transporters in relation to uncertainty factors for chemical risk assessment.

Transporters are divided into the ABC and SLC super-families, mediating the cellular efflux and influx of various xenobiotic and endogenous substrates. Here, an extensive literature search was performed to identify in vivo probe substrates for P-gp, BCRP and OAT1/3. For other transporters (e.g. OCT, OATP), no in vivo probe substrates could be identified from the available literature. Human kinetic data (Cmax, clearance, AUC) were extracted from 142 publications and Bayesian meta-analyses were performed using a hierarchical model to derive variability distributions and related uncertainty factors (UFs). For P-gp, human variability indicated that the kinetic default UF (3.16) would cover over 97.5% of healthy individuals, when considering the median value, while the upper confidence interval is exceeded. For BCRP and OAT1/3 human variability indicated that the default kinetic UF would not be exceeded while considering the upper confidence interval. Although limited kinetic data on transporter polymorphisms were available, inter-phenotypic variability for probe substrates was reported, which may indicate that the current default kinetic UF may be insufficient to cover such polymorphisms. Overall, it is recommended to investigate human genetic polymorphisms across geographical ancestry since they provide more robust surrogate measures of genetic differences compared to geographical ancestry alone. This analysis is based on pharmaceutical probe substrates which are often eliminated relatively fast from the human body. The transport of environmental contaminants and food-relevant chemicals should be investigated to broaden the chemical space of this analysis and assess the likelihood of potential interactions with transporters at environmental concentrations.

Bayesian meta-analysis of inter-phenotypic differences in human serum paraoxonase-1 activity for chemical risk assessment.

Human variability in paraoxonase-1 (PON1) activities is driven by genetic polymorphisms that affect the internal dose of active oxons of organophosphorus (OP) insecticides. Here, an extensive literature search has been performed to collect human genotypic frequencies (i.e. L55M, Q192R, and C-108T) in subgroups from a range of geographical ancestry and PON1 activities in three probe substrates (paraoxon, diazoxon and phenyl acetate). Bayesian meta-analyses were performed to estimate variability distributions for PON1 activities and PON1-related uncertainty factors (UFs), while integrating quantifiable sources of inter-study, inter-phenotypic and inter-individual differences. Inter-phenotypic differences were quantified using the population with high PON1 activity as the reference group. Results from the meta-analyses provided PON1 variability distributions and these can be implemented in generic physiologically based kinetic models to develop quantitative in vitro in vivo extrapolation models. PON1-related UFs in the Caucasian population were above the default toxicokinetic UF of 3.16 for two specific genotypes namely -108CC using diazoxon as probe substrate and, -108CT, -108TT, 55MM and 192QQ using paraoxon as probe substrate. However, integration of PON1 genotypic frequencies and activity distributions showed that all UFs were within the default toxicokinetic UF. Quantitative inter-individual differences in PON1 activity are important for chemical risk assessment particularly with regards to the potential sensitivity to organophosphates' toxicity.

An open source physiologically based kinetic model for the chicken (Gallus gallus domesticus): Calibration and validation for the prediction residues in tissues and eggs.

Xenobiotics from anthropogenic and natural origin enter animal feed and human food as regulated compounds, environmental contaminants or as part of components of the diet. After dietary exposure, a chemical is absorbed and distributed systematically to a range of organs and tissues, metabolised, and excreted. Physiologically based kinetic (PBK) models have been developed to estimate internal concentrations from external doses. In this study, a generic multi-compartment PBK model was developed for chicken. The PBK model was implemented for seven compounds (with log Kow range -1.37-6.2) to quantitatively link external dose and internal dose for risk assessment of chemicals. Global sensitivity analysis was performed for a hydrophilic and a lipophilic compound to identify the most sensitive parameters in the PBK model. Model predictions were compared to measured data according to dataset-specific exposure scenarios. Globally, 71% of the model predictions were within a 3-fold change of the measured data for chicken and only 7% of the PBK predictions were outside a 10-fold change. While most model input parameters still rely on in vivo experiments, in vitro data were also used as model input to predict internal concentration of the coccidiostat monensin. Future developments of generic PBK models in chicken and other species of relevance to animal health risk assessment are discussed.

Generic physiologically based kinetic modelling for farm animals: Part II. Predicting tissue concentrations of chemicals in swine, cattle, and sheep.

The development of three generic multi-compartment physiologically based kinetic (PBK) models is described for farm animal species, i.e. cattle, sheep, and swine. The PBK models allow one to quantitatively link external dose and internal dose for risk assessment of chemicals relevant to food and feed safety. Model performance is illustrated by predicting tissue concentrations of melamine and oxytetracycline and validated through comparison with measured data. Overall, model predictions were reliable with 71% of predictions within a 3-fold of the measured data for all three species and only 6% of predictions were outside a 10-fold of the measured data. Predictions within a 3-fold change were best for cattle, followed by sheep, and swine (82%, 76%, and 63%). Global sensitivity analysis was performed to identify the most sensitive parameters in the PBK model. The sensitivity analysis showed that body weight and cardiac output were the most sensitive parameters. Since interspecies differences in metabolism impact on the fate of a wide range of chemicals, a key step forward is the introduction of species-specific information on transporters and metabolism including expression and activities.

Generic physiologically based kinetic modelling for farm animals: Part I. Data collection of physiological parameters in swine, cattle and sheep.

Physiologically based kinetic (PBK) models for farm animals are of growing interest in food and feed safety with key applications for regulated compounds including quantification of tissue concentrations, kinetic parameters and the setting of safe exposure levels on an internal dose basis. The development and application of these models requires data for physiological, anatomical and chemical specific parameters. Here, we present the results of a structured data collection of anatomical and physiological parameters in three key farm animal species (swine, cattle and sheep). We performed an extensive literature search and meta-analyses to quantify intra-species variability and associated uncertainty of the parameters. Parameters were collected for organ weights and blood flows in all available breeds from 110 scientific publications, of which 29, 48 and 33 for cattle, sheep, and swine, respectively. Organ weights were available in literature for all three species. Blood flow parameter values were available for all organs in sheep but were scarcer in swine and cattle. Furthermore, the parameter values showed a large intra-species variation. Overall, the parameter values and associated variability provide reference values which can be used as input for generic PBK models in these species.

Physiologically based kinetic models for farm animals: Critical review of published models and future perspectives for their use in chemical risk assessment.

Physiologically based kinetic (PBK) models in the 10 most common species of farm animals were identified through an extensive literature search. This resulted in 39 PBK models, mostly for pharmaceuticals. The models were critically assessed using the WHO criteria for model evaluation, i.e. 1) purpose, 2) structure and mathematical representation, 3) computer implementation, 4) parameterisation, 5) performance, and 6) documentation. Overall, most models were calibrated and validated with published data (92% and 67% respectively) but only a fraction of model codes were published along with the manuscript (28%) and local sensitivity analysis was performed without considering global sensitivity analysis. Hence, the reliability of these PBK models is hard to assess and their potential for use in chemical risk assessment is limited. In a risk assessment context, future PBK models for farm animals should include a more generic and flexible model structure, use input parameters independent on calibration and include assessment tools to assess model performance. Development and application of PBK models for farm animal species would furthermore benefit from the setup of structured databases providing data on physiological and chemical-specific parameters as well as enzyme expression and activities to support the development of species-specific QIVIVE models.

Evaluation of SimpleTreat 4.0: Simulations of pharmaceutical removal in wastewater treatment plant facilities.

In this study, the removal of pharmaceuticals from wastewater as predicted by SimpleTreat 4.0 was evaluated. Field data obtained from literature of 43 pharmaceuticals, measured in 51 different activated sludge WWTPs were used. Based on reported influent concentrations, the effluent concentrations were calculated with SimpleTreat 4.0 and compared to measured effluent concentrations. The model predicts effluent concentrations mostly within a factor of 10, using the specific WWTP parameters as well as SimpleTreat default parameters, while it systematically underestimates concentrations in secondary sludge. This may be caused by unexpected sorption, resulting from variability in WWTP operating conditions, and/or QSAR applicability domain mismatch and background concentrations prior to measurements. Moreover, variability in detection techniques and sampling methods can cause uncertainty in measured concentration levels. To find possible structural improvements, we also evaluated SimpleTreat 4.0 using several specific datasets with different degrees of uncertainty and variability. This evaluation verified that the most influencing parameters for water effluent predictions were biodegradation and the hydraulic retention time. Results showed that model performance is highly dependent on the nature and quality, i.e. degree of uncertainty, of the data. The default values for reactor settings in SimpleTreat result in realistic predictions.