Development of a Physiologically Based Pharmacokinetic Model for Nitrofurantoin in Rabbits, Rats, and Humans.

Nitrofurantoin (NFT) is a commonly used antibiotic for the treatment of urinary tract infections that can cause liver toxicity. Despite reports of hepatic adverse events associated with NFT exposure, there is still limited understanding of the interplay between NFT exposure, its disposition, and the risk of developing liver toxicity. In this study, we aim to develop a physiologically based pharmacokinetic (PBPK) model for NFT in three different species (rabbits, rats, and humans) that can be used as a standard tool for predicting drug-induced liver injury (DILI). We created several versions of the PBPK model using previously published kinetics data from rabbits, and integrated enterohepatic recirculation (EHR) using rat data. Our model showed that active tubular secretion and reabsorption in the kidney are critical in explaining the non-linear renal clearance and urine kinetics of NFT. We subsequently extrapolated the PBPK model to humans. Adapting the physiology to humans led to predictions consistent with human kinetics data, considering a low amount of NFT to be excreted into bile. Model simulations predicted that the liver of individuals with a moderate-to-severe glomerular filtration rate (GFR) is exposed to two-to-three-fold higher concentrations of NFT than individuals with a normal GFR, which coincided with a substantial reduction in the NFT urinary concentration. In conclusion, people with renal insufficiency may be at a higher risk of developing DILI due to NFT exposure, while at the same time having a suboptimal therapeutic effect with a high risk of drug resistance. Our PBPK model can in the future be used to predict NFT kinetics in individual patients on the basis of characteristics like age and GFR.

Development of a rat physiologically based kinetic model (PBK) for three organophosphate flame retardants (TDCIPP, TCIPP, TCEP).

Tris(1,3-dichloro-2-propyl) phosphate (TDCIPP), Tris (1-chloro-2-propyl) phosphate (TCIPP) and tris (2-chloroethyl) phosphate (TCEP) are three widely used organophosphate flame retardants (OPFRs) being frequently detected in human body fluids. Although OPFRs are being detected in human beings, the toxicological effects of their exposure are not clearly understood due to limited data. For this, a physiologically based kinetic model (PBK) was developed in MCSIM integrated with R studio and validated in rats to understand the toxicokinetics of OPFRs for the first time. The model required the enterohepatic recirculation (EHR) mechanism which was included to explain the non-linear data. Model parameters were optimized using the Bayesian framework (Markov Chain Monte Carlo) along with a visual fitting to explain toxicokinetic data. Goodness-of-fit was calculated to evaluate model predictability power in Rstudio. The model can appropriately predict the concentration of OPFRs in several organs like plasma, urine, kidney, etc. within 1-2-fold of experimental data. Slow elimination of OPFRs was observed from adipose tissue and brain at late time points, showing their potential to accumulate upon daily exposure. The use of PBK was demonstrated by reconstructing the oral exposure equivalent to the in-vitro toxic dose to support neurotoxic risk assessment. This version of PBK can be extrapolated to human for toxicological risk assessment. Nonetheless, further investigation is required to understand whether these chemicals follow similar kinetics in humans, which could lead to a greater risk to human health. CODE AVAILABILITY: The model will be available to access through Rshiny using GIThub soon, InSilicoVida/Flame-Retardant-PBPK-Model: It contains organophosphate flame retardant (OPFRs) PBK for TDCIPP, TCIPP and TCEP (github.com).

Chlorpyrifos, permethrin and cyfluthrin effect on cell survival, permeability, and tight junction in an in-vitro model of the human blood-brain barrier (BBB).

The blood-brain barrier (BBB) is a structural and functional interface between the plasma and the human brain. Predictive BBB in-vitro models like immortalized human capillary microvascular endothelial cells (HCMEC/D3) can be used to explore the BBB disruption potential of daily exposed chemicals. The present study was focused on investigating the human BBB permeation potential of one organophosphate pesticide, chlorpyrifos (CPF), and two pyrethroids, permethrin (PMT) and cyfluthrin (CFT). HCMEC/D3 cells were exposed to the chemical and the time-dependent pass across BBB along with permeation coefficient (Papp) was calculated. Transendothelial electrical resistance (TEER) was measured for the cells to check the monolayer formation and later to check the reduction in integrity after chemical exposure. Real time PCR was conducted to investigate the effect of chemicals on the expression BBB´s tight and adherens junction proteins. Calculated Papp value for three chemicals was in the following order: CPF>CFT>PMT, where CPF showed the highest permeation coefficient. TEER calculation showed that the integrity decreased after CPF exposure which was in concordance with Papp value whereas for other chemicals, no change in TEER after exposure was observed. In addition, the transwell study showed a higher efflux ratio (ER) (>2) of CFT indicating that CFT could be a substrate for active transport. For CPF and PMT, ER was less than 2, so no active transport seems to be involved. The evaluation of the mRNA expression analysis revealed a statistically significant decrease in Occludin (OCLN) gene expression for CPF, VE-Cadherin (CDH5) for PMT and Zonula Occludens (ZO1) expression for CFT. Our study showed that CPF has the highest potential for inducing cell death, higher permeation, and capability to induce BBB dysfunction than among the above-mentioned chemicals. Additionally, the results of the permeation study could be useful to build a human PBPK model using in vitro-to-in vivo extrapolation approach.

Unravelling sex-specific BPA toxicokinetics in children using a pediatric PBPK model.

Bisphenol A (BPA) is a widely known endocrine disruptor (ED) found in many children's products such as toys, feeding utensils, and teething rings. Recent epidemiology association studies have shown postnatal BPA exposure resulted in developing various diseases such as diabetes, obesity, and neurodegeneration, etc., later in their lives. However, little is known about its sex-specific metabolism and consequently internal exposure. The aim of this study was to develop a sex-specific pediatric physiologically based pharmacokinetic model (PBPK) for BPA to compare their toxicokinetic differences. First, the published adult PBPK model was re-validated, and then this model was extended by interpolation to incorporate pediatric sex specific physiological and biochemical parameters. We used both the classical body weight and ontogeny-based scaling approach to interpolate the metabolic process. Then, the pharmacokinetic attributes of the models using the two-scaling approach mentioned above were compared with adult model. Further, a sex-specific PBPK model with an ontogeny scaling approach was preferred to evaluate the pharmacokinetic differences. Moreover, this model was used to reconstruct the BPA exposure from two cohorts (Helix and PBAT Cohort) from 7 EU countries. The half-life of BPA was found to be almost the same in boys and girls at the same exposure levels. Our model estimated BPA children's exposure to be about 1500 times higher than the tolerable daily intake (TDI) recently set by European Food Safety Authority (EFSA) i.e., 0.04 ng/kg BW/day. The model demonstrated feasibility of extending the adult PBPK to sex-specific pediatric, thus investigate a gender-specific health risk assessment.

Risk Assessment of Perfluorooctane Sulfonate (PFOS) using Dynamic Age Dependent Physiologically based Pharmacokinetic Model (PBPK) across Human Lifetime.

The widespread use of Perfluorooctane sulfonate (PFOS) in everyday life, its long half-life, and the lipophilicity that makes it easily accumulate in the body, raises the question of its safe exposure among different population groups. There are currently enough epidemiological studies showing evidence of PFOS exposure and its associated adverse effects on humans. Moreover, it is already known that physiological changes along with age e.g. organ volume, renal blood flow, cardiac output and albumin concentrations affect chemicals body burden. Human biomonitoring cohort studies have reported PFOS concentrations in blood and autopsy tissue data with PFOS present in sensitive organs across all human lifespan. However, to interpret such biomonitoring data in the context of chemical risk assessment, it is necessary to have a mechanistic framework that explains show the physiological changes across age affects the concentration of chemical inside different tissues of the human body. PBPK model is widely and successfully used in the field of risk assessment. The objective of this manuscript is to develop a dynamic age-dependent PBPK model as an extension of the previously published adult PFOS model and utilize this model to predict and compare the PFOS tissue distribution and plasma concentration across different age groups. Different cohort study data were used for exposure dose reconstruction and evaluation of time-dependent concentration in sensitive organs. Predicted plasma concentration followed trends observed in biomonitoring data and model predictions showed the increased disposition of PFOS in the geriatric population. PFOS model is sensitive to parameters governing renal resorption and elimination across all ages, which is related to PFOS half-life in humans. This model provides an effective framework for improving the quantitative risk assessment of PFOS throughout the human lifetime, particularly in susceptible age groups. The dynamic age-dependent PBPK model provides a step forward for developing such kind of dynamic model for other perfluoroalkyl substances.

ROS networks: designs, aging, Parkinson's disease and precision therapies.

How the network around ROS protects against oxidative stress and Parkinson's disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only five simpler subnetworks each delivering one type of robustness. The comprehensive dynamic model described in vitro data sets from two independent laboratories. Notwithstanding its five-fold robustness, it exhibited a relatively sudden breakdown, after some 80 years of virtually steady performance: it predicted aging. PD-related conditions such as lack of DJ-1 protein or increased α-synuclein accelerated the collapse, while antioxidants or caffeine retarded it. Introducing a new concept (aging-time-control coefficient), we found that as many as 25 out of 57 molecular processes controlled aging. We identified new targets for "life-extending interventions": mitochondrial synthesis, KEAP1 degradation, and p62 metabolism.

An integrative translational framework for chemical induced neurotoxicity - a systematic review.

Many chemicals in day-to-day and industrial usage have the ability to cross the blood-brain barrier and develop neurotoxicity in humans. There are numerous in vitro, in vivo, epidemiological and in silico studies developed to test the neurotoxicity of such chemicals. This systematic review summarized the endpoints and biochemical markers generated from in vitro models, organism-based models, human studies and in silico tools and how they are used to translate the data for risk assessment of neurotoxic chemicals. Increased evidence about different biomarkers through genomics and proteomics has developed data related to genes and proteins facilitating some understanding about the molecular mechanism of neurotoxicity. Fluid-based biomarkers such as those found in serum, plasma and urine from human studies act as indirect endpoints for neurotoxicity. Meanwhile, with improvement in knowledge of molecular mechanisms and different biomarkers, there is a potential to develop a translational platform that can integrate the biological data from different studies mechanistically and thereby translated across intra and interspecies for neurotoxicity assessment. Further, this review proposed an integrative translational framework combining experimental and in silico studies like toxicokinetic models and integrative systems biology to assess the chemicals for neurotoxicity. This framework can be used to predict the inherent risk of neurotoxicity and extend to such chemicals where less experimental data exists.

Hepatotoxicity of the pesticides imazalil, thiacloprid and clothianidin - Individual and mixture effects in a 28-day study in female Wistar rats.

Humans are exposed to pesticide residues through various food products. As these residues can occur in mixtures, there is a need to investigate possible mixture effects on human health. Recent exposure studies revealed the preponderance of imazalil, thiacloprid, and clothianidin in food diets. In this study, we assessed their toxicity alone and in binary mixtures in a 28-day gavage study in female Wistar rats. Five dose levels (up to 350 mg/kg bw/day) ranging from a typical toxicological reference value to a clear effect dose were applied. Data show that the liver was a target organ of all pesticides and their mixtures. Increases in liver weight were observed and histopathological examination revealed centrilobular hepatocellular hypertrophy and cytoplasm degeneration for all treatment conditions. No accumulation of hepatic triglycerides was reported. Tissue residue analysis showed altered pesticide residues in the liver and the kidney when being in mixture as compared to the levels of pesticide residues for the single compound treatment, indicating possible toxicokinetic interactions. Overall, all mixtures appeared to follow the additivity concept, even though quantitative analysis was limited for some endpoints due to the semi-quantitative nature of the data, raising no specific concern for the risk assessment of the examined pesticides.

Maternal exposure to mixtures of dienestrol, linuron and flutamide. Part I: Feminization effects on male rat offspring.

Exposure to endocrine-disrupting compounds (EDCs) during pregnancy can result in negative health effects in later generations, including sex changes and feminization. The present study assessed the feminization effects on male offspring rats of three EDCs: Dienestrol (DIES), Linuron (LIN), and Flutamide (FLU). Sexually mature female rats were exposed from gestation day (GD) 6 until postnatal day (PND) 21 to: 0.37, 0.75, 1.5, 3.12 or 6.25 µg/kg/day of DIES, 1.5, 3, 6, 12.5, 25 or 50 mg/kg/day of LIN, 3.5, 6.7, 12.5, 25 or 50 mg/kg/day of FLU, and the following mixtures: FLU + DIES (mg/kg/day+µg/kg/day), 3.5 + 0.37, or 3.5 + 3, 25 + 0.37, or 25 + 3; FLU + LIN (mg/kg/day + mg/kg/day), 3.5 + 12.5, or 25 + 12.5; and DIES + LIN (µg/kg/day + mg/kg/day), 0.37 + 12.5, or 3 + 12.5. Anogenital distance (AGD), nipple retention (NR) and cryptorchidism were evaluated. FLU produced a decrease of AGD, an increase of NR, and an increase of cryptorchidism at the highest dose. None of these three endpoints were significantly affected by LIN or DIES treatments alone. Combinations of FLU + LIN and FLU + DIES increased NR, and decreased AGD, while DIES + LIN did not produce any effects in male pups. Results show that FLU is able to induce feminization in male pups, while binary combinations of LIN and DIES did not modify the effects produced by FLU.

Development and evaluation of a harmonized whole body physiologically based pharmacokinetic (PBPK) model for flutamide in rats and its extrapolation to humans.

By their definition, inadvertent exposure to endocrine disrupting compounds (EDCs) intervenes with the endocrine signalling system, even at low dose. On the one hand, some EDCs are used as important pharmaceutical drugs that one would not want to dismiss. On the other hand, these pharmaceutical drugs are having off-target effects and increasingly significant exposure to the general population with unwanted health implications. Flutamide, one of the top pharmaceutical products marketed all over the world for the treatment of prostate cancer, is also a pollutant. Its therapeutic action mainly depends on targeting the androgen receptors and inhibiting the androgen action that is essential for growth and survival of prostate tissue. Currently flutamide is of concern with respect to its categorization as an endocrine disruptor. In this work we have developed a physiologically based pharmacokinetic (PBPK) model of flutamide that could serve as a standard tool for its human risk assessment. First we built the model for rat (where many parameters have been measured). The rat PBPK model was extrapolated to human where the re-parameterization involved human-specific physiology, metabolic kinetics derived from in-vitro studies, and the partition coefficient same as the rat model. We have harmonized the model by integrating different sets of in-vitro, in-vivo and physiological data into a PBPK model. Then the model was used to simulate different exposure scenarios and the results were compared against the observed data. Both uncertainty and sensitivity analysis was done. Since this new whole-body PBPK model can predict flutamide concentrations not only in plasma but also in various organs, the model may have clinical applications in efficacy and safety assessment of flutamide. The model can also be used for reverse dosimetry in the context of interpreting the available biomonitoring data to estimate the degree to which the population is currently being exposed, and a tool for the pharmaceutical companies to validate the estimated Permitted Daily Exposure (PDE) for flutamide.

Oxidative stress in testes of rats exposed to n-butylparaben.

This study was aimed at determining if oxidative stress imbalance in testes of rats occurs after n-butylparaben (n-ButP) exposure. Young male Sprague-Dawley rats were subcutaneously treated with n-ButP during one spermatogenic cycle (57 days) at 0 (control-oil), 150, 300 and 600 mg/kg/d with peanut oil as vehicle. A non-vehicle control group was also included. Antioxidant enzyme activities (superoxide dismutase, catalase, glutathione reductase, and glutathione peroxidase) and levels of reduced and oxidized glutathione were measured in testes. Lipid peroxidation and H2O2 concentrations were also assessed. Results showed an increase of oxidative stress in oil-treated groups, excepting 600 mg/kg/d, suggesting oxidative stress due to peanut oil. A possible antioxidant effect due to n-ButP and its metabolites was suggested at 600 mg/kg/d, the only group not showing oxidative stress. An increase of calcium concentration in testes was also observed. On the other hand, a physiologically-based pharmacokinetic (PBPK) model was developed and the concentrations of n-ButP and its metabolites were simulated in plasma and testes. The peak concentration (Cmax) in testes was found slightly higher than that in plasma. The current results indicate that peanut oil can cause oxidative stress while high doses of n-ButP can act as antioxidant agent in testes.

Prenatal exposure to PFOS and PFOA in a pregnant women cohort of Catalonia, Spain.

This study was aimed at assessing the prenatal exposure to perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in a cohort of pregnant women living in Reus (Tarragona County, Catalonia, Spain). These chemicals were biomonitored in maternal plasma during the first trimester of pregnancy, at delivery, and in cord blood. The dietary exposure of PFOS and PFOA was estimated by using questionnaires of food frequency and water intake, as well as data on food levels previously reported in the same area. In addition, the exposure through air inhalation and indoor dust ingestion was also calculated. Finally, a physiologically-based pharmacokinetic (PBPK) model was applied in order to establish the prenatal exposure of the fetus/child and to adjust exposure assessment vs. biomonitoring results. Probabilistic calculations of fetal exposure were performed by forward internal dosimetry and Monte-Carlo simulation. Mean plasma levels of PFOA were 0.45, 0.13 and 0.12 ng/mL at the first trimester, at delivery and in cord plasma, while those of PFOS were 2.93, 2.21, and 1.17 ng/mL, respectively. Traces of PFOS were found in all samples in the trimester and at delivery, and almost in all cord blood samples. Transplacental transfers of PFOS and PFOA were estimated to be around 70% and 60%, respectively. A temporal decrease trend in plasma levels of PFOS and PFOA was noticed, when comparing current values with data obtained 10 years ago in the same area. In agreement with many other studies, dietary intake was the main route of exposure to PFOS and PFOA in our cohort of pregnant women. It is an important issue to establish the exposure in critical windows periods such as fetal development to perfluoroalkylated substances, but also to other endocrine disrupting chemicals.

Development of a human physiologically based pharmacokinetic (PBPK) model for phthalate (DEHP) and its metabolites: A bottom up modeling approach.

DEHP exposure to human comes from different sources such as food, diet, cosmetics, toys, medical products, and food wraps. Recently, DEHP was categorized as non-persistent endocrine disrupting compounds (EDCs) by the world health organization (WHO). Rat experimental studies showed that phthalate and its metabolite(s) can cause hepatic, developmental and reproductive toxicity. In human, DEHP rapidly metabolizes into a toxic metabolite MEHP. This MEHP further metabolizes into the different chemical forms of 5OH-MEHP, 5oxo-MEHP, 5cx-MEPP and phthalic acid. A simple DEHP pharmacokinetics model has been developed, but with a limited number of metabolites. A chemical like DEHP which extensively metabolised indicate the need of a detail metabolic kinetics study. A physiological based pharmacokinetics (PBPK) model of the DEHP considering all the major metabolites in human, has not been developed yet. The objective of this study is to develop a detailed human PBPK model for the DEHP and its major metabolites by using a bottom-up modelling approach with the integration of a in vitro metabolic data. This approach uses an in-vitro-in-vivo extrapolation (IVIVE) and a quantitative structure-activity relationship (QSAR) method for the parameterization of the model. Monte Carlo simulations were performed to estimate the impact of parametric uncertainty onto the model predictions. First, the model was calibrated using the control human kinetic study that represents the time course of DEHP metabolites concentration in both the blood and the urine. Then, the model was evaluated against the published independent data on different dosing scenarios. The results of model predictions for the DEHP metabolites in both the blood and the urine were well within the range of experimentally observed data. The model also captured the similar trend of time course profile to the observed data, shows model good predictability power. The current developed PBPK model can futher be used for the prediction of the time course of chemical concentrations for the different exposure scenarios not only in the blood and the urine but also in the other compartments. Moreover, this model can also be used to explore different biomonitoring studies for the human health risk assessment and might be useful for integrative toxicological study in improving exposure-target tissue dose-response relationship.

The development of a pregnancy PBPK Model for Bisphenol A and its evaluation with the available biomonitoring data.

Recent studies suggest universal fetal exposure to Bisphenol A (BPA) and its association with the adverse birth outcomes. Estimation of the fetal plasma BPA concentration from the maternal plasma BPA would be highly useful to predict its associated risk to this specific population. The objective of current work is to develop a pregnancy-physiologically based pharmacokinetic (P-PBPK) model to predict the toxicokinetic profile of BPA in the fetus during gestational growth, and to evaluate the developed model using biomonitoring data obtained from different pregnancy cohort studies. To achieve this objective, first, the adult PBPK model was developed and validated with the human BPA toxicokinetic data. This validated human PBPK model was extended to develop a P-PBPK model, which included the physiological changes during pregnancy and the fetus sub-model. The developed model would be able to predict the BPA pharmacokinetics (PKs) in both mother and fetus. Transplacental BPA kinetics parameters for this study were taken from the previous pregnant mice study. Both oral and dermal exposure routes were included into the model to simulate total BPA internal exposure. The impact of conjugation and deconjugation of the BPA and its metabolites on fetal PKs was investigated. The developed P-PBPK model was evaluated against the observed BPA concentrations in cord blood, fetus liver and amniotic fluid considering maternal blood concentration as an exposure source. A range of maternal exposure dose for the oral and dermal routes was estimated, so that simulation concentration matched the observed highest and lowest mother plasma concentration in different cohorts' studies. The developed model could be used to address the concerns regarding possible adverse health effects in the fetus being exposed to BPA and might be useful in identifying critical windows of exposure during pregnancy.

Developing integrated PBPK/PD coupled mechanistic pathway model (miRNA-BDNF): An approach towards system toxicology.

Integration of a dynamic signal transduction pathway into the tissue dosimetry model is a major advancement in the area of computational toxicology. This paper illustrates the ways to incorporate the use of existing system biological model in the field of toxicology via its coupling to the Physiological based Pharmacokinetics and Pharmacodynamics (PBPK/PD) model. This expansion framework of integrated PBPK/PD coupled mechanistic system pathway model can be called as system toxicology that describes the kinetics of both - the chemicals and - biomolecules, help us to understand the dynamic and steady-state behaviors of molecular pathways under perturbed condition. The objective of this article is to illustrate a system toxicology based approach by developing an integrated PBPK/PD coupled miRNA-BDNF pathway model and to demonstrate its application by taking a case study of the PFOS mediated neurotoxicity. System dynamic involves miRNA-mediated BDNF regulation, which plays an important role in the control of neuronal cell proliferation, differentiation, and survivability.

Review on crosstalk and common mechanisms of endocrine disruptors: Scaffolding to improve PBPK/PD model of EDC mixture.

Endocrine disruptor compounds (EDCs) are environment chemicals that cause harmful effects through multiple mechanisms, interfering with hormone system resulting in alteration of homeostasis, reproduction and developmental effect. Many of these EDCs have concurrent exposure with crosstalk and common mechanisms which may lead to dynamic interactions. To carry out risk assessment of EDCs' mixture, it is important to know the detailed toxic pathway, crosstalk of receptor and other factors like critical window of exposure. In this review, we summarize the major mechanism of actions of EDCs with the different/same target organs interfering with the same/different class of hormone by altering their synthesis, metabolism, binding and cellular action. To show the impact of EDCs on life stage development, a case study on female fertility affecting germ cell is illustrated. Based on this summarized discussion, major groups of EDCs are classified based on their target organ, mode of action and potential risk. Finally, a conceptual model of pharmacodynamic interaction is proposed to integrate the crosstalk and common mechanisms that modulate estrogen into the predictive mixture dosimetry model with dynamic interaction of mixture. This review will provide new insight for EDCs' risk assessment and can be used to develop next generation PBPK/PD models for EDCs' mixture analysis.