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

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.

The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment

Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.

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.

Novel test strategies for in vitro seizure liability assessment

INTRODUCTION

The increasing incidence of mental illnesses and neurodegenerative diseases results in a high demand for drugs targeting the central nervous system (CNS). These drugs easily reach the CNS, have a high affinity for CNS targets, and are prone to cause seizures as an adverse drug reaction. Current seizure liability assessment heavily depends on in vivo or ex vivo animal models and is therefore ethically debated, labor intensive, expensive, and not always predictive for human risk.

AREAS COVERED

The demand for CNS drugs urges the development of alternative safety assessment strategies. Yet, the complexity of the CNS hampers reliable detection of compound-induced seizures. This review provides an overview of the requirements of in vitro seizure liability assays and highlights recent advances, including micro-electrode array (MEA) recordings using rodent and human cell models.

EXPERT OPINION

Successful and cost-effective replacement of in vivo and ex vivo models for seizure liability screening can reduce animal use for drug development, while increasing the predictive value of the assays, particularly if human cell models are used. However, these novel test strategies require further validation and standardization as well as additional refinements to better mimic the human in vivo situation and increase their predictive value.

Physiologically based pharmacokinetic (PBPK) modeling of RNAi therapeutics: Opportunities and challenges

Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool with many demonstrated applications in various phases of drug development and regulatory review. RNA interference (RNAi)-based therapeutics are a class of drugs that have unique pharmacokinetic properties and mechanisms of action. With an increasing number of RNAi therapeutics in the pipeline and reaching the market, there is a considerable amount of active research in this area requiring a multidisciplinary approach. The application of PBPK models for RNAi therapeutics is in its infancy and its utility to facilitate the development of this new class of drugs is yet to be fully evaluated. From this perspective, we briefly discuss some of the current computational modeling approaches used in support of efficient development and approval of RNAi therapeutics. Considerations for PBPK model development are highlighted both in a relative context between small molecules and large molecules such as monoclonal antibodies and as it applies to RNAi therapeutics. In addition, the prospects for drawing upon other recognized avenues of PBPK modeling and some of the foreseeable challenges in PBPK model development for these chemical modalities are briefly discussed. Finally, an exploration of the potential application of PBPK model development for RNAi therapeutics is provided. We hope these preliminary thoughts will help initiate a dialogue between scientists in the relevant sectors to examine the value of PBPK modeling for RNAi therapeutics. Such evaluations could help standardize the practice in the future and support appropriate guidance development for strengthening the RNAi therapeutics development program.

MicroRNA-202-3p Targets Brain-Derived Neurotrophic Factor and Is Involved in Depression-Like Behaviors

BACKGROUND

Brain-derived neurotrophic factor (BDNF) and microRNA (miRNA) play crucial roles in the etiology of depression. However, the molecular mechanisms underlying this disease are not fully understood. The primary objective of this study was to investigate the relationship between miR-202-3p and BDNF in a chronic unpredictable mild stress (CUMS) model.

METHODS

Depression model was established with chronic mild unpredictable mild stimulation (CUMS) combined with solitary feeding. The expression levels of miR-202-3p and BDNF in rat hippocampus were measured by qRT-PCR. The novelty inhibition feeding test (NSFT), sucrose preference test (SPT), and forced swimming test (FST) were used to evaluate the functions of miR-202-3p and BDNF. Target gene prediction and screening and luciferase reporter assay were used to verify the target of miR-202-3p. The expression levels of BNDF, CREB1 and p-CREB1 were detected by Western blot.

RESULTS

Upregulation of miR-202-3p was associated with decreased expression of BDNF in the hippocampus of the CUMS model. Antidepressant was observed when LV-BDNF or LV-si-miR-202-3p was injected into the hippocampus. In addition, in the rat hippocampus and cultured nerve cells, the expression levels of BDNF and cyclic AMP response element binding protein 1 (CREB1), which is a target gene of BDNF, were reduced after LV-miR-202-3p injection. Overexpression of miR-202-3p aggravated depressive behavior and decreased the expression levels of BDNF. Luciferase reporter assay also confirmed that BDNF was a target of miR-202-3p.

CONCLUSION

Silencing miR-202-3p can reduce the damage to hippocampal nerve in CUMS rats; the mechanism may be related to the upregulation of BNDF expression. miR-202-3p may be an effective target for the treatment of depression.

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.

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.

Better prediction of the local concentration-effect relationship: the role of physiologically based pharmacokinetics and quantitative systems pharmacology and toxicology in the evolution of model-informed drug discovery and development

Model-informed drug discovery and development (MID3) is an umbrella term under which sit several computational approaches: quantitative systems pharmacology (QSP), quantitative systems toxicology (QST) and physiologically based pharmacokinetics (PBPK). QSP models are built using mechanistic knowledge of the pharmacological pathway focusing on the putative mechanism of drug efficacy; whereas QST models focus on safety and toxicity issues and the molecular pathways and networks that drive these adverse effects. These can be mediated through exaggerated on-target or off-target pharmacology, immunogenicity or the physiochemical nature of the compound. PBPK models provide a mechanistic description of individual organs and tissues to allow the prediction of the intra- and extra-cellular concentration of the parent drug and metabolites under different conditions. Information on biophase concentration enables the prediction of a drug effect in different organs and assessment of the potential for drug-drug interactions. Together, these modelling approaches can inform the exposure-response relationship and hence support hypothesis generation and testing, compound selection, hazard identification and risk assessment through to clinical proof of concept (POC) and beyond to the market.

Mechanistic Computational Models of MicroRNA-Mediated Signaling Networks in Human Diseases

MicroRNAs (miRs) are endogenous non-coding RNA molecules that play important roles in human health and disease by regulating gene expression and cellular processes. In recent years, with the increasing scientific knowledge and new discovery of miRs and their gene targets, as well as the plentiful experimental evidence that shows dysregulation of miRs in a wide variety of human diseases, the computational modeling approach has emerged as an effective tool to help researchers identify novel functional associations between differential miR expression and diseases, dissect the phenotypic expression patterns of miRs in gene regulatory networks, and elucidate the critical roles of miRs in the modulation of disease pathways from mechanistic and quantitative perspectives. Here we will review the recent systems biology studies that employed different kinetic modeling techniques to provide mechanistic insights relating to the regulatory function and therapeutic potential of miRs in human diseases. Some of the key computational aspects to be discussed in detail in this review include (i) models of miR-mediated network motifs in the regulation of gene expression, (ii) models of miR biogenesis and miR⁻target interactions, and (iii) the incorporation of such models into complex disease pathways in order to generate mechanistic, molecular- and systems-level understanding of pathophysiology. Other related bioinformatics tools such as computational platforms that predict miR-disease associations will also be discussed, and we will provide perspectives on the challenges and opportunities in the future development and translational application of data-driven systems biology models that involve miRs and their regulatory pathways in human diseases.

Comparing dietary and non-dietary source contribution of BPA and DEHP to prenatal exposure: A Catalonia (Spain) case study

Bisphenol A (BPA) and Di-(2-ethylhexyl) phthalate (DEHP) are two wide spread chemicals classified as endocrine disruptors (ED). The present study aims to estimate the non-dietary (dermal, non-dietary ingestion and inhalation) exposure to BPA and DEHP for a pregnant women cohort. In addition, to assess the prenatal exposure for the fetus, a physiologically based pharmacokinetic (PBPK) model was used. It was adapted for pregnancy in order to assess the internal dosimetry levels of EDs (BPA and DEHP) in the fetus. Estimates of exposure to BPA and DEHP from all pathways along with their relative importance were provided in order to establish which proportion of the total exposure came from diet and which came from non-dietary exposures. In this study, the different oral dosing scenarios (dietary and non-dietary) were considered keeping inhalation as a continuous exposure case. Total non-dietary mean values were 0.002 µg/kg_bw/day (0.000; 0.004 µg/kg_bw/day for 5th and 95th percentile, respectively) for BPA and 0.597 µg/kg_bw/day (0.116 µg/kg_bw/day and 1.506 µg/kg_bw/day for 5th and 95th percentile, respectively) for DEHP. Indoor environments and especially dust ingestion were the main non-dietary contributors to the total exposure of BPA and DEHP with 60% and 81%. However, as expected, diet showed the higher contribution to total exposure with > 99.9% for BPA and 63% for DEHP. Although diet was considered the primary source of exposure to BPA and phthalates, it must be taken into account that with non-dietary sources the first-pass metabolism is lacking, so these may be of equal or even higher toxicological relevance than dietary sources. The present study is in the framework of "Health and environmental-wide associations based on large population surveys" (HEALS) project (FP7-603946).

In silico models in drug development: where we are

The use and utility of computational models in drug development has significantly grown in the last decades, fostered by the availability of high throughput datasets and new data analysis strategies. These in silico approaches are demonstrating their ability to generate reliable predictions as well as new knowledge on the mode of action of drugs and the mechanisms underlying their side effects, altogether helping to reduce the costs of drug development. The aim of this review is to provide a panorama of developments in the field in the last two years.

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.