Toxicokinetic modeling and its applications in chemical risk assessment

Screening of the antileishmanial and antiplasmodial potential of synthetic 2-arylquinoline analogs

In this study, six analogs of 2-arylquinoline were synthesized and evaluated for their in vitro and in vivo antiplasmodial and leishmanicidal activity. At a later stage, hemolytic activity and druggability were tested in vitro and in silico, respectively, observing as a result: firstly, compounds showed half-maximal effective concentration (EC50) values between 3.6 and 19.3 µM. Likewise, a treatment using the compounds 4a-f caused improvement in most of the treated hamsters and cured some of them. Regarding the antiplasmodial activity, the compounds showed moderate to high activity, although they did not show hemolytic activity. Furthermore, 4e and 4f compounds were not able to control P. berghei infection when administered to animal models. Molecular dynamic simulations, molecular docking and ligand binding affinity indicate good characteristics of the studied compounds, which are expected to be active. And lastly, the compounds are absorbable at the hematoencephalic barrier but not in the gastrointestinal tract. In summary, ADMET properties suggest that these molecules may be used as a safe treatment against Leishmania.

A State-of-the-Science Review of Interactions of Per- and Polyfluoroalkyl Substances (PFAS) with Renal Transporters in Health and Disease: Implications for Population Variability in PFAS Toxicokinetics

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous in the environment and have been shown to cause various adverse health impacts. In animals, sex- and species-specific differences in PFAS elimination half-lives have been linked to the activity of kidney transporters. However, PFAS molecular interactions with kidney transporters are still not fully understood. Moreover, the impact of kidney disease on PFAS elimination remains unclear.

OBJECTIVES

This state-of-the-science review integrated current knowledge to assess how changes in kidney function and transporter expression from health to disease could affect PFAS toxicokinetics and identified priority research gaps that should be addressed to advance knowledge.

METHODS

We searched for studies that measured PFAS uptake by kidney transporters, quantified transporter-level changes associated with kidney disease status, and developed PFAS pharmacokinetic models. We then used two databases to identify untested kidney transporters that have the potential for PFAS transport based on their endogenous substrates. Finally, we used an existing pharmacokinetic model for perfluorooctanoic acid (PFOA) in male rats to explore the influence of transporter expression levels, glomerular filtration rate (GFR), and serum albumin on serum half-lives.

RESULTS

The literature search identified nine human and eight rat kidney transporters that were previously investigated for their ability to transport PFAS, as well as seven human and three rat transporters that were confirmed to transport specific PFAS. We proposed a candidate list of seven untested kidney transporters with the potential for PFAS transport. Model results indicated PFOA toxicokinetics were more influenced by changes in GFR than in transporter expression.

DISCUSSION

Studies on additional transporters, particularly efflux transporters, and on more PFAS, especially current-use PFAS, are needed to better cover the role of transporters across the PFAS class. Remaining research gaps in transporter expression changes in specific kidney disease states could limit the effectiveness of risk assessment and prevent identification of vulnerable populations. https://doi.org/10.1289/EHP11885.

Development, testing, parameterisation, and calibration of a human PBK model for the plasticiser, di (2-ethylhexyl) adipate (DEHA) using in silico, in vitro and human biomonitoring data

Introduction: A physiologically based biokinetic model for di (2-ethylhexyl) adipate (DEHA) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHA following a single oral dosage of 50 mg to two male and two female volunteers. Methods: The model was parameterized using in vitro and in silico methods such as, measured intrinsic hepatic clearance scaled from in vitro to in vivo and algorithmically predicted parameters such as plasma unbound fraction and tissue:blood partition coefficients (PCs). Calibration of the DEHA model was achieved using concentrations of specific downstream metabolites of DEHA excreted in urine. The total fractions of ingested DEHA eliminated as specific metabolites were estimated and were sufficient for interpreting the human biomonitoring data. Results: The specific metabolites of DEHA, mono-2-ethyl-5-hydroxyhexyl adipate (5OH-MEHA), mono-2-ethyl-5-oxohexyl adipate (5oxo-MEHA), mono-5-carboxy-2-ethylpentyl adipate (5cx-MEPA) only accounted for ∼0.45% of the ingested DEHA. Importantly, the measurements of adipic acid, a non-specific metabolite of DEHA, proved to be important in model calibration. Discussion: The very prominent trends in the urinary excretion of the metabolites, 5cx-MEPA and 5OH-MEHA allowed the important absorption mechanisms of DEHA to be modelled. The model should be useful for the study of exposure to DEHA of the general human population.

Development, testing, parameterisation, and calibration of a human PBPK model for the plasticiser, di-(2-ethylhexyl) terephthalate (DEHTP) using in silico, in vitro and human biomonitoring data

A physiologically based pharmacokinetic model for di-(2-ethylhexyl) terephthalate (DEHTP) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHTP following a single oral dose of 50 mg to three male volunteers. In vitro and in silico methods were used to generate parameters for the model. For example, measured intrinsic hepatic clearance scaled from in vitro to in vivo and plasma unbound fraction and tissue:blood partition coefficients (PCs) were predicted algorithmically. Whereas the development and calibration of the DPHP model was based upon two data streams, blood concentrations of parent chemical and first metabolite and the urinary excretion of metabolites, the model for DEHTP was calibrated against a single data stream, the urinary excretion of metabolites. Despite the model form and structure being identical significant quantitative differences in lymphatic uptake between the models were observed. In contrast to DPHP the fraction of ingested DEHTP entering lymphatic circulation was much greater and of a similar magnitude to that entering the liver with evidence for the dual uptake mechanisms discernible in the urinary excretion data. Further, the absolute amounts absorbed by the study participants, were much higher for DEHTP relative to DPHP. The in silico algorithm for predicting protein binding performed poorly with an error of more than two orders of magnitude. The extent of plasma protein binding has important implications for the persistence of parent chemical in venous blood-inferences on the behaviour of this class of highly lipophilic chemicals, based on calculations of chemical properties, should be made with extreme caution. Attempting read across for this class of highly lipophilic chemicals should be undertaken with caution since basic adjustments to PCs and metabolism parameters would be insufficient, even when the structure of the model itself is appropriate. Therefore, validation of a model parameterized entirely with in vitro and in silico derived parameters would need to be calibrated against several human biomonitoring data streams to constitute a data rich source chemical to afford confidence for future evaluations of other similar chemicals using the read-across approach.

Quantitative in vitro to in vivo extrapolation for developmental toxicity potency of valproic acid analogues

BACKGROUND

The developmental toxicity potential (dTP) concentration from the devTOX quickPredict (devTOX^qP ) assay, a metabolomics-based human induced pluripotent stem cell assay, predicts a chemical's developmental toxicity potency. Here, in vitro to in vivo extrapolation (IVIVE) approaches were applied to address whether the devTOX^qP assay could quantitatively predict in vivo developmental toxicity lowest effect levels (LELs) for the prototypical teratogen valproic acid (VPA) and a group of structural analogues.

METHODS

VPA and a series of structural analogues were tested with the devTOX^qP assay to determine dTP concentration and we estimated the equivalent administered doses (EADs) that would lead to plasma concentrations equivalent to the in vitro dTP concentrations. The EADs were compared to the LELs in rat developmental toxicity studies, human clinical doses, and EADs reported using other in vitro assays. To evaluate the impact of different pharmacokinetic (PK) models on IVIVE outcomes, we compared EADs predicted using various open-source and commercially available PK and physiologically based PK (PBPK) models. To evaluate the effect of in vitro kinetics, an equilibrium distribution model was applied to translate dTP concentrations to free medium concentrations before subsequent IVIVE analyses.

RESULTS

The EAD estimates for the VPA analogues based on different PK/PBPK models were quantitatively similar to in vivo data from both rats and humans, where available, and the derived rank order of the chemicals was consistent with observed in vivo developmental toxicity. Different models were identified that provided accurate predictions for rat prenatal LELs and conservative estimates of human safe exposure. The impact of in vitro kinetics on EAD estimates is chemical-dependent. EADs from this study were within range of predicted doses from other in vitro and model organism data.

CONCLUSIONS

This study highlights the importance of pharmacokinetic considerations when using in vitro assays and demonstrates the utility of the devTOX^qP human stem cell-based platform to quantitatively assess a chemical's developmental toxicity potency.

Toxicokinetic of cyphenothrin in rabbits

Type II pyrethroids, including cyphenothrin, have a wider efficacy and spectrum of action because they have a killing effect rather than a knockdown effect on pests. For this reason, they are among the most widely used pyrethroid groups today. In addition, this group also has repellent activity. Thus, cyphenothrin is a commonly used pyrethroid, which poses an exposure/toxicity risk for living organisms. Toxicokinetic studies have an important place in predicting the toxicity risks of compounds and evaluating viable treatment options. In this study, the toxicokinetics of cyphenothrin were investigated in rabbits. The animal material of the study comprised 6-month-old female 14 New Zealand rabbits, each weighing 2-2.5 kg. The animals were randomly assigned to two groups, each of 7 animals. The rabbits in group 1 were administered a single dose of 2.5 mg/kg bw cyphenothrin in dimethyl sulfoxide as an intravenous bolus, while the rabbits in group 2 were administered a single dose of 2.5 mg/kg bw cyphenothrin in the same vehicle as an oral bolus. Following the administration of cyphenothrin, blood samples were taken at certain intervals from the auricular vein into heparinized tubes. Plasma cyphenothrin levels were determined by gas chromatography, using a capillary column and a micro-electron capture detector. For orally administered cyphenothrin, the plasma maximum concentration (Cmax), time to reach the maximum value (tmax), half-life (t1/2β), mean residence time (MRT), area under the curve (AUC0→∞), and bioavailability (F) values were determined as 172.28 ± 47.30 ng/ml, 1.07 ± 0.42 h, 12.95 ± 1.11 h, 17.79 ± 1.69 h, 2220.07 ± 572.02 ng/h/ml, and 29.50%, respectively. For intravenous cyphenothrin, the t1/2β, MRT and AUC0→∞ values were ascertained as 7.66 ± 0.74 h, 9.28 ± 0.62 h, and 7524.31 ± 2988.44 ng/h/ml, respectively. Although the bioavailability of cyphenothrin was limited when taken orally, its half-life and mean residence time in the body were found to be long. This suggests that high doses of this pesticide may pose a poisoning risk.

Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies

Human health risks from chronic exposures to environmental chemicals are typically estimated from potential human exposure estimates and dose-response data obtained from repeated-dose animal toxicity studies. Various criteria are available for selecting the top (highest) dose used in these animal studies. For example, toxicokinetic (TK) and toxicological data provided by shorter-term or dose range finding studies can be evaluated in a weight of evidence approach to provide insight into the dose range that would provide dose-response data that are relevant to human exposures. However, there are concerns that a top dose resulting from the consideration of TK data may be too low compared to other criteria, such as the limit dose or the maximum tolerated dose. In this paper, we address several concerns related to human exposures by discussing 1) the resources and methods available to predict human exposure levels and the associated uncertainty and variability, and 2) the margin between predicted human exposure levels and the dose levels used in repeated-dose animal studies. A series of case studies, ranging from data-rich to data-poor chemicals, are presented to demonstrate that expected human exposures to environmental chemicals are typically orders of magnitude lower than no-observed-adverse-effect levels/lowest-observed-adverse-effect levels (NOAELs/LOAELs) when available (used as conservative surrogates for top doses). The results of these case studies support that a top dose based, in part, on TK data is typically orders of magnitude higher than expected human exposure levels.

A PBPK model describing the pharmacokinetics of γ-HBCD exposure in mice

The brominated flame retardant, hexabromocyclododecane (HBCD), is added-but not bound-to consumer products and is eventually found in the environment and human tissues. Commercial-grade HBCD mixtures contain three major stereoisomers, alpha (α), beta (β), and gamma (γ), that are typically at a ratio of 12%:6%:82%, respectively. Although HBCD is widely used, the toxicological effects from its exposure in humans are not clearly understood. Using a physiologically based pharmacokinetic (PBPK) model could help improve our understanding of the toxicity of HBCD. The aim of this work was to develop a PBPK model, consisting of five permeability limited compartments (i.e., brain, liver, adipose tissue, blood, and rest of the body), to evaluate the pharmacokinetics of γ-HBCD in C57BL/6 mice. Physiological parameters related to body size, organ weights, and blood flow were taken from the literature. All partition coefficients were calculated based on the log Kow. The elimination in urine and feces was optimized to reflect the percent dose eliminated, as published in the literature. Compared with data from the literature for brain, liver, blood, and adipose tissue, the model simulations accurately described the mouse data set within 1.5-fold of the data points. Also, two examples showing the utility of the PBPK model supplement the information regarding the internal dose that caused the health effects observed during these studies. Although this version of the PBPK model expressly describes γ-HBCD, more efforts are needed to clarify and improve the model to discriminate between the α, β, and γ stereoisomers.

Development, Testing, Parameterisation and Calibration of a Human PBPK Model for the Plasticiser, Di-(2-propylheptyl) Phthalate (DPHP) Using in Silico, in vitro and Human Biomonitoring Data

A physiologically based pharmacokinetic model for Di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the biokinetics in humans after single oral doses. The model was parameterized with in vitro and in silico derived parameters and uncertainty and sensitivity analysis was used during the model development process to assess structure, biological plausibility and behaviour prior to simulation and analysis of human biological monitoring data. To provide possible explanations for some of the counter-intuitive behaviour of the biological monitoring data the model included a simple lymphatic uptake process for DPHP and enterohepatic recirculation (EHR) for DPHP and the mono ester metabolite mono-(2-propylheptyl) phthalate (MPHP). The model was used to simultaneously simulate the concentration-time profiles of blood DPHP, MPHP and the urinary excretion of two metabolites, mono-(2-propyl-6-hydroxyheptyl) phthalate (OH-MPHP) and mono-(2-propyl-6-carboxyhexyl) phthalate (cx-MPHP). The availability of blood and urine measurements permitted a more robust qualitative and quantitative investigation of the importance of EHR and lymphatic uptake. Satisfactory prediction of blood DPHP and urinary metabolites was obtained whereas blood MPHP was less satisfactory. However, the delayed peak of DPHP concentration relative to MPHP in blood and second order metabolites in urine could be explained as a result of three processes: 1) DPHP entering the systemic circulation from the lymph, 2) rapid and very high protein binding and 3) the efficiency of the liver in removing DPHP absorbed via the hepatic route. The use of sensitivity analysis is considered important in the evaluation of uncertainty around in vitro and in silico derived parameters. By quantifying their impact on model output sufficient confidence in the use of a model should be afforded. This approach could expand the use of PBPK models since parameterization with in silico techniques allows for rapid model development. This in turn could assist in reducing the use of animals in toxicological evaluations by enhancing the utility of “read across” techniques.

Development and Application of an interactive Physiologically Based Pharmacokinetic (iPBPK) Model to Predict Oxytetracycline Tissue Distribution and Withdrawal Intervals in Market-Age Sheep and Goats

Oxytetracycline (OTC) is a widely used antibiotic in food-producing animals. Extralabel use of OTC is common and may lead to violative residues in edible tissues. It is important to have a quantitative tool to predict scientifically-based withdrawal intervals (WDIs) after extralabel use in food animals to ensure human food safety. This study focuses on developing a physiologically based pharmacokinetic (PBPK) model for OTC in sheep and goats. The model included seven compartments: plasma, lung, liver, kidneys, muscle, fat, and rest of the body. The model was calibrated with serum and tissue (liver, muscle, kidney, and fat) concentration data following a single intramuscular (IM, 20 mg/kg) and/or intravenous (IV, 10 mg/kg) administration of a long-acting formulation in sheep and goats. The model was evaluated with independent datasets from Food Animal Residue Avoidance Databank (FARAD). Results showed that the model adequately simulated the calibration datasets with an overall estimated coefficient of determination (R2) of 0.95 and 0.92, respectively, for sheep and goat models and had acceptable accuracy for the validation datasets. Monte Carlo sampling technique was applied to predict the time needed for drug concentrations in edible tissues to fall below tolerances for the 99th percentiles of the population. The model was converted to a web-based interactive PBPK (iPBPK) interface to facilitate model applications. This iPBPK model provides a useful tool to estimate WDIs for OTC after extralabel use in small ruminants to ensure food safety and serves as a basis for extrapolation to other tetracycline drugs and other food animals.

Accurate assessment of parabens exposure in healthy Chinese female adults: Findings from a multi-pathway exposure assessment coupled with intervention study

Exposure of humans to parabens is widespread and urinary parabens are widely used as exposure biomarkers. However, are the levels of these chemicals suitable to assess exposure to parabens? We conducted an intervention study by controlling the use of personal care products (PCPs) to explore the exposure of parabens. Ten female participants were recruited who were treated with different types of PCPs during the 18-day study period. The concentrations of parabens and their metabolites in matrices of different exposure pathways (dust, drinking water and dietary food) and urine samples were determined. We demonstrated that PCPs were the major sources of parabens, accounting for >99% of total exposure. The metabolites were nonspecific to individual parabens and could not be used as exposure biomarkers. Urinary paraben concentrations were positively correlated with external exposure levels. However, poor reproducibility was observed, with intraclass correlation coefficients (ICC) ranging from 0.125 to 0.295 in unadjusted urinary concentrations. Creatinine-adjusting could not significantly improve the ICC values in random spot samples. After adjusting for both creatinine and kinetic models, the ICC values ranged from 0.695 to 0.886, indicating a good reproducibility. So, toxicokinetic parameters may be taken into consideration for precise monitoring of exposures for the non-persistent pollutants.

Overview of Pharmacokinetics and Liver Toxicities of Radix Polygoni Multiflori

Radix Polygoni Multiflori (RPM), a traditional Chinese medicine, has been used as a tonic and an anti-aging remedy for centuries. However, its safe and effective application in clinical practice could be hindered by its liver injury potential and lack of investigations on its hepatotoxicity mechanism. Our current review aims to provide a comprehensive overview and a critical assessment of the absorption, distribution, metabolism, excretion of RPM, and their relationships with its induced liver injury. Based on the well-reported intrinsic liver toxicity of emodin, one of the major components in RPM, it is concluded that its plasma and liver concentrations could attribute to RPM induced liver injury via metabolic enzymes alteration, hepatocyte apoptosis, bile acids homeostasis disruption, and inflammatory damage. Co-administered 2,3,5,4'-tetrahydroxystilbene-2-O-β-D-glucopyranoside in RPM and other drugs/herbs could further aggravate the hepatotoxicity of emodin via enhancing its absorption and inhibiting its metabolism. To ensure the safe clinical use of RPM, a better understanding of the toxicokinetics and effect of its co-occurring components or other co-administered drugs/herbs on the pharmacokinetics of emodin is warranted.

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).

Human continuous hydrogen cyanide inhalation predictor with a physiologically based pharmacokinetic (PBPK) model

Hydrogen cyanide (HCN) is volatile and highly toxic with acute and chronic effects on humans. Gaseous HCN enters the atmosphere from natural processes or industrial activities, which lead to human exposure. Effective intervention in cases of HCN inhalation requires an efficient diagnostic tool. The existing physiologically based pharmacokinetic (PBPK) model for HCN cannot clearly simulate continuous HCN inhalation or predict HCN levels in inhaled air. The current study presents a PBPK model for continuous inhalation of HCN, called Human Continuous Cyanide Inhalation Predictor (HCCIP). Since existing data on pharmacokinetics of HCN inhalation are limited, HCCIP utilizes extensive data from the current authors' PBPK model on cyanide ingestion. The structure of HCCIP comprises the lungs, kidneys, liver, and slowly perfused tissue. In both the human body and in exhaled air, HCCIP features the ability to predict concentration-time courses of cyanide. Moreover, HCCIP can predict HCN concentration in inhaled air from known blood cyanide levels. After completion, the results of HCCIP were validated against preexisting published datasets. The simulation results agreed with these datasets, validating the model. The HCCIP model is an effective tool for assessing risk from continuous HCN inhalation, and HCCIP extends the capabilities of air dispersion modeling, such as AERMOD or CALPUFF, to assess HCN risk from specific release sources.

Database of pharmacokinetic time-series data and parameters for 144 environmental chemicals

Time courses of compound concentrations in plasma are used in chemical safety analysis to evaluate the relationship between external administered doses and internal tissue exposures. This type of experimental data is rarely available for the thousands of non-pharmaceutical chemicals to which people may potentially be unknowingly exposed but is necessary to properly assess the risk of such exposures. In vitro assays and in silico models are often used to craft an understanding of a chemical's pharmacokinetics; however, the certainty of the quantitative application of these estimates for chemical safety evaluations cannot be determined without in vivo data for external validation. To address this need, we present a public database of chemical time-series concentration data from 567 studies in humans or test animals for 144 environmentally-relevant chemicals and their metabolites (187 analytes total). All major administration routes are incorporated, with concentrations measured in blood/plasma, tissues, and excreta. We also include calculated pharmacokinetic parameters for some studies, and a bibliography of additional source documents to support future extraction of time-series. In addition to pharmacokinetic model calibration and validation, these data may be used for analyses of differential chemical distribution across chemicals, species, doses, or routes, and for meta-analyses on pharmacokinetic studies.

The Influence of Obesity on the Pharmacokinetics of Dioxin in Mice: An Assessment Using Classical and PBPK Modeling

The effects of body fat mass on the elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) was examined in mice. When male C57BL/6J mice are fed a high-fat, simple carbohydrate diet (HFD) for 13 weeks, they develop an obese phenotype. In contrast, A/J mice fed an HFD do not become obese. After 13 weeks on a normal diet (ND) or HFD, male C57BL/6J and A/J mice received a single dose by gavage of 0.1 or 5.0 µg of 2,3,7,8-tetrachloro[1,6-3H] dibenzo-p-dioxin per kg body weight. Using classical pharmacokinetics, the blood elimination half-life of TCDD was approximately 10 and 2 times longer in the C57BL/6J on the HFD compared with the mice on the ND at 0.1 and 5.0 μg/kg doses, respectively. The diet did not increase the blood half-life of TCDD in the A/J mice, which did not get obese. Using a physiologically based pharmacokinetic model for TCDD that incorporated experimentally derived percent body fat mass and tissue partition coefficients, as well as data on hepatic sequestration, did not provide accurate predictions to the data and could not explain the increase in half-life of TCDD in the HFD groups. This work demonstrates that obesity influences the half-life of TCDD, but other undetermined factors are involved in its elimination because the increase in body fat mass, decreases in cytochrome P4501A2, and altered partition coefficients could not completely explain the prolonged half-life.

QSAR modeling of adipose/blood partition coefficients of Alcohols, PCBs, PBDEs, PCDDs and PAHs: A data gap filling approach

Physiologically-based toxicokinetic (PBTK) model has immense role to play in the risk assessment process due to specified mathematical representation of the absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) of chemicals in diverse environmental compartment. Determination of adipose/blood partition coefficient [logP_{(adipose/blood)}] is regarded as one of the crucial constraints of PBTK models. In respect to the challenge for identifying the chemical-definite parameters for these models, especially within short time frame and with limited resources, quantitative structure-activity relationship (QSAR) models are beneficial for providing the chemical-specific parameters of PBTK models. In the present study, we have developed robust, statistically highly significant (R² = 0.92, Q_LOO² = 0.90, R_Pred² = 0.92) and mechanistically interpretable three descriptors QSAR models for 67 environmental chemicals [Alcohols, polybrominated diphenyl ethers (PBDEs), polychlorinated dibenzodioxins (PCDDs), polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs)] employing the experimental values of adipose/blood partition coefficient for human. The partitioning of chemicals into adipose tissue and blood offers information related to distribution and toxicological effects of these molecules in to the mammal system. The developed models are helpful to understand the mechanistic basis of toxicokinetic processes into the mammal system followed by risk assessment and risk management process. The applicability domain (AD) of the developed model was checked and followed by its employment to predict adipose/blood partition coefficient of 513 environmental contaminants consist of PCBs, PBDEs, PCDDs and PAHs from USA Environmental protection agency (US EPA) site.

Statistical relationship between metabolic decomposition and chemical uptake predicts bioconcentration factor data for diverse chemical exposures

BACKGROUND

A challenge of in vitro to in vivo extrapolation (IVIVE) is to predict the physical state of organisms exposed to chemicals in the environment from in vitro exposure assay data. Although toxicokinetic modeling approaches promise to bridge in vitro screening data with in vivo effects, they are often encumbered by a need for redesign or re-parameterization when applied to different tissues or chemicals.

RESULTS

We demonstrate a parameterization of reverse toxicokinetic (rTK) models developed for the adult zebrafish (Danio rerio) based upon particle swarm optimizations (PSO) of the chemical uptake and degradation rates that predict bioconcentration factors (BCF) for a broad range of chemicals. PSO reveals a relationship between chemical uptake and decomposition parameter values that predicts chemical-specific BCF values with moderate statistical agreement to a limited yet diverse chemical dataset, and all without a need to retrain the model to new data.

CONCLUSIONS

The presented model requires only the octanol-water partitioning ratio to predict BCFs to a fidelity consistent with existing QSAR models. This success begs re-evaluation of the modeling assumptions; specifically, it suggests that chemical uptake into arterial blood may be limited by transport across gill membranes (diffusion) rather than by counter-current flow between gill lamellae (convection). Therefore, more detailed molecular modeling of aquatic respiration may further improve predictive accuracy of the rTK approach.

Formation of PFAAs in fish through biotransformation: A PBPK approach

A physiologically-based pharmacokinetic (PBPK) model for perfluorinated alkyl acids (PFAAs) in rainbow trout has been updated to include formation of perfluorooctanoic acid (PFOA) from the biotransformation of 8:2 fluorotelomer carboxylic acid (8:2 FTCA). The updated model is dynamic and simulates both uptake and depuration phases. Two empirical studies are used to parameterize and test the model. In the first case, parameters related to fecal elimination and protein binding were optimized. In the second case, parameters were sourced either from literature or from optimized values based on the first study to test model performance. Optimization of parameters resulted in a decrease in the difference between experimental data and simulation results by 57 and 23 percent for the first and the second case, respectively, compared to the original case. Sensitivity analysis was performed to identify important parameters, and uncertainty in model prediction propagated by these parameters was assessed using Monte Carlo analysis. For each case, 80 and 89 percent, respectively, of median predicted values were within the limits of experimental error when comparing simulated and experimental data. This is the first toxicokinetic model that incorporates biotransformation of PFAA precursors and simultaneously predicts the distribution of the precursor and metabolite in different tissues. The model is mechanistic, and could be applied to simulate a variety of scenarios by using the organism-specific physiological properties compiled here with other chemical-specific parameters (e.g. protein interactions).

Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits

The environmental fates of pharmaceuticals and the effects of crop protection products on non-target species are subjects that are undergoing intense review. Since measuring the concentrations and effects of xenobiotics on all affected species under all conceivable scenarios is not feasible, standard laboratory animals such as rabbits are tested, and the observed adverse effects are translated to focal species for environmental risk assessments. In that respect, mathematical modelling is becoming increasingly important for evaluating the consequences of pesticides in untested scenarios. In particular, physiologically based pharmacokinetic/toxicokinetic (PBPK/TK) modelling is a well-established methodology used to predict tissue concentrations based on the absorption, distribution, metabolism and excretion of drugs and toxicants. In the present work, a rabbit PBPK/TK model is developed and evaluated with data available from the literature. The model predictions include scenarios of both intravenous (i.v.) and oral (p.o.) administration of small and large compounds. The presented rabbit PBPK/TK model predicts the pharmacokinetics (Cmax, AUC) of the tested compounds with an average 1.7-fold error. This result indicates a good predictive capacity of the model, which enables its use for risk assessment modelling and simulations.

Charting a path towards non-destructive biomarkers in threatened wildlife: A systematic quantitative literature review

Threatened species are susceptible to irreversible population decline caused by adverse sub-lethal effects of chemical contaminant exposure. It is therefore vital to develop the necessary tools to predict and detect these effects as early as possible. Biomarkers of contaminant exposure and effect are widely applied to this end, and a significant amount of research has focused on development and validation of sensitive and diagnostic biomarkers. However, progress in the use biomarkers that can be measured using non-destructive techniques has been relatively slow and there are still many difficulties to overcome in the development of sound methods. This paper systematically quantifies and reviews studies that have aimed to develop or validate non-destructive biomarkers in wildlife, and provides an analysis of the successes of these methods based on the invasiveness of the methods, the potential for universal application, cost, and the potential for new biomarker discovery. These data are then used to infer what methods and approaches appear the most effective for successful development of non-destructive biomarkers of contaminant exposure in wildlife. This review highlights that research on non-destructive biomarkers in wildlife is severely lacking, and suggests further exploration of in vitro methods in future studies.

Evaluating opportunities for advancing the use of alternative methods in risk assessment through the development of fit-for-purpose in vitro assays

An evolving regulatory, scientific, and legislative landscape is driving a fundamental change in how chemical safety decisions are made. As we move to implement changes, regulatory agencies and industry are beginning to adopt tiered approaches, which leverage high-throughput screening technologies for prioritization and read across, followed by interrogation of "hit chemicals" with more rigorous dose-response assessment either in fit-for-purpose human cell-based assays or with traditional in vivo tests. However, to date, suitable in vitro alternatives do not exist for the vast majority of the organ toxicities that form the basis of current regulatory decisions. To successfully support safety decisions, biologically relevant, quantitative, cell-based assays that evaluate dose-response and identify regions of safety for chemical exposure are required. This review evaluates the current state of the science in the development of such assays, identifies key gaps in the current tests, and recommends areas where research efforts may be focused to help move the risk assessment community towards more wide-spread use of in vitro methods. Our analysis suggests that a key shortcoming in the current efforts is the ability to test volatile compounds and to predict pulmonary toxicity. We present a mechanistically-based path forward for the development of a fit-for-purpose lung toxicity assay.

Physiological fidelity or model parsimony? The relative performance of reverse-toxicokinetic modeling approaches

Background

Physiologically-based toxicokinetic (PBTK) models are often developed to facilitate in vitro to in vivo extrapolation (IVIVE) using a top-down, compartmental approach, favoring architectural simplicity over physiological fidelity despite the lack of general guidelines relating model design to dynamical predictions. Here we explore the impact of design choice (high vs. low fidelity) on chemical distribution throughout an animal’s organ system.

Results

We contrast transient dynamics and steady states of three previously proposed PBTK models of varying complexity in response to chemical exposure. The steady states for each model were determined analytically to predict exposure conditions from tissue measurements. Steady state whole-body concentrations differ between models, despite identical environmental conditions, which originates from varying levels of physiological fidelity captured by the models. These differences affect the relative predictive accuracy of the inverted models used in exposure reconstruction to link effects-based exposure data with whole-organism response thresholds obtained from in vitro assay measurements.

Conclusions

Our results demonstrate how disregarding physiological fideltiy in favor of simpler models affects the internal dynamics and steady state estimates for chemical accumulation within tissues, which, in turn, poses significant challenges for the exposure reconstruction efforts that underlie many IVIVE methods. Developing standardized systems-level models for ecological organisms would not only ensure predictive consistency among future modeling studies, but also ensure pragmatic extrapolation of in vivo effects from in vitro data or modeling exposure-response relationships.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0407-3) contains supplementary material, which is available to authorized users.

Direct Dosing of Preweaning Rodents in Toxicity Testing and Research: Deliberations of an ILSI RSI Expert Working Group

Laboratory animal studies designed to assess the effects of exposure of a test substance during postnatal development are commonly utilized in basic research and to evaluate potential hazard to children for chemical and pharmaceutical regulation. Direct dosing, defined here as the administration of a test substance directly to a preweaning mammal, has been identified as a useful tool that can be used in the conduct of such studies for regulatory purposes. The International Life Sciences Institute Risk Science Institute (ILSI RSI) convened an Expert Working Group to develop guidance on the design and implementation of direct dosing regulatory studies on preweaning mammals, which was published as an ILSI monograph in 2003 (Zoetis and Walls, Principles and Practices for Direct Dosing of Pre-Weaning Mammals in Toxicity Testing and Research, Washington, DC: ILSI Press, 2003). A summary of the Working Group conclusions regarding direct dosing studies with laboratory rodents are presented here, although the ILSI monograph also includes rabbits, canines, swine and nonhuman primates. Issues to be considered when designing the protocol include selection of the test species, the route of administration, dose levels, and the timing of dosing. Knowledge of the maturational status of the test species and information on critical windows of development are important in creating a valid study design. Most common routes of administration (e.g., oral, inhalation, injection) are possible with typical laboratory species; however, adjustments may be necessary due to practical considerations. Information on the pharmacokinetic profile in young animals versus adults and in the test species versus humans is very useful for determining dosing parameters. The conduct of the study and the interpretation of the data will be improved by an understanding of confounding factors as well as statistical and biological issues specific for postnatal studies. Ultimately, the success of the study will depend upon careful preparation, including thorough training of the technical staff.

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

Modelling the exposure to chemicals for risk assessment: a comprehensive library of multimedia and PBPK models for integration, prediction, uncertainty and sensitivity analysis - the MERLIN-Expo tool

MERLIN-Expo is a library of models that was developed in the frame of the FP7 EU project 4FUN in order to provide an integrated assessment tool for state-of-the-art exposure assessment for environment, biota and humans, allowing the detection of scientific uncertainties at each step of the exposure process. This paper describes the main features of the MERLIN-Expo tool. The main challenges in exposure modelling that MERLIN-Expo has tackled are: (i) the integration of multimedia (MM) models simulating the fate of chemicals in environmental media, and of physiologically based pharmacokinetic (PBPK) models simulating the fate of chemicals in human body. MERLIN-Expo thus allows the determination of internal effective chemical concentrations; (ii) the incorporation of a set of functionalities for uncertainty/sensitivity analysis, from screening to variance-based approaches. The availability of such tools for uncertainty and sensitivity analysis aimed to facilitate the incorporation of such issues in future decision making; (iii) the integration of human and wildlife biota targets with common fate modelling in the environment. MERLIN-Expo is composed of a library of fate models dedicated to non biological receptor media (surface waters, soils, outdoor air), biological media of concern for humans (several cultivated crops, mammals, milk, fish), as well as wildlife biota (primary producers in rivers, invertebrates, fish) and humans. These models can be linked together to create flexible scenarios relevant for both human and wildlife biota exposure. Standardized documentation for each model and training material were prepared to support an accurate use of the tool by end-users. One of the objectives of the 4FUN project was also to increase the confidence in the applicability of the MERLIN-Expo tool through targeted realistic case studies. In particular, we aimed at demonstrating the feasibility of building complex realistic exposure scenarios and the accuracy of the modelling predictions through a comparison with actual measurements.

Animal-Free Chemical Safety Assessment

The exponential growth of the Internet of Things and the global popularity and remarkable decline in cost of the mobile phone is driving the digital transformation of medical practice. The rapidly maturing digital, non-medical world of mobile (wireless) devices, cloud computing and social networking is coalescing with the emerging digital medical world of omics data, biosensors and advanced imaging which offers the increasingly realistic prospect of personalized medicine. Described as a potential “seismic” shift from the current “healthcare” model to a “wellness” paradigm that is predictive, preventative, personalized and participatory, this change is based on the development of increasingly sophisticated biosensors which can track and measure key biochemical variables in people. Additional key drivers in this shift are metabolomic and proteomic signatures, which are increasingly being reported as pre-symptomatic, diagnostic and prognostic of toxicity and disease. These advancements also have profound implications for toxicological evaluation and safety assessment of pharmaceuticals and environmental chemicals. An approach based primarily on human in vivo and high-throughput in vitro human cell-line data is a distinct possibility. This would transform current chemical safety assessment practice which operates in a human “data poor” to a human “data rich” environment. This could also lead to a seismic shift from the current animal-based to an animal-free chemical safety assessment paradigm.

The application of global sensitivity analysis in the development of a physiologically based pharmacokinetic model for m-xylene and ethanol co-exposure in humans

Global sensitivity analysis (SA) was used during the development phase of a binary chemical physiologically based pharmacokinetic (PBPK) model used for the analysis of m-xylene and ethanol co-exposure in humans. SA was used to identify those parameters which had the most significant impact on variability of venous blood and exhaled m-xylene and urinary excretion of the major metabolite of m-xylene metabolism, 3-methyl hippuric acid. This analysis informed the selection of parameters for estimation/calibration by fitting to measured biological monitoring (BM) data in a Bayesian framework using Markov chain Monte Carlo (MCMC) simulation. Data generated in controlled human studies were shown to be useful for investigating the structure and quantitative outputs of PBPK models as well as the biological plausibility and variability of parameters for which measured values were not available. This approach ensured that a priori knowledge in the form of prior distributions was ascribed only to those parameters that were identified as having the greatest impact on variability. This is an efficient approach which helps reduce computational cost.

A physiologically-based pharmacokinetic model for disposition of 2,3,7,8-TCDD in fathead minnow and medaka

A physiologically-based pharmacokinetic model was developed for the disposition of 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) in 2 fish species--fathead minnow and medaka. The model was developed based on the empirical data on disposition of dioxins in fish tissues, as well as existing knowledge on the mechanisms of uptake, distribution, storage, and elimination of dioxins in various species (other than fish). The present study examined the applicability of mechanisms known to occur in other species for fish and concluded that the same mechanisms defined for disposition of 2,3,7,8-TCDD in (mostly) rodents can be applicable for the 2 fish species examined as well. Parameter values for the model were selected and/or calibrated using available databases. Model compartments included the gill, kidney, liver, and other richly-perfused tissues, as well as fat and other slowly-perfused tissues. The model was calibrated using 2 independent datasets for exposure of fathead minnow and medaka to 2,3,7,8-TCDD in water. The initial values of the model parameters were selected from several sources, and calibrated to represent the 2 exposure datasets. With very few exceptions, the estimated parameter values for the 2 species were comparable, and the final predictions were in strong agreement with the observations. The model developed in the present study can therefore be used in the prediction of the body burden of 2,3,7,8-TCDD in fathead minnow and medaka. Uncertainty in the model prediction as a result of variability in input parameters is discussed for the parameters with the highest impacts on the model outcome.

Pollutant concentration profile reconstruction using digital soft sensors for biodegradation and exposure assessment in the presence of model uncertainty

A new approach to the problem of environmental hazard assessment and monitoring for pollutant biodegradation reaction systems in the presence of uncertainty is proposed using soft sensor-based pollutant concentration dynamic profile reconstruction techniques. In particular, a robust reduced-order soft sensor is proposed that can be digitally implemented in the presence of inherent complexity and the inevitable model uncertainty. The proposed method explicitly incorporates all the available information associated with a process model characterized by varying degrees of uncertainty, as well as available sensor measurements of certain physicochemical quantities. Based on the above information, a reduced-order soft sensor is designed enabling the reliable reconstruction of pollutant concentration profiles in complex biodegradation systems that can not be always achieved due to physical and/or technical limitations associated with current sensor technology. The option of using the aforementioned approach to compute toxic load and persistence indexes on the basis of the reconstructed concentration profiles is also pursued. Finally, the performance of the proposed method is evaluated in two illustrative environmental hazard assessment case studies.

A physiologically based toxicokinetic and toxicodynamic model links the tissue distribution of benzo[a]pyrene and toxic effects in the scallop Chlamys farreri

A physiologically based toxicokinetic and toxicodynamic (PBTK-TD) model was developed for benzo[a]pyrene (B[a]P) in scallop Chlamys farreri. The PBTK model structure consisted of gill, digestive gland, adductor muscle, hemolymph and other tissues. In TD modeling, aryl hydrocarbon hydroxylase (AHH) activity assay, comet assay, protein carbonyl measurement and lipid peroxidation level determination in digestive gland were used as biomarkers to reflect toxic effects. We integrated B[a]P concentration and biomarkers by using sigmoid Emax model in digestive gland. The PBTK-TD model predicted the B[a]P concentrations within each organ compartment and the toxic effects in digestive gland. The results showed that the predicted and measured data in different organs were in good agreement and comet assay was considered as the best biomarker. This model would serve as a useful tool for pollution monitoring and food security.

Review of acute chemical incidents as a first step in evaluating the usefulness of physiologically based pharmacokinetic models in such incidents

CONTEXT. Acute chemical incidents can have substantial public health consequences in terms of morbidity and mortality. OBJECTIVE. We aimed to characterize acute chemical incidents and near-misses in the Netherlands and compare the results with previous studies. This review is a first step in evaluating whether Physiologically Based Pharmacokinetic (PBPK) models can be of value in acute chemical incidents. MATERIAL AND METHODS. Government, regional, municipal and University Hospital Institutes involved in the management of acute chemical incidents in the Netherlands were contacted, and they provided data between 2008 and 2010 on the characteristics and consequences of the incidents. The study is a retrospective epidemiological study based on data from five institutes. Incidents involving biological agents or radiation were excluded. RESULTS. A total of 764 reports were available which involved 722 incidents after cross-matching the different sources of data. Forty incidents were excluded, leaving 682 incidents for which information was available in accordance with the inclusion criteria. Of the 682 incidents included in this study, most occurred in non-industrial buildings (37%) or industrial sites (34%). The most frequently observed event types were loss of containment (60%) and fire (36%), leading to gas emission (54%), followed by spill of liquid or solid chemicals (36%). The chemicals involved were most often products of combustion (e.g. smoke, soot, particles, 25%) and volatile organic compounds (e.g. solvents, styrene, xylene, 23%), followed by inorganic gases (e.g. carbon monoxide, hydrogen, hydrogen sulphide, 13%). A minimum of 847 people experienced adverse health effects following exposure during a chemical incident, and 10 fatalities were reported. The most frequently reported symptoms were respiratory (27%), due to irritant chemicals. The number of incidents related to fire and the number of injured people were higher in this study than in previous studies; 49% of the injured were transported to hospital. DISCUSSION. This study helps to identify which chemicals are frequently involved in acute chemical incidents in the Netherlands. The results will be used in future to assess whether PBPK models may be useful for risk assessment of chemicals often involved in acute chemical incidents and for which human toxicological and kinetic data are scarce.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental-based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents--methyl ethyl ketone, 1-methoxy-2-propanol, and 1,1,1,-trichloroethane--and to take into account sex differences. In a previous human volunteer study we assessed the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could be even more pronounced. A general and simple toxicokinetic model, adapted for three well-known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variability, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Lifetime PCB 153 bioaccumulation and pharmacokinetics in pilot whales: Bayesian population PBPK modeling and Markov chain Monte Carlo simulations

Physiologically based pharmacokinetic (PBPK) models for wild animal populations such as marine mammals typically have a high degree of model uncertainty and variability due to the scarcity of information and the embryonic nature of this field. Parameters values used in marine mammals models are usually taken from other mammalian species (e.g. rats or mice) and might not be entirely suitable to properly explain the kinetics of pollutants in marine mammals. Therefore, several parameters for a PBPK model for the bioaccumulation and pharmacokinetics of PCB 153 in long-finned pilot whales were estimated in the present study using the Bayesian approach executed with Markov chain Monte Carlo (MCMC) simulations. This method uses 'prior' information of the parameters, either from the literature or from previous model runs. The advantage is that this method uses such 'prior' parameters to calculate probability distributions to determine 'posterior' values that best explain the field observations. Those field observations or datasets were PCB 153 concentrations in blubber of long-finned pilot whales from Sandy Cape and Stanley, Tasmania, Australia. The model predictions showed an overall decrease in PCB 153 levels in blubber over the lifetime of the pilot whales. All parameters from the Sandy Cape model were updated using the Stanley dataset, except for the concentration of PCB 153 in the milk. The model presented here is a promising and preliminary start to PBPK modeling in long-finned pilot whales that would provide a basis for non-invasive studies in these protected marine mammals.

Studying permethrin exposure in flight attendants using a physiologically based pharmacokinetic model

Assessment of potential health risks to flight attendants from exposure to pyrethroid insecticides, used for aircraft disinsection, is limited because of (a) lack of information on exposures to these insecticides, and (b) lack of tools for linking these exposures to biomarker data. We developed and evaluated a physiologically based pharmacokinetic (PBPK) model to assess the exposure of flight attendants to the pyrethroid insecticide permethrin attributable to aircraft disinsection. The permethrin PBPK model was developed by adapting previous models for pyrethroids, and was parameterized using currently available metabolic parameters for permethrin. The human permethrin model was first evaluated with data from published human studies. Then, it was used to estimate urinary metabolite concentrations of permethrin in flight attendants who worked in aircrafts, which underwent residual and pre-flight spray treatments. The human model was also applied to analyze the toxicokinetics following permethrin exposures attributable to other aircraft disinsection scenarios. Predicted levels of urinary 3-phenoxybenzoic acid (3-PBA), a metabolite of permethrin, following residual disinsection treatment were comparable to the measurements made for flight attendants. Simulations showed that the median contributions of the dermal, oral and inhalation routes to permethrin exposure in flight attendants were 83.5%, 16.1% and 0.4% under residual treatment scenario, respectively, and were 5.3%, 5.0% and 89.7% under pre-flight spray scenario, respectively. The PBPK model provides the capability to simulate the toxicokinetic profiles of permethrin, and can be used in the studies on human exposure to permethrin.

Case study illustrating the WHO IPCS guidance on characterization and application of physiologically based pharmacokinetic models in risk assessment

The World Health Organization (WHO) International Programme on Chemical Safety (IPCS) Guidance on Characterization and Application of Physiologically Based Pharmacokinetic Models in Risk Assessment (IPCS, 2010) describes key principles for risk assessors and model developers. In the WHO Guidance, a template for model documentation was developed and a case study included. Here the WHO Guidance, including the template, is summarized and an additional case study is presented to illustrate its application, based upon an existing risk assessment for 2-butoxyethanol (CAS NO. 111-76-2). The goal of the WHO Guidance and the current paper is to increase regulatory acceptance of complex biologically descriptive pharmacokinetic (or toxicokinetic) models, such as PBPK models, by facilitating communication and successful interaction between modelers and risk assessors.

Elevation of 4-hydroxynonenal and malondialdehyde modified protein levels in cerebral cortex with cognitive dysfunction in rats exposed to 1-bromopropane

1-Bromopropane (1-BP), an alternative to ozone-depleting solvents (ODS), exhibits central nervous system (CNS) toxicity in animals and humans. This study was designed to relate CNS damage by Morris water maze (MWM) test and oxidative stress to 1-BP exposure in the rat. Male Wistar rats were randomly divided into 4 groups (n=10), and treated with 0, 200, 400 and 800 mg/kgbw 1-BP for consecutive 12 days, respectively. From day 8 to day 12 of the experiment, MWM test was employed to assess the cognitive function of rats. The cerebral cortex of rats was obtained immediately following the 24h after MWM test conclusion. Glutathione (GSH), oxidized glutathione (GSSG) and total thiol (total-SH) content, GSH reductase (GR) and GSH peroxidase (GSH-Px) activities, malondialdehyde (MDA) level, as well as 4-hydroxynonenal (4-HNE) and MDA modified proteins in homogenates of cerebral cortex were measured. The obtained results showed that 1-BP led to cognitive dysfunction of rats, which was evidenced by delayed escape latency time and swimming distances in MWM performance. GSH and total-SH content, GSH/GSSG ratio, GR activity significantly decreased in cerebral cortex of rats, coupling with the increase of MDA level. 4-HNE and MDA modified protein levels obviously elevated after 1-BP exposure. GSH-Px activities in cerebral cortex of rats also increased. These data suggested that 1-BP resulted in enhanced lipid peroxidation of brain, which might play an important role in CNS damage induced by 1-BP.

Computational toxicology: application in environmental chemicals

This chapter provides an overview of computational models that describe various aspects of the source-to-health effect continuum. Fate and transport models describe the release, transportation, and transformation of chemicals from sources of emission throughout the general environment. Exposure models integrate the microenvironmental concentrations with the amount of time an individual spends in these microenvironments to estimate the intensity, frequency, and duration of contact with environmental chemicals. Physiologically based pharmacokinetic (PBPK) models incorporate mechanistic biological information to predict chemical-specific absorption, distribution, metabolism, and excretion. Values of parameters in PBPK models can be measured in vitro, in vivo, or estimated using computational molecular modeling. Computational modeling is also used to predict the respiratory tract dosimetry of inhaled gases and particulates [computational fluid dynamics (CFD) models], to describe the normal and xenobiotic-perturbed behaviors of signaling pathways, and to analyze the growth kinetics of preneoplastic lesions and predict tumor incidence (clonal growth models).