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

The intracellular free concentration of endocrine disrupting chemicals enables translation between cell-free and cell-based estrogenic activity assays

Many environmental toxicants can activate estrogen receptor α (ERα), disrupting normal endocrine function. While these activities are predicted across in silico, in vitro, and in vivo models, translating active concentrations between these systems remains challenging. We hypothesized that cellular uptake and the resulting free intracellular toxicant concentration could bridge this gap. Using cell-free (hER) and cell-based (ERα-CALUX cells) estrogen assays, we tested this hypothesis by determination of the free intracellular concentration available for binding to the intracellularly located ERα. Predictive modeling identified three classes of estrogenic chemicals from the ToxCast collection: bisphenols, parabens, and phthalates. Experimental data confirmed potency differences of up to 100-fold between the cell-free and cell-based models. Cellular toxicokinetic (TK) parameters, including cellular uptake and intracellular binding, were determined using computational and experimental methods. Incorporating experimental TK parameters significantly improved the correlation between ERα activities in the cell-free and cellular models (from r=0.6230, P=0.0989 without corrections to r=0.8869, P=0.0033 after corrections), and bridged the gap between the cell free and cell based assays. Both computational and experimental TK parameters varied widely across chemical classes and compounds. Correcting active concentrations for free intracellular levels enhanced assay correlations, with experimentally derived corrections showing the strongest improvement with r=0.8869 (compared to the in silico derived corrections with r=0.811). Our findings highlight the critical role of free intracellular concentration in determining the biological activity of estrogenic toxicants and emphasize its importance in accurately assessing their endocrine-disrupting potential.

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.

From In Vivo Predictive Dissolution to Virtual Bioequivalence: A GastroPlus®-Driven Framework for Generic Candesartan Cilexetil Tablets

Background: Candesartan cilexetil, a Biopharmaceutics Classification System (BCS) II prodrug, demonstrates compromised bioavailability attributable to its limited aqueous solubility coupled with P-glycoprotein (P-gp)-mediated efflux and hepatic first-pass metabolism, thereby introducing complexities in generic drug bioequivalence assessments. With the rapid advancement of computational technologies, the integration of biorelevant dissolution methodologies with physiologically based pharmacokinetic (PBPK) modeling is emerging as a transformative paradigm in advancing bioequivalence evaluation strategies for generic drug products. This study presents a GastroPlus®-driven framework integrating in vivo predictive dissolution (IPD) and virtual bioequivalence (VBE) to evaluate the quality consistency of generic candesartan cilexetil tablets. Methods: By developing an oral PBPK model in GastroPlus®, we established an IPD method using a phosphate-buffer-based flow-through cell dissolution apparatus. In vitro dissolution profiles of generic tablets from four manufacturers were measured and incorporated into the model to perform VBE simulations. Results: The results demonstrated that only the product from Company A achieved virtual bioequivalence with the reference product, aligning with real-world quality consistency assessments. Conclusions: The proposed framework exhibited robust predictive capability, bridging in vitro dissolution data to in vivo bioequivalence outcomes, thereby offering a cost-effective and efficient strategy for formulation optimization and preclinical bioequivalence evaluation of generic drugs.

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.

Per- and polyfluoroalkyl substances alter innate immune function: evidence and data gaps

Per- and polyfluoroalkyl substances (PFASs) are a large class of compounds used in a variety of processes and consumer products. Their unique chemical properties make them ubiquitous and persistent environmental contaminants while also making them economically viable and socially convenient. To date, several reviews have been published to synthesize information regarding the immunotoxic effects of PFASs on the adaptive immune system. However, these reviews often do not include data on the impact of these compounds on innate immunity. Here, current literature is reviewed to identify and incorporate data regarding the effects of PFASs on innate immunity in humans, experimental models, and wildlife. Known mechanisms by which PFASs modulate innate immune function are also reviewed, including disruption of cell signaling, metabolism, and tissue-level effects. For PFASs where innate immune data are available, results are equivocal, raising additional questions about common mechanisms or pathways of toxicity, but highlighting that the innate immune system within several species can be perturbed by exposure to PFASs. Recommendations are provided for future research to inform hazard identification, risk assessment, and risk management practices for PFASs to protect the immune systems of exposed organisms as well as environmental health.

Global sensitivity analysis of Open Systems Pharmacology Suite physiologically based pharmacokinetic models

Sensitivity analyses are important components of physiologically based pharmacokinetic (PBPK) model development and are required by regulatory agencies for PBPK submissions. They assess the impact of parametric uncertainty and variability on model estimates, aid model optimization by identifying parameters requiring calibration, and enable the testing of assumptions within PBPK models. One-at-a-time (OAT) sensitivity analyses quantify the impact on a model output in response to changes in a single parameter while holding others fixed. Global sensitivity analysis (GSA) methods provide more comprehensive assessments by accounting for changes in all uncertain or variable parameters, though at a higher computational cost. This tutorial article presents a software package for conducting both OAT and GSA of PBPK models built in the Open Systems Pharmacology (OSP) Suite. The tool is accessible through either an R script or a graphical user interface, and the outputs consist of sensitivity metrics of pharmacokinetic (PK) parameters, such as Cmax and AUC, evaluated with respect to model input parameters. Results are formatted according to regulatory standards. The OAT analysis methods comprise two-way local sensitivity analyses and probabilistic uncertainty analyses, whereas the GSA methods include the Morris, Sobol, and EFAST methods. These analyses can be conducted on single PBPK models or pairs of models for the evaluation of the sensitivity of PK parameter ratios in drug-drug interaction studies. The practical application of the package is demonstrated through three illustrative case studies.

The Role of Simulation Science in Public Health at the Agency for Toxic Substances and Disease Registry: An Overview and Analysis of the Last Decade

Environmental exposures are ubiquitous and play a significant, and sometimes understated, role in public health as they can lead to the development of various chronic and infectious diseases. In an ideal world, there would be sufficient experimental data to determine the health effects of exposure to priority environmental contaminants. However, this is not the case, as emerging chemicals are continuously added to this list, furthering the data gaps. Recently, simulation science has evolved and can provide appropriate solutions using a multitude of computational methods and tools. In its quest to protect communities across the country from environmental health threats, ATSDR employs a variety of simulation science tools such as Physiologically Based Pharmacokinetic (PBPK) modeling, Quantitative Structure-Activity Relationship (QSAR) modeling, and benchmark dose (BMD) modeling, among others. ATSDR's use of such tools has enabled the agency to evaluate exposures in a timely, efficient, and effective manner. ATSDR's work in simulation science has also had a notable impact beyond the agency, as evidenced by external researchers' widespread appraisal and adaptation of the agency's methodology. ATSDR continues to advance simulation science tools and their applications by collaborating with researchers within and outside the agency, including other federal/state agencies, NGOs, the private sector, and academia.

Effects of novel flame retardants tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) and triphenyl phosphate (TPhP) on function and homeostasis in human and rat pancreatic beta-cell lines

Despite the fact that environmental pollution has been implicated in the global rise of diabetes, the research on the impact of emerging pollutants such as novel flame retardants remains limited. In line with the shift towards the use of non-animal approaches in toxicological testing, this study aimed to investigate the effects of two novel flame retardants tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) and triphenyl phosphate (TPhP) in rat (INS1E) and human (NES2Y) pancreatic beta-cell lines. One-week exposure to 1 μM and 10 μM TDCIPP and TPhP altered intracellular insulin and proinsulin levels, but not the levels of secreted insulin (despite the presence of a statistically insignificant trend). The exposures also altered the protein expression of several factors involved in beta-cell metabolic pathways and signaling, including ATP citrate lyase, isocitrate dehydrogenase 1, perilipins, glucose transporters, ER stress-related factors, and antioxidant enzymes. This study has brought new and valuable insights into the toxicity of TDCIPP and TPhP on beta-cell function and revealed alterations that might impact insulin secretion after more extended exposure. It also adds to the scarce studies using in vitro pancreatic beta-cells models in toxicological testing, thereby promoting the development of non-animal testing strategy for identifying pro-diabetic effects of chemical pollutants.

Making PBPK models more reproducible in practice

Systems biology aims to understand living organisms through mathematically modeling their behaviors at different organizational levels, ranging from molecules to populations. Modeling involves several steps, from determining the model purpose to developing the mathematical model, implementing it computationally, simulating the model's behavior, evaluating, and refining the model. Importantly, model simulation results must be reproducible, ensuring that other researchers can obtain the same results after writing the code de novo and/or using different software tools. Guidelines to increase model reproducibility have been published. However, reproducibility remains a major challenge in this field. In this paper, we tackle this challenge for physiologically-based pharmacokinetic (PBPK) models, which represent the pharmacokinetics of chemicals following exposure in humans or animals. We summarize recommendations for PBPK model reporting that should apply during model development and implementation, in order to ensure model reproducibility and comprehensibility. We make a proposal aiming to harmonize abbreviations used in PBPK models. To illustrate these recommendations, we present an original and reproducible PBPK model code in MATLAB, alongside an example of MATLAB code converted to Systems Biology Markup Language format using MOCCASIN. As directions for future improvement, more tools to convert computational PBPK models from different software platforms into standard formats would increase the interoperability of these models. The application of other systems biology standards to PBPK models is encouraged. This work is the result of an interdisciplinary collaboration involving the ELIXIR systems biology community. More interdisciplinary collaborations like this would facilitate further harmonization and application of good modeling practices in different systems biology fields.

In vitro to in vivo extrapolation to derive a metabolism factor for estimating the aggregate exposure to salicylic acid after dermal exposure of its esters

As part of the safety assessment of salicylate esters in cosmetics, we developed a metabolism factor based on in vitro to in vivo extrapolation (IVIVE) to provide a better estimation of the aggregate internal exposure to the common metabolite, salicylic acid. Optimal incubation conditions using human liver S9 were identified before measuring salicylic acid formation from 31 substances. Four control substances, not defined as salicylic esters but which could be mistaken as such due to their nomenclature, did not form salicylic acid. For the remaining substances, higher in vitro intrinsic clearance (CLint, in vitro) values generally correlated with lower LogP values. A "High-Throughput Pharmacokinetic" (HTPK) model was used to extrapolate CLint, in vitro values to human in vivo clearance and half-lives. The latter were used to calculate the percentage of substance metabolised to salicylic acid in 24 h in vivo following human exposure to the ester, i.e. the "metabolism factor". The IVIVE model correctly reproduced the observed elimination rate of 3 substances using in silico or in vitro input parameters. For other substances, in silico only-based predictions generally resulted in lower metabolism factors than when in vitro values for plasma binding and liver S9 CLint, in vitro were used. Therefore, in vitro data input provides the more conservative metabolism factors compared to those derived using on in silico input. In conclusion, these results indicate that not all substances contribute equally (or at all) to the systemic exposure to salicylic acid. Therefore, we propose a realistic metabolism correction factor by which the potential contribution of salicylate esters to the aggregate consumer exposure to salicylic acid from cosmetic use can be estimated.

Effects of Aqueous Boundary Layers and Paracellular Transport on the Efflux Ratio as a Measure of Active Transport Across Cell Layers

The efflux ratio (ER), determined by Caco-2/MDCK assays, is the standard in vitro metric to establish qualitatively whether a compound is a substrate of an efflux transporter. However, others have also enabled the utilisation of this metric quantitatively by deriving a relationship that expresses the ER as a function of the intrinsic membrane permeability of the membrane (P0) as well as the permeability of carrier-mediated efflux (Ppgp). As of yet, Ppgp cannot be measured directly from transport experiments or otherwise, but the ER relationship provides easy access to this value if P0 is known. However, previous derivations of this relationship failed to consider the influence of additional transport resistances such as the aqueous boundary layers (ABLs) and the filter on which the monolayer is grown. Since single fluxes in either direction can be heavily affected by these experimental artefacts, it is crucial to consider the potential impact on the ER. We present a model that includes these factors and show both mathematically and experimentally that this simple ER relationship also holds for the more realistic scenario that does not neglect the ABLs/filter. Furthermore, we also show mathematically how paracellular transport affects the ER, and we experimentally confirm that paracellular dominance reduces the ER to unity and can mask potential efflux.

Estimation of volatile organic compound exposure concentrations and time to reach a specific dermal absorption using physiologically based pharmacokinetic modeling

A procedure was proposed to estimate dermal exposures based on a physiologically based pharmacokinetic (PBPK) model developed in rats. The study examined vapor concentrations ranging from 500 to 10,000 ppm for dibromomethane and 2,500 to 40,000 ppm for bromochloromethane. These concentrations were reconstructed based on chemical blood levels measured in 4 hr, with errors varying from 0.0% to 52.0%. The PBPK approach adequately predicted the blood concentrations and helped simulate contaminant transport through the stratum corneum and distribution in the body compartments. The proposed technique made it possible to estimate the skin absorption time (SAT) obtained from acute inhalation toxicity data. An inverse relationship exists between the SAT and exposure concentration. The method can be helpful in toxicology and risk assessment of hazardous volatile organic compounds.

Investigating industrial PAH air pollution in relation to population exposure in major countries: A scoring approach

Polycyclic aromatic hydrocarbons (PAHs) are common air pollutants worldwide, associated with industrial processes. In the general population, both modeling and field studies revealed a positive correlation between air PAH concentrations and urinary PAH metabolite levels. Many countries lack population urinary data that correspond to local PAH air concentrations. Thus, we proposed a scoring-based approximate approach to investigating that correlation in selected countries, hypothesizing that PAH air concentrations in selected regions could represent the national air quality influenced by industrial emission and further correlate to PAH internal exposure in the general population. This research compiled 85 peer-reviewed journal articles and 9 official monitoring datasets/reports covering 34 countries, 16 of which with both atmospheric PAH data and human biomonitoring data. For the air pollution score (AirS), Egypt had the highest AirS at 0.94 and Pakistan was at the bottom of the score ranking at -1.95, as well as the median in the UK (AirS: 0.50). For the population exposure score (ExpS), China gained the top ExpS at 0.44 and Spain was with the lowest ExpS of -1.52, with the median value in Italy (ExpS: 0.43). Through the correlation analysis, atmospheric PAHs and their corresponding urinary metabolites provided a positive relationship to a diverse extent, indicating that the related urinary metabolites could reflect the population's exposure to specific atmospheric PAHs. The findings also revealed that in the 16 selected countries, AirS indexes were positively correlated with ExpS indexes, implying that higher PAH levels in the air may lead to elevated metabolite urinary levels in general populations. Furthermore, lowering PAH air concentrations could reduce population internal PAH exposure, implying that strict PAH air regulation or emission would reduce health risks for general populations. Notably, this study was an ideal theoretical research based on proposed assumptions to some extent. Further research should focus on understanding exposure pathways, protecting vulnerable populations, and improving the PAH database to optimize PAH pollution control.