Pharmacokinetics of oseltamivir phosphate and oseltamivir carboxylate in non-pregnant and pregnant rhesus monkeys.

Oseltamivir is an antiviral drug approved to treat influenza in humans. Although the dosing regimen of this drug is well established for non-pregnant patients, it is not clear if the significant physiological alterations associated with pregnancy affect the pharmacokinetics of oseltamivir and, thus, warrant different dosing regimens to assure efficacy. In this study, we investigated the suitability of rhesus macaques as an animal model for studying oseltamivir pharmacokinetics during all trimesters of pregnancy in comparison to pre-pregnant conditions. Specifically, we compared the pharmacokinetics of oseltamivir and its pharmacologically active metabolite oseltamivir carboxylate in rhesus monkeys after intravenous and nasogastric administration of 2.5 mg oseltamivir phosphate/kg body weight given prior to and during the first, second, and third trimesters of pregnancy. Pregnancy had only a modest effect upon the pharmacokinetic parameters of oseltamivir and oseltamivir carboxylate. Monkeys treated intravenously in the third trimester had a reduction in Vd and CL, compared to non-pregnant monkeys. These changes did not occur in the other two trimesters. Pregnant monkeys treated intravenously had 20-25% decrease in AUC0-∞ of oseltamivir carboxylate and a corresponding increase in Vd and CL. Pregnant monkeys treated nasogastrically with oseltamivir phosphate demonstrated a pattern that recapitulated intravenous dosing. Taken together these data indicate that rhesus monkeys are an acceptable model for studying drug-pregnancy interactions.

PBPK model reporting template for chemical risk assessment applications.

Physiologically-based pharmacokinetic (PBPK) modeling analysis does not stand on its own for regulatory purposes but is a robust tool to support drug/chemical safety assessment. While the development of PBPK models have grown steadily since their emergence, only a handful of models have been accepted to support regulatory purposes due to obstacles such as the lack of a standardized template for reporting PBPK analysis. Here, we expand the existing guidances designed for pharmaceutical applications by recommending additional elements that are relevant to environmental chemicals. This harmonized reporting template can be adopted and customized by public health agencies receiving PBPK model submission, and it can also serve as general guidance for submitting PBPK-related studies for publication in journals or other modeling sharing purposes. The current effort represents one of several ongoing collaborations among the PBPK modeling and risk assessment communities to promote, when appropriate, incorporating PBPK modeling to characterize the influence of pharmacokinetics on safety decisions made by regulatory agencies.

Characterization of the modes of action and dose-response relationship for thiocyanate on the thyroid hormone levels in rats using a computational approach.

Current practices for evaluating the cumulative risk of thyroid-active chemical mixtures (perchlorate, thiocyanate, nitrate) focus on the inhibition of thyroidal iodide uptake via the sodium iodide symporter (NIS) as the mode of action for potency equivalence calculations. However, unlike perchlorate, thiocyanate presents additional modes of action within the thyroid that could contribute to the overall thyroid perturbation. We tested the hypothesis of whether assuming a single mode of action of thyroidal iodide uptake inhibition is sufficient for describing the observed dose-response relationship for thiocyanate and its effects on serum thyroxine levels. An interaction model was developed by linking a biologically based dose-response model for iodide and thyroid hormones to a thiocyanate physiologically based pharmacokinetic model. Each model, adapted from the literature, was restructured and recalibrated in a Bayesian framework for the current mode of actions study. For a chronic exposure scenario, NIS inhibition alone was found not to be sufficient to describe the dose-response relationship for thiocyanate. Inclusion of additional modes of action involving iodide flux across the thyroid membrane and inhibition of iodide organification via thyroid peroxidase showed only moderate improvements in capturing the dose-response at environmental thiocyanate doses of exposure and failed to capture trends at very high doses. Our findings emphasize the need for more mechanistic data for chronic exposure scenarios to characterize better the overall dose-response relationship for thiocyanate. Risk assessment approaches for thyroid-active chemical mixtures that rely on NIS inhibition as the single mode of action may over-predict the contribution of thiocyanate to thyroid disruption.

Thiocyanate: a review and evaluation of the kinetics and the modes of action for thyroid hormone perturbations.

Exposure of the population to thiocyanate is predominantly through the diet and cigarette smoke. Thiocyanate is a potential thyroid disruptor due to its capacity to inhibit the uptake of iodide by the thyroid. Thiocyanate also interacts with the enzymatic reactions associated with iodide organification and thyroid hormone synthesis. Quantification of the dose-response relationships of thiocyanate and alteration in thyroid hormone levels is important for evaluating the risk of exposure to thiocyanate in humans. In this review, we highlight the key whole-body and intra-thyroidal aspects of thiocyanate kinetics in rats and its various modes of action for perturbing thyroid function. The inter-play between the various transporter- and enzyme-mediated modes of action contributes to the complexity in the dose-response relationship determinations for thiocyanate. We map the available modes of action in a mechanistic and quantitative manner. Findings summarized in this study can help support the development of a quantitative model to study the interaction effects of thiocyanate on the thyroid function. Additionally, the data gaps identified can help guide future experimental designs to characterize further thiocyanate dose-response. Finally, the strengths and weaknesses in current risk assessment considerations used for thiocyanate as a component of thyroid-active chemical mixtures are discussed.

Development of a PBPK model of thiocyanate in rats with an extrapolation to humans: A computational study to quantify the mechanism of action of thiocyanate kinetics in thyroid.

Thyroid homeostasis can be disturbed due to thiocyanate exposure from the diet or tobacco smoke. Thiocyanate inhibits both thyroidal uptake of iodide, via the sodium-iodide symporter (NIS), and thyroid hormone (TH) synthesis in the thyroid, via thyroid peroxidase (TPO), but the mode of action of thiocyanate is poorly quantified in the literature. The characterization of the link between intra-thyroidal thiocyanate concentrations and dose of exposure is crucial for assessing the risk of thyroid perturbations due to thiocyanate exposure. We developed a PBPK model for thiocyanate that describes its kinetics in the whole-body up to daily doses of 0.15mmol/kg, with a mechanistic description of the thyroidal kinetics including NIS, passive diffusion, and TPO. The model was calibrated in a Bayesian framework using published studies in rats. Goodness-of-fit was satisfactory, especially for intra-thyroidal thiocyanate concentrations. Thiocyanate kinetic processes were quantified in vivo, including the metabolic clearance by TPO. The passive diffusion rate was found to be greater than NIS-mediated uptake rate. The model captured the dose-dependent kinetics of thiocyanate after acute and chronic exposures. Model behavior was evaluated using a Morris screening test. The distribution of thiocyanate into the thyroid was found to be determined primarily by the partition coefficient, followed by NIS and passive diffusion; the impact of the latter two mechanisms appears to increase at very low doses. Extrapolation to humans resulted in good predictions of thiocyanate kinetics during chronic exposure. The developed PBPK model can be used in risk assessment to quantify dose-response effects of thiocyanate on TH.

Predicting Clinical Pharmacokinetics/Pharmacodynamics and Impact of Organ Impairment on siRNA-Based Therapeutics Using a Mechanistic Physiologically-Based Pharmacokinetic-Pharmacodynamic Model.

Approved and emerging siRNA therapeutics are primarily designed for targeted delivery to liver where the therapeutic gene silencing effects occurs. Impairment of hepatic/renal function and its impact on siRNA pharmacokinetics/pharmacodynamics (PKs/PDs) are yet to be mechanistically evaluated to describe the unanticipated clinical observations for this novel modality. We developed pathophysiologically relevant models for organ impairment within a physiologically-based PK-PD (PBPK-PD) modeling framework focusing on modality-specific mechanistic factors to evaluate impact on siRNA PKs and PDs. PBPK-PD models for two US Food and Drug Administration (FDA) approved siRNAs inclisiran and vutrisiran were developed as case studies leveraging available tissue-specific data and translated to humans. Key determinants of the clinical PK and PD of N-acetylgalactosamine conjugated siRNAs (GalNAc-siRNAs) with varying sequences were also identified to inform effective clinical translation strategies for emerging GalNAc-siRNA candidates. A 30-70% reduction in hepatic asialoglycoprotein receptors concentrations still allowed for sufficient amount of free cytoplasmic siRNA for RISC-loading to produce PD effects comparable in extent and duration to normal liver function. This included severe hepatic impairment for which no clinical data are available. Inclusion of other modality agnostic physiological changes relevant to organ impairment did not alter the findings. Changes in renal physiologies, including changes in GFR across various degrees of impairment, well predicted minimal changes in PD for inclisiran and vutrisiran. This work provides a quantitative mechanistic framework and insights on modality-specific factors that drive clinical translation and patient/disease-related factors that impact specific dosing considerations and clinical outcomes to help accelerate the optimal development of siRNA therapeutics.

A Mechanistic Physiologically-Based Pharmacokinetic Platform Model to Guide Adult and Pediatric Intravenous and Subcutaneous Dosing for Bispecific T Cell Engagers.

Bispecific T cell engagers (Bi-TCEs) have revolutionized the treatment of oncology indications across both liquid and solid tumors. Bi-TCEs are rapidly evolving from conventional intravenous (i.v.) to more convenient subcutaneous (s.c.) administrations and extending beyond adults to also benefit pediatric patients. Leveraging clinical development experience across three generations of Bi-TCE molecules across both liquid and solid tumor indications from i.v./s.c. dosing in adults and pediatric subjects, we developed a mechanistic-physiologically-based pharmacokinetic (PBPK) platform model for Bi-TCEs. The model utilizes a full PBPK model framework and was successfully validated for PK predictions following i.v. and s.c. dosing across both liquid and solid tumor space in adults for eight Bi-TCEs. After refinement to incorporate physiological ontogeny, the model was successfully validated to predict pediatric PKs in 1 month - < 2 years, 2-11 years, and 12-17 years old subjects following i.v. dosing. Following s.c. dosing in pediatric subjects, the model predicted similar bioavailability, however, a shorter time to maximum concentration (Tmax ) for the three age groups compared with adults. The model was also applied to guide the dosing strategy for first generation of Bi-TCEs for organ impairment, specifically renal impairment, and was able to accurately predict the impact of renal impairment on PK for these relatively small-size Bi-TCEs. This work highlights a novel mechanistic platform model for accurately predicting the PK in adult and pediatric patients across liquid and solid tumor indications from i.v./s.c. dosing and can be used to guide optimal dose and dosing regimen selection and accelerating the clinical development for Bi-TCEs.

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science.

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

Extrapolation of hypothalamic-pituitary-thyroid axis perturbations and associated toxicity in rodents to humans: case study with perchlorate.

Functional aspects of the Hypothalamic-Pituitary-Thyroid (HPT) axis in rats and humans are compared, exposing why extrapolation of toxicant-induced perturbations in the rat HPT axis to the human HPT axis cannot be accomplished using default risk assessment methodology. Computational tools, such as biologically based dose response models for the HPT axis, are recommended to perform complex animal to human extrapolations involving the HPT axis. Experimental and computational evidence are presented that suggest perchlorate acts directly on the thyroid gland in rats. The apparent escape from perchlorate-induced inhibition of thyroidal uptake of radioactive iodide in humans is discussed along with "rebound" or increased thyroidal uptake of radioactive iodide observed after discontinued clinical treatment with perchlorate.

Evaluation of a rapid, generic human gestational dose model.

Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.

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 (devTOXqP ) 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 devTOXqP 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 devTOXqP 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 devTOXqP human stem cell-based platform to quantitatively assess a chemical's developmental toxicity potency.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

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.

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.

If the KI is defined by the free energy of binding to P-glycoprotein, which kinetic parameters define the IC50 for the Madin-Darby canine kidney II cell line overexpressing human multidrug resistance 1 confluent cell monolayer?

From previous fits of drug transport kinetics across confluent Madin-Darby canine kidney II cell line overexpressing human multidrug resistance 1 cell monolayers, we found that a drug's binding constant to P-glycoprotein (P-gp) was significantly smaller than its IC(50) when that drug was used as an inhibitor against another P-gp substrate. We tested several IC(50) candidate functions, including the standard function, the Kalvass-Pollack function, and the efflux ratio, to determine whether any of them yielded an IC(50) = K(I), as would be expected for water-soluble enzymes. For the confluent cell monolayer, the IC(50)/K(I) ratio is greater than 1 for all candidate functions tested. From the mass action kinetic model, we have derived a simple approximate equation that shows how the IC(50)/K(I) ratio depends on the elementary rate constants from our mass action model. Thus, the IC(50) will differ between cell lines and tissues, for the same probe substrate and inhibitor, if there are different membrane concentrations of P-gp, or the probe substrate's elementary rate constants, partition coefficient, binding constant to P-gp, passive permeability, and ability to access the other transporters (if any) in the two cell lines. The mass action model and the approximate equation for the IC(50)/K(I) ratio derived here can be used to estimate the elementary rate constants needed to extrapolate in vitro drug-drug interactions for compounds to the in vivo environment.

Application of physiologically based pharmacokinetic modeling for sertraline dosing recommendations in pregnancy.

Pregnancy is a period of significant change that impacts physiological and metabolic status leading to alterations in the disposition of drugs. Uncertainty in drug dosing in pregnancy can lead to suboptimal therapy, which can contribute to disease exacerbation. A few studies show there are increased dosing requirements for antidepressants in late pregnancy; however, the quantitative data to guide dose adjustments are sparse. We aimed to develop a physiologically based pharmacokinetic (PBPK) model that allows gestational-age dependent prediction of sertraline dosing in pregnancy. A minimal physiological model with defined gut, liver, plasma, and lumped placental-fetal compartments was constructed using the ordinary differential equation solver package, 'mrgsolve', in R. We extracted data from the literature to parameterize the model, including sertraline physicochemical properties, in vitro metabolism studies, disposition in nonpregnant women, and physiological changes during pregnancy. The model predicted the pharmacokinetic parameters from a clinical study with eight subjects for the second trimester and six subjects for the third trimester. Based on the model, gestational-dependent changes in physiology and metabolism account for increased clearance of sertraline (up to 143% at 40 weeks gestational age), potentially leading to under-dosing of pregnant women when nonpregnancy doses are used. The PBPK model was converted to a prototype web-based interactive dosing tool to demonstrate how the output of a PBPK model may translate into optimal sertraline dosing in pregnancy. Quantitative prediction of drug exposure using PBPK modeling in pregnancy will support clinically appropriate dosing and increase the therapeutic benefit for pregnant women.

Membrane transporter data to support kinetically-informed chemical risk assessment using non-animal methods: Scientific and regulatory perspectives.

Humans are continuously exposed to low levels of thousands of industrial chemicals, most of which are poorly characterised in terms of their potential toxicity. The new paradigm in chemical risk assessment (CRA) aims to rely on animal-free testing, with kinetics being a key determinant of toxicity when moving from traditional animal studies to integrated in vitro-in silico approaches. In a kinetically informed CRA, membrane transporters, which have been intensively studied during drug development, are an essential piece of information. However, how existing knowledge on transporters gained in the drug field can be applied to CRA is not yet fully understood. This review outlines the opportunities, challenges and existing tools for investigating chemical-transporter interactions in kinetically informed CRA without animal studies. Various environmental chemicals acting as substrates, inhibitors or modulators of transporter activity or expression have been shown to impact TK, just as drugs do. However, because pollutant concentrations are often lower in humans than drugs and because exposure levels and internal chemical doses are not usually known in contrast to drugs, new approaches are required to translate transporter data and reasoning from the drug sector to CRA. Here, the generation of in vitro chemical-transporter interaction data and the development of transporter databases and classification systems trained on chemical datasets (and not only drugs) are proposed. Furtheremore, improving the use of human biomonitoring data to evaluate the in vitro-in silico transporter-related predicted values and developing means to assess uncertainties could also lead to increase confidence of scientists and regulators in animal-free CRA. Finally, a systematic characterisation of the transportome (quantitative monitoring of transporter abundance, activity and maintenance over time) would reinforce confidence in the use of experimental transporter/barrier systems as well as in established cell-based toxicological assays currently used for CRA.

Capturing the applicability of in vitro-in silico membrane transporter data in chemical risk assessment and biomedical research.

Costs, scientific and ethical concerns related to animal tests for regulatory decision-making have stimulated the development of alternative methods. When applying alternative approaches, kinetics have been identified as a key element to consider. Membrane transporters affect the kinetic processes of absorption, distribution, metabolism and excretion (ADME) of various compounds, such as drugs or environmental chemicals. Therefore, pharmaceutical scientists have intensively studied transporters impacting drug efficacy and safety. Besides pharmacokinetics, transporters are considered as major determinant of toxicokinetics, potentially representing an essential piece of information in chemical risk assessment. To capture the applicability of transporter data for kinetic-based risk assessment in non-pharmaceutical sectors, the EU Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) created a survey with a view of identifying the improvements needed when using in vitro and in silico methods. Seventy-three participants, from different sectors and with various kinds of expertise, completed the survey. The results revealed that transporters are investigated mainly during drug development, but also for risk assessment purposes of food and feed contaminants, industrial chemicals, cosmetics, nanomaterials and in the context of environmental toxicology, by applying both in vitro and in silico tools. However, to rely only on alternative methods for chemical risk assessment, it is critical that the data generated by in vitro and in silico methods are scientific integer, reproducible and of high quality so that they are trusted by decision makers and used by industry. In line, the respondents identified various challenges related to the interpretation and use of transporter data from non-animal methods. Overall, it was determined that a combined mechanistically-anchored in vitro-in silico approach, validated against available human data, would gain confidence in using transporter data within an animal-free risk assessment paradigm. Finally, respondents involved primarily in fundamental research expressed lower confidence in non-animal studies to unravel complex transporter mechanisms.

In vitro to in vivo extrapolation for high throughput prioritization and decision making.

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

Short-term dietary methionine supplementation affects one-carbon metabolism and DNA methylation in the mouse gut and leads to altered microbiome profiles, barrier function, gene expression and histomorphology.

BACKGROUND: Methionine, a central molecule in one-carbon metabolism, is an essential amino acid required for normal growth and development. Despite its importance to biological systems, methionine is toxic when administered at supra-physiological levels. The aim of this study was to investigate the effects of short-term methionine dietary modulation on the proximal jejunum, the section of the gut specifically responsible for amino acid absorption, in a mouse model. Eight-week-old CBA/J male mice were fed methionine-adequate (MAD; 6.5 g/kg) or methionine-supplemented (MSD; 19.5 g/kg) diets for 3.5 or 6 days (average food intake 100 g/kg body weight). The study design was developed in order to address the short-term effects of the methionine supplementation that corresponds to methionine dietary intake in Western populations. Biochemical indices in the blood as well as metabolic, epigenetic, transcriptomic, metagenomic, and histomorphological parameters in the gut were evaluated. RESULTS: By day 6, feeding mice with MSD (protein intake <10% different from MAD) resulted in increased plasma (2.3-fold; p < 0.054), but decreased proximal jejunum methionine concentrations (2.2-fold; p < 0.05) independently of the expression of neutral amino acid transporters. MSD has also caused small bowel bacteria colonization, increased the abundance of pathogenic bacterial species Burkholderiales and decreased the gene expression of the intestinal transmembrane proteins-Cldn8 (0.18-fold, p < 0.05), Cldn9 (0.24-fold, p < 0.01) and Cldn10 (0.05-fold, p < 0.05). Feeding MSD led to substantial histomorphological alterations in the proximal jejunum exhibited as a trend towards decreased plasma citrulline concentrations (1.8-fold, p < 0.07), as well as loss of crypt depth (by 28%, p < 0.05) and mucosal surface (by 20%, p < 0.001). CONCLUSIONS: Together, these changes indicate that short-term feeding of MSD substantially alters the normal gut physiology. These effects may contribute to the pathogenesis of intestinal inflammatory diseases and/or sensitize the gut to exposure to other stressors.