Predictive Performance of Next Generation Physiologically Based Kinetic (PBK) Model Predictions in Rats Based on In Vitro and In Silico Input Data

High-throughput and sustainable B vitamins analysis in nutritional supplements, vegetables, and fruits via 2D carbon microfiber fractionation system coupled with mass spectrometry

B vitamins are essential for energy metabolism, nervous health, blood production, and the immune system. Their quantification in nutritional supplements and food is mandatory to manage a correct daily intake and dosage. In this study, a fast and sustainable method for the analysis of 8 B vitamins (VB1, VB2, VB3, nicotinamide, VB5, VB6, VB9, VB12) in real samples using a 2D-carbon microfiber fractionation system combined with a triple quadrupole mass spectrometer (2DμCFs-QqQ-MS/MS) is presented. The method shortens the analysis time to 5 min, showing high sensitivities (LODs: 1.7-13.7 ng mL-1, LOQs: 5.5-45.7 ng mL-1, obtained with standard solutions), good reproducibility (RSDs <15 %), and strong linear correlations (R2 > 0.997). When applied for B vitamin determination in nutritional supplements, results matched product label values at a 95 % confidence level, with batch reproducibility never exceeding 5 %. Furthermore, coupling a 2D-carbon microfiber fraction system with a quadrupole time-of-flight high-resolution mass spectrometry (2DμCFs-QTOF-HRMS) it is possible to carry out quick monitoring of B vitamin contents together with impurity evaluation in real samples.

Quantitative in vitro-to-in vivo extrapolation of human adrenergic and trace amine-associated receptor 1 potencies of pre-workout supplement ingredients using physiologically based kinetic modelling-based reverse dosimetry

The present study predicts effective doses of a set of phenethylamine (PEA) analogues that are frequently present in pre-workout and weight-loss food supplements, to prioritize these compounds for further risk assessment. In vitro determined EC50 values of PEA analogues for multiple human adrenergic receptor (ADR) subtypes (ADRα1A, α1B, α1D, α2A, β1, β2) and trace-amine associated receptor 1 (TAAR1) were extrapolated to human ED50 values by using physiologically based kinetic (PBK) modelling-based reverse dosimetry combined with in silico and in vitro determined PBK model input parameters. The predicted ED50 values of the studied PEAs for activation of ADRα1A/B/D, ADRα2A, ADRβ1 and TAAR1 were within a range of 0.914-29.7 mg/kg body weight (bw), 139-234 mg/kg bw, 0.0839-38.8 mg/kg bw and 0.995-264 mg/kg bw, respectively. Comparison of the predicted ED50 values with reported intake values revealed that particularly the exposure of the PEA analogues higenamine, isopropyloctopamine, β-methylphenethylamine and p-synephrine is in the same range or exceeds the predicted ED50 values. This suggests that these PEAs can (in)directly affect the cardiovascular system after the intake of food supplements. These PEA analogues should therefore be considered as high priority compounds for further risk assessment. In conclusion, our study shows that the use of quantitative in vitro-to-in vivo extrapolation (QIVIVE) of adrenergic and TAAR1 potencies using a generic PBK model can serve as an efficient prioritization method for a whole set of chemical analogues.

Next Generation Risk Assessment of Acute Neurotoxicity from Organophosphate Exposures Using the In Vitro-In Silico Derived Dietary Comparator Ratio

Organophosphate (OP) pesticides are common environmental contaminants, of which the resulting acetylcholinesterase (AChE) inhibition and concomitant neurotoxic effects following exposure remain a global concern. To evaluate the safety upon acute exposure to OP pesticides, the Dietary Comparator Ratio (DCR) approach was used for the first time for this class of chemicals. Six OPs including chlorpyrifos, diazinon, fenitrothion, methyl parathion, profenofos, and chlorfenvinphos were selected as model compounds. Seventy-four reports of human exposures were collected, and a DCR value at each defined exposure level was calculated with in vitro determined AChE inhibition potency and in silico simulated internal exposures. Results indicate that the DCR outcomes are comparable to the actual knowledge on the presence or absence of in vivo AChE inhibition and adverse effects for the respective exposure scenarios. Of all collected scenarios, only four false positives but no false negatives were obtained. No safety concern on acute neurotoxicity appears to be raised for the evaluated environmental exposure scenarios to OPs. To conclude, the described DCR approach provides an adequate evaluation of the OP-induced adverse outcomes for humans, shedding light on its utility for 3Rs-compliant safety assessment of chemicals with different toxicity mechanisms especially for which in vitro bioassays are available.

Chemical risk assessment in food animals via physiologically based pharmacokinetic modeling - Part I: Veterinary drugs on human food safety assessment

Veterinary drugs and environmental pollutants can enter food animals and remain as residues in food chains threatening human food safety and health. Performing health risk and food safety assessments to derive safety levels of these xenobiotics can protect human health. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical tool to quantitatively describe chemical disposition in humans and animals informing human food safety and health risk assessments. However, few reviews focus on the application of PBPK models in food animals and discuss their relationship to human food safety and health risk assessments in the last five years (2020-2024). In this series of reviews, we introduce the methodology, recent progress and challenges of PBPK modeling in food animals. The present review is Part I of this series of reviews and it focuses on applications of PBPK models of veterinary drugs in food animals, whereas Part II is a companion review focusing on environmental chemicals. Advanced strategies of PBPK modeling in risk and food safety assessment, including population PBPK, interactive PBPK web dashboard, and generic PBPK are also summarized in Part I. Additionally, we share our perspective on the existing challenges and future direction for PBPK modeling of veterinary medicines in food animals.

Development of a Generic Physiologically Based Kinetic Model for the Prediction of Internal Exposure to Organophosphate Pesticides

Since their introduction into agriculture, the toxicity of organophosphate (OP) pesticides has been widely studied in animal models. However, next generation risk assessment (NGRA) intends to maximize the use of novel approach methodologies based on in vitro and in silico methods. Therefore, this study describes the development and evaluation of a generic physiologically based kinetic (PBK) model for acute exposure to OP pesticides in rats and humans using quantitative structure property relationships and data from published in vitro studies. The models were evaluated using in vivo studies from the literature for chlorpyrifos, diazinon, fenitrothion, methyl-parathion, ethyl-parathion, dimethoate, chlorfenvinphos, and profenofos. Evaluation was performed by comparing simulated and in vivo observed time profiles for blood, plasma, or urinary concentrations and other toxicokinetic parameters. Of simulated concentration-time profiles, 87 and 91% were within a 5-fold difference from observed toxicokinetic data from rat and human studies, respectively. Only for dimethyl-organophosphates further refinement of the model is required. It is concluded that the developed generic PBK model provides a new tool to assess species differences in rat and human kinetics of OP pesticides. This approach provides a means to perform NGRA for these compounds and could also be adopted for other classes of compounds.

From hazard to risk prioritization: a case study to predict drug-induced cholestasis using physiologically based kinetic modeling

Cholestasis is characterized by hepatic accumulation of bile acids. Clinical manifestation of cholestasis only occurs in a small proportion of exposed individuals. The present study aims to develop a new approach methodology (NAM) to predict drug-induced cholestasis as a result of drug-induced hepatic bile acid efflux inhibition and the resulting bile acid accumulation. To this end, hepatic concentrations of a panel of drugs were predicted by a generic physiologically based kinetic (PBK) drug model. Their effects on hepatic bile acid efflux were incorporated in a PBK model for bile acids. The predicted bile acid accumulation was used as a measure for a drug's cholestatic potency. The selected drugs were known to inhibit hepatic bile acid efflux in an assay with primary suspension-cultured hepatocytes and classified as common, rare, or no for cholestasis incidence. Common cholestasis drugs included were atorvastatin, chlorpromazine, cyclosporine, glimepiride, ketoconazole, and ritonavir. The cholestasis incidence of the drugs appeared not to be adequately predicted by their Ki for inhibition of hepatic bile acid efflux, but rather by the AUC of the PBK model predicted internal hepatic drug concentration at therapeutic dose level above this Ki. People with slower drug clearance, a larger bile acid pool, reduced bile salt export pump (BSEP) abundance, or given higher than therapeutic dose levels were predicted to be at higher risk to develop drug-induced cholestasis. The results provide a proof-of-principle of using a PBK-based NAM for cholestasis risk prioritization as a result of transporter inhibition and identification of individual risk factors.

Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans

Physiologically based kinetic (PBK) modelling offers a mechanistic basis for predicting the pharmaco-/toxicokinetics of compounds and thereby provides critical information for integrating toxicity and exposure data to replace animal testing with in vitro or in silico methods. However, traditional PBK modelling depends on animal and human data, which limits its usefulness for non-animal methods. To address this limitation, high-throughput PBK modelling aims to rely exclusively on in vitro and in silico data for model generation. Here, we evaluate a variety of in silico tools and different strategies to parameterise PBK models with input values from various sources in a high-throughput manner. We gather 2000 + publicly available human in vivo concentration-time profiles of 200 + compounds (IV and oral administration), as well as in silico, in vitro and in vivo determined compound-specific parameters required for the PBK modelling of these compounds. Then, we systematically evaluate all possible PBK model parametrisation strategies in PK-Sim and quantify their prediction accuracy against the collected in vivo concentration-time profiles. Our results show that even simple, generic high-throughput PBK modelling can provide accurate predictions of the pharmacokinetics of most compounds (87% of Cmax and 84% of AUC within tenfold). Nevertheless, we also observe major differences in prediction accuracies between the different parameterisation strategies, as well as between different compounds. Finally, we outline a strategy for high-throughput PBK modelling that relies exclusively on freely available tools. Our findings contribute to a more robust understanding of the reliability of high-throughput PBK modelling, which is essential to establish the confidence necessary for its utilisation in Next-Generation Risk Assessment.

Physiologically based Kinetic Modeling-Facilitated Quantitative In Vitro to In Vivo Extrapolation to Predict the Effects of Aloe-Emodin in Rats and Humans

Aloe-emodin, a natural hydroxyanthraquinone, exerts both adverse and protective effects. This study aimed at investigating these potential effects of aloe-emodin in humans upon the use of food supplements and herbal medicines using a physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach. For this, PBK models in rats and humans were established for aloe-emodin including its active metabolite rhein and used to convert in vitro data on hepatotoxicity, nephrotoxicity, reactive oxidative species (ROS) generation, and Nrf2 induction to corresponding in vivo dose-response curves, from which points of departure (PODs) were derived by BMD analysis. The derived PODs were subsequently compared to the estimated daily intakes (EDIs) resulting from the use of food supplements or herbal medicines. It is concluded that the dose levels of aloe-emodin from food supplements or herbal medicines are unlikely to induce toxicity, ROS generation, or Nrf2 activation in liver and kidney.

Trust your gut: Establishing confidence in gastrointestinal models - An overview of the state of the science and contexts of use

The webinar series and workshop titled “Trust Your Gut: Establishing Confidence in Gastrointestinal Models – An Overview of the State of the Science and Contexts of Use” was co-organized by NICEATM, NIEHS, FDA, EPA, CPSC, DoD, and the Johns Hopkins Center for Alternatives to Animal Testing (CAAT) and hosted at the National Institutes of Health in Bethesda, MD, USA on October 11-12, 2023. New approach methods (NAMs) for assessing issues of gastrointestinal tract (GIT)- related toxicity offer promise in addressing some of the limitations associated with animal-based assessments. GIT NAMs vary in complexity, from two-dimensional monolayer cell line-based systems to sophisticated 3-dimensional organoid systems derived from human primary cells. Despite advances in GIT NAMs, challenges remain in fully replicating the complex interactions and pro­cesses occurring within the human GIT. Presentations and discussions addressed regulatory needs, challenges, and innovations in incorporating NAMs into risk assessment frameworks; explored the state of the science in using NAMs for evaluating systemic toxicity, understanding absorption and pharmacokinetics, evaluating GIT toxicity, and assessing potential allergenicity; and discussed strengths, limitations, and data gaps of GIT NAMs as well as steps needed to establish confidence in these models for use in the regulatory setting.

Integrating In Vitro Data and Physiologically Based Kinetic Modeling to Predict and Compare Acute Neurotoxic Doses of Saxitoxin in Rats, Mice, and Humans

Current climate trends are likely to expand the geographic distribution of the toxigenic microalgae and concomitant phycotoxins, making intoxications by such toxins a global phenomenon. Among various phycotoxins, saxitoxin (STX) acts as a neurotoxin that might cause severe neurological symptoms in mammals following consumptions of contaminated seafood. To derive a point of departure (POD) for human health risk assessment upon acute neurotoxicity induced by oral STX exposure, a physiologically based kinetic (PBK) modeling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE) approach was employed. The PBK models for rats, mice, and humans were built using parameters from the literature, in vitro experiments, and in silico predictions. Available in vitro toxicity data for STX were converted to in vivo dose-response curves via the PBK models established for these three species, and POD values were derived from the predicted curves and compared to reported in vivo toxicity data. Interspecies differences in acute STX toxicity between rodents and humans were found, and they appeared to be mainly due to differences in toxicokinetics. The described approach resulted in adequate predictions for acute oral STX exposure, indicating that new approach methodologies, when appropriately integrated, can be used in a 3R-based chemical risk assessment paradigm.

Development of physiologically-based gut absorption model for probabilistic prediction of environmental chemical bioavailability

Absorption in the gastrointestinal tract is a key factor determining the bioavailability of chemicals after oral exposure but is frequently assumed to have a conservative value of 100% for environmental chemicals, particularly in the context of high-throughput toxicokinetics for in vitro-to-in vivo extrapolation (IVIVE). For pharmaceutical compounds, the physiologically based advanced compartmental absorption and transit (ACAT) model has been used extensively to predict gut absorption but has not generally been applied to environmental chemicals. Here we develop a probabilistic environmental compart­mental absorption and transit (PECAT) model, adapting the ACAT model to environmental chemicals. We calibrated the model parameters to human in vivo, ex vivo, and in vitro datasets of drug permeability and fractional absorption by con­sidering two key factors: (1) differences between permeability in Caco-2 cells and in vivo permeability in the jejunum, and (2) differences in in vivo permeability across different gut segments. Incorporating these factors probabilistically, we found that given Caco-2 permeability measurements, predictions of the PECAT model are consistent with the (limited) available gut absorption data for environmental chemicals. However, the substantial chemical-to-chemical variability observed in the cal­ibration data often led to wide probabilistic confidence bounds in the predicted fraction absorbed and resulting steady state blood concentration. Thus, while the PECAT model provides a statistically rigorous, physiologically based approach for incor­porating in vitro data on gut absorption into toxicokinetic modeling and IVIVE, it also highlights the need for more accurate in vitro models and data for measuring gut segment-specific in vivo permeability of environmental chemicals.

Establishing allometric relationships between microsomal protein and cytochrome P450 content with body weight in vertebrate species

Data from in vitro studies are routinely used to estimate in vivo hepatic clearance of chemicals and this information is needed to parameterise physiologically based kinetic models. Such clearance data can be obtained from laboratory experiments using liver microsomes, hepatocytes, precision-cut liver slices or recombinant enzymes. Irrespective of the selected test system, scaling factors are required to convert the in vitro measured intrinsic clearance to a whole liver intrinsic clearance. Scaling factors such as the hepatic microsomal protein per gram of liver and/or the amount of cytochrome P450 per hepatocyte provide a means to calculate the whole liver intrinsic clearance. Here, a database from the peer-reviewed literature has been developed and provides quantitative metrics on microsomal protein (MP) and cytochrome P450 contents in vertebrate orders namely amphibians, mammals, birds, fish and reptiles. This database allows to address allometric relationships between body weight and MP content, and body weight and cytochrome P450 content. A total of 85 and 74 vertebrate species were included to assess the relationships between log10 body weight versus log10 MP, and between log10 body weight and log10 cytochrome P450 content, respectively. The resulting slopes range from 0.76 to 1.45 in a range of vertebrate species. Such data-driven allometric relationships can be used to estimate the MP content necessary for in vitro to in vivo extrapolation of in vitro clearance data. Future work includes applications of these relationships for different vertebrate taxa using quantitative in vitro to in vivo extrapolation models coupled to physiologically based kinetic models using chemicals of relevance as case studies including pesticides, contaminants and feed additives.

Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment

With an increasing need to incorporate new approach methodologies (NAMs) in chemical risk assessment and the concomitant need to phase out animal testing, the interpretation of in vitro assay readouts for quantitative hazard characterisation becomes more important. Physiologically based kinetic (PBK) models, which simulate the fate of chemicals in tissues of the body, play an essential role in extrapolating in vitro effect concentrations to in vivo bioequivalent exposures. As PBK-based testing approaches evolve, it will become essential to standardise PBK modelling approaches towards a consensus approach that can be used in quantitative in vitro-to-in vivo extrapolation (QIVIVE) studies for regulatory chemical risk assessment based on in vitro assays. Based on results of an ECETOC expert workshop, steps are recommended that can improve regulatory adoption: (1) define context and implementation, taking into consideration model complexity for building fit-for-purpose PBK models, (2) harmonise physiological input parameters and their distribution and define criteria for quality chemical-specific parameters, especially in the absence of in vivo data, (3) apply Good Modelling Practices (GMP) to achieve transparency and design a stepwise approach for PBK model development for risk assessors, (4) evaluate model predictions using alternatives to in vivo PK data including read-across approaches, (5) use case studies to facilitate discussions between modellers and regulators of chemical risk assessment. Proof-of-concepts of generic PBK modelling approaches are published in the scientific literature at an increasing rate. Working on the previously proposed steps is, therefore, needed to gain confidence in PBK modelling approaches for regulatory use.

Effects of Drugs Formerly Proposed for COVID-19 Treatment on Connexin43 Hemichannels

Connexin43 (Cx43) hemichannels form a pathway for cellular communication between the cell and its extracellular environment. Under pathological conditions, Cx43 hemichannels release adenosine triphosphate (ATP), which triggers inflammation. Over the past two years, azithromycin, chloroquine, dexamethasone, favipiravir, hydroxychloroquine, lopinavir, remdesivir, ribavirin, and ritonavir have been proposed as drugs for the treatment of the coronavirus disease 2019 (COVID-19), which is associated with prominent systemic inflammation. The current study aimed to investigate if Cx43 hemichannels, being key players in inflammation, could be affected by these drugs which were formerly designated as COVID-19 drugs. For this purpose, Cx43-transduced cells were exposed to these drugs. The effects on Cx43 hemichannel activity were assessed by measuring extracellular ATP release, while the effects at the transcriptional and translational levels were monitored by means of real-time quantitative reverse transcriptase polymerase chain reaction analysis and immunoblot analysis, respectively. Exposure to lopinavir and ritonavir combined (4:1 ratio), as well as to remdesivir, reduced Cx43 mRNA levels. None of the tested drugs affected Cx43 protein expression.

PBK modelling of topical application and characterisation of the uncertainty of Cmax estimate: A case study approach

Combined with in vitro bioactivity data, physiologically based kinetic (PBK) models has increasing applications in next generation risk assessment for animal-free safety decision making. A tiered framework of building PBK models for such application has been developed with increasing complexity and refinements, as model parameters determined in silico, in vitro, and with human pharmacokinetic data become progressively available. PBK modelling has been widely applied for oral/intravenous administration, but less so on topically applied chemicals. Therefore, building PBK models for topical applications and characterizing their uncertainties in the tiered approach is critical to safety decision making. The purpose of this study was to assess the confidence of PBK modelling of topically applied chemicals following the tiered framework, using non-animal methods derived parameters. Prediction of maximum plasma concentration (C_max) and area under the curve were compared to observed kinetics from published dermal clinical studies for five chemicals (diclofenac, salicylic acid, coumarin, nicotine, caffeine). A bespoke Bayesian statistical model was developed to describe the distributions of C_max errors between the predicted and observed data. We showed a general trend that confidence in model predictions increases when more quality in vitro data, particularly those on hepatic clearance and dermal absorption, are available as model input. The overall fold error distributions are useful for characterizing model uncertainty. We concluded that by identifying and quantifying the uncertainties in the tiered approach, we can increase the confidence in using PBK modelling to help make safety decisions on topically applied chemicals in the absence of human pharmacokinetic data.