In vitro-to-in vivo extrapolation (IVIVE) by PBTK modeling for animal-free risk assessment approaches of potential endocrine-disrupting compounds

A novel approach to triazole fungicides risk characterization: Bridging human biomonitoring and computational toxicology

Brazil stands as the world's leading coffee producer, where the extensive use of pesticides is economically critical yet poses health and environmental risks due to their non-selective mechanisms of action. Specifically, triazole fungicides are widely used in agriculture to manage fungal diseases and are known to disrupt mammalian CYP450 and liver microsomal enzymes. This research establishes a framework for risk characterization of human exposure to triazole fungicides by internal-dose biomonitoring, biochemical marker measurements, and integration of high-throughput screening (HTS) data via computational toxicology workflows from the Integrated Chemical Environment (ICE). Volunteers from the southern region of Minas Gerais, Brazil, were divided into two groups: farmworkers and spouses occupationally and environmentally exposed to pesticides from rural areas (n = 140) and individuals from the urban area to serve as a comparison group (n = 50). Three triazole fungicides, cyproconazole, epoxiconazole, and triadimenol, were detected in the urine samples of both men and women in the rural group. Androstenedione and testosterone hormones were significantly reduced in the farmworker group (Mann-Whitney test, p < 0.0001). The data show a significant inverse association of testosterone with cholesterol, LDL, VLDL, triglycerides, and glucose and a direct association with HDL (Spearman's correlation, p < 0.05). In the ICE workflow, active in vitro HTS assays were identified for the three measured triazoles and three other active ingredients from the pesticide formulations. The curated HTS data confirm bioactivities predominantly related to steroid hormone metabolism, cellular stress processes, and CYP450 enzymes impacted by fungicide exposure at occupationally and environmentally relevant concentrations based on the in vitro to in vivo extrapolation models. These results characterize the potentially significant human health risk, particularly from the high frequency and intensity of exposure to epoxiconazole. This study showcases the critical role of biomonitoring and utility of computational tools in evaluating pesticide exposure and minimizing the risk.

Development and validation of PBPK models for genistein and daidzein for use in a next-generation risk assessment

Introduction

All cosmetic ingredients must be evaluated for their safety to consumers. In the absence of in vivo data, systemic concentrations of ingredients can be predicted using Physiologically based Pharmacokinetic (PBPK) models. However, more examples are needed to demonstrate how they can be validated and applied in Next-Generation Risk Assessments (NGRA) of cosmetic ingredients. We used a bottom-up approach to develop human PBPK models for genistein and daidzein for a read-across NGRA, whereby genistein was the source chemical for the target chemical, daidzein.

Methods

An oral rat PBPK model for genistein was built using PK-Sim® and in vitro ADME input data. This formed the basis of the daidzein oral rat PBPK model, for which chemical-specific input parameters were used. Rat PBPK models were then converted to human models using human-specific physiological parameters and human in vitro ADME data. In vitro skin metabolism and penetration data were used to build the dermal module to represent the major route of exposure to cosmetics.

Results

The initial oral rat model for genistein was qualified since it predicted values within 2-fold of measured in vivo PK values. This was used to predict plasma concentrations from the in vivo NOAEL for genistein to set test concentrations in bioassays. Intrinsic hepatic clearance and unbound fractions in plasma were identified as sensitive parameters impacting the predicted Cmax values. Sensitivity and uncertainty analyses indicated the developed PBPK models had a moderate level of confidence. An important aspect of the development of the dermal module was the implementation of first-pass metabolism, which was extensive for both chemicals. The final human PBPK model for daidzein was used to convert the in vitro PoD of 33 nM (from an estrogen receptor transactivation assay) to an external dose of 0.2% in a body lotion formulation.

Conclusion

PBPK models for genistein and daidzein were developed as a central component of an NGRA read-across case study. This will help to gain regulatory confidence in the use of PBPK models, especially for cosmetic ingredients.

Predicting the in vivo developmental toxicity of fenarimol from in vitro toxicity data using PBTK modelling-facilitated reverse dosimetry approach

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.

Hepatic cholesterol biosynthesis and dioxin-induced dysregulation: A multiscale computational approach

Humans are constantly exposed to lipophilic persistent organic pollutants (POPs) that accumulate in fatty foods. Among the numerous POPs, dioxins, in particular 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), can impact several organ systems. While the hazard is clearly recognized, it is still difficult to develop a comprehensive understanding of the overall health impacts of dioxins. As chemical toxicity testing is steadily adopting new approach methodologies (NAMs), it becomes imperative to develop computational models that can bridge the data gaps between in vitro testing and in vivo outcomes. As an effort to address this challenge, we propose a multiscale computational approach using a "template-and-anchor" (T&A) structure. A template is a high-level umbrella model that permits the integration of information from various, detailed anchor models. In the present study, we use this T&A approach to describe the effect of TCDD on cholesterol dynamics. Specifically, we represent hepatic cholesterol biosynthesis as an anchor model that is perturbed by TCDD, leading to steatosis, along with alterations of plasma cholesterol. In the future, incorporating pertinent information from all anchor models into the template model will allow the characterization of the global effects of dioxin, which can subsequently be translated into overall - and ultimately personalized - human health risk assessment.

The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment

Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.

Impact of chemical pollution on threatened marine mammals: A systematic review

Marine mammals, due to their long life span, key position in the food web, and large lipid deposits, often face significant health risks from accumulating contaminants. This systematic review examines published literature on pollutant-induced adverse health effects in the International Union for Conservation of Nature (IUCN) red-listed marine mammal species. Thereby, identifying gaps in literature across different extinction risk categories, spatial distribution and climatic zones of studied habitats, commonly used methodologies, researched pollutants, and mechanisms from cellular to population levels. Our findings reveal a lower availability of exposure-effect data for higher extinction risk species (critically endangered 16%, endangered 15%, vulnerable 66%), highlighting the need for more research. For many threatened species in the Southern Hemisphere pollutant-effect relationships are not established. Non-destructively sampled tissues, like blood or skin, are commonly measured for exposure assessment. The most studied pollutants are POPs (31%), metals (30%), and pesticides (17%). Research on mixture toxicity is scarce while pollution-effect studies primarily focus on molecular and cellular levels. Bridging the gap between molecular data and higher-level effects is crucial, with computational approaches offering a high potential through in vitro to in vivo extrapolation using (toxico-)kinetic modelling. This could aid in population-level risk assessment for threatened marine mammals.

Alternatives to animal testing in toxicity testing: Current status and future perspectives in food safety assessments

The development of alternative methods to animal testing has gained great momentum since Russel and Burch introduced the "3Rs" concept of Reduction, Refinement, and Replacement of animals in safety testing in 1959. Several alternatives to animal testing have since been introduced, including but not limited to in vitro and in chemico test systems, in silico models, and computational models (e.g., [quantitative] structural activity relationship models, high-throughput screens, organ-on-chip models, and genomics or bioinformatics) to predict chemical toxicity. Furthermore, several agencies have developed robust integrated testing strategies to determine chemical toxicity. The cosmetics sector is pioneering the adoption of alternative methodologies for safety evaluations, and other sectors are aiming to completely abandon animal testing by 2035. However, beyond the use of in vitro genetic testing, agencies regulating the food industry have been slow to implement alternative methodologies into safety evaluations compared with other sectors; setting health-based guidance values for food ingredients requires data from systemic toxicity, and to date, no standalone validated alternative models to assess systemic toxicity exist. The abovementioned models show promise for assessing systemic toxicity with further research. In this paper, we review the current alternatives and their applicability and limitations in food safety evaluations.

Research advances in identification procedures of endocrine disrupting chemicals

Endocrine disrupting chemicals (EDCs) are increasingly concerned substance endangering human health and environment. However, there is no unified standard for identifying chemicals as EDCs, which is also controversial internationally. In this review, the procedures for EDC identification in different organizations/countries were described. Importantly, three aspects to be considered in identifying chemical substances as EDCs were summarized, which were mechanistic data, animal experiments, and epidemiological information. The relationships between them were also discussed. To elaborate more clearly on these three aspects of evidence, scientific data on some chemicals including bisphenol A, 1,2-dibromo-4-(1,2 dibromoethyl) cyclohexane and perchlorate were collected and evaluated. Altogether, the above three chemicals were assessed for interfering with hormones and elaborated their health hazards from macroscopic to microscopic. This review is helpful for standardizing the identification procedure of EDCs.

Linking Transthyretin-Binding Chemicals and Free Thyroid Hormones: In Vitro to In Vivo Extrapolation Based on a Competitive Binding Model

Large numbers of pollutants competitively inhibit the binding between thyroid hormones and transthyretin (TTR) in vitro. However, the impact of this unintended binding on free thyroid hormones in vivo has not yet been characterized. Herein, we established a quantitative in vitro to in vivo extrapolation (QIVIVE) method based on a competitive binding model to quantify the effect of TTR-binding chemicals on free thyroid hormones in human blood. Twenty-five TTR-binding chemicals including 6 hydroxyl polybromodiphenyl ethers (OH-PDBEs), 6 hydroxyl polychlorobiphenyls (OH-PCBs), 4 halogenphenols, 5 per- and polyfluorinated substances (PFASs), and 4 phenols were selected for investigation. Incorporating the in vitro binding parameters and human exposure data, the QIVIVE model could well predict the in vivo effect on free thyroid hormones. Co-exposure to twenty-five typical TTR-binding chemicals resulted in median increases of 0.080 and 0.060% in circulating levels of free thyroxine (FT4) and free triiodothyronine (FT3) in the general population. Individuals with occupational exposure to TTR-binding chemicals suffered 1.88-32.2% increases in free thyroid hormone levels. This study provides a quantitative tool to evaluate the thyroid-disrupting risks of TTR-binding chemicals and proposes a new framework for assessing the in vivo effects of chemical exposures on endogenous molecules.

Pollution effects on retinal health: A review on current methodologies and findings

In our daily life, we are exposed to numerous industrial chemicals that may be harmful to the retina, which is a delicate and sensitive part of our eyes. This could lead to irreversible changes and cause retinal diseases or blindness. Current retinal environmental health studies primarily utilize animal models, isolated mammalian retinas, animal- or human-derived retinal cells, and retinal organoids, to address both pre- and postnatal exposure. However, as there is limited toxicological information available for specific populations, human induced pluripotent stem cell (hiPSC)-induced models could be effective tools to supplement such data. In order to obtain more comprehensive and reliable toxicological information, we need more appropriate models, novel evaluation methods, and computational technologies to develop portable equipment. This review mainly focused on current toxicology models with particular emphasis on retinal organoids, and it looks forward to future models, analytical methods, and equipment that can efficiently and accurately evaluate retinal toxicity.

Rapid equilibrium dialysis, ultrafiltration or ultracentrifugation? Evaluation of methods to quantify the unbound fraction of substances in plasma

In pharmacokinetics plasma protein binding (PPB) is a well-established parameter impacting drug disposition. The unbound fraction (f_u) is arguably regarded the effective concentration at the target site. Pharmacology and toxicology, increasingly use in vitro models. The translation of in vitro concentrations to in vivo doses can be supported by toxicokinetic modelling, e.g. physiologically based toxicokinetic models (PBTK). PPB of a test substance is an input parameter for PBTK. We compared three methods to quantify f_u: rapid equilibrium dialysis (RED), ultrafiltration (UF) and ultracentrifugation (UC) using twelve substances covering a wide range of Log P_ow (-0.1 to 6.8) and molecular weights (151 and 531 g/mol): Acetaminophen, Bisphenol A, Caffeine, Colchicine, Fenarimol, Flutamide, Genistein, Ketoconazole, α-Methyltestosterone, Tamoxifen, Trenbolone and Warfarin. After RED and UF separation, three polar substances (Log P_ow < 2) were largely unbound (f_u > 70%), while more lipophilic substances were largely bound (f_u < 33%). Compared to RED or UF, UC resulted in a generally higher f_u of lipophilic substances. f_u obtained after RED and UF were more consistent with published data. For half of the substances, UC resulted in f_u higher than the reference data. UF, RED and both UF and UC, resulted in lower f_u of Flutamide, Ketoconazole and Colchicine, respectively. For f_u quantifications, the separation method should be selected according to the test substance's properties. Based on our data, RED is suitable for a broader range of substances while UC and UF are suitable for polar substances.

Human health risk assessment of 6:2 Cl-PFESA through quantitative in vitro to in vivo extrapolation by integrating cell-based assays, an epigenetic key event, and physiologically based pharmacokinetic modeling

Human health risk assessment of chemicals is essential but often relies on time-consuming and animal and labor-extensive procedures. Here, we develop a population-based, quantitative in vitro to in vivo extrapolation (QIVIVE) approach which depended on cellular effects monitored by in vitro assays, considered chemical internal concentration determined by LC-MS/MS, extrapolated into in vivo target tissue concentration through physiologically based pharmacokinetic (PBPK) modelling, and assessed populational health risk using in silico modelling. By applying this QIVIVE approach to 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), as a representative of the emerging pollutants, we find that 6:2 Cl-PFESA disturbed lipid homeostasis in HepG2 cells through enhancement of lipid accumulation and fatty acid β-oxidation, during which miR-93-5p served as a key event towards toxicity and thus, could serve as an efficient toxicity marker for risk assessment; further, the disruption potency of lipid homeostasis of 6:2 Cl-PFESA for the most of studied populations in China might be of moderate concern. Together, our approach improved the reliability of QIVIVE during human health risk assessment, which can readily be used for other chemicals.

Development of physiologically based toxicokinetic models for 3-monochloropropane-1,2-diol and glycidol

3-Monochloropropane-1,2-diol (3-MCPD), glycidol, together with their fatty acid esters are commonly presented in various food and have shown carcinogenicity in various laboratory animals. Public health risk assessment of 3-MPCD and glycidol exposure relies on quantitative tools that represent their in vivo toxicokinetics. In order to better understand the absorption, distribution, metabolism, and excretion profiles of 3-MCPD and glycidol in male rats, a physiologically based pharmacokinetic (PBTK) model was developed. The model's predictive power was evaluated by comparing in silico simulations to in vivo time course data obtained from experimental studies. Results indicate that our PBTK model successfully captured the toxicokinetics of both free chemicals in key organs, and their metabolites in accessible biological fluids. With the validated PBTK model, we then gave an animal-free example on how to extrapolate the toxicological knowledge acquired from a single gavage to a realistic dietary intake scenario. Three biomarkers, free compound in serum, urinary metabolite DHPMA, and glycidol-hemoglobin adduct (diHOPrVal) were selected for in silico simulation following constant dietary intakes, and their internal levels were correlated with proposed external daily exposure via reverse dosimetry approaches. Taken together, our model provides a computational approach for extrapolating animal toxicokinetic experiments to biomonitoring measurement and risk assessment.

Development, testing, parameterisation, and calibration of a human PBK model for the plasticiser, di (2-ethylhexyl) adipate (DEHA) using in silico, in vitro and human biomonitoring data

Introduction: A physiologically based biokinetic model for di (2-ethylhexyl) adipate (DEHA) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHA following a single oral dosage of 50 mg to two male and two female volunteers. Methods: The model was parameterized using in vitro and in silico methods such as, measured intrinsic hepatic clearance scaled from in vitro to in vivo and algorithmically predicted parameters such as plasma unbound fraction and tissue:blood partition coefficients (PCs). Calibration of the DEHA model was achieved using concentrations of specific downstream metabolites of DEHA excreted in urine. The total fractions of ingested DEHA eliminated as specific metabolites were estimated and were sufficient for interpreting the human biomonitoring data. Results: The specific metabolites of DEHA, mono-2-ethyl-5-hydroxyhexyl adipate (5OH-MEHA), mono-2-ethyl-5-oxohexyl adipate (5oxo-MEHA), mono-5-carboxy-2-ethylpentyl adipate (5cx-MEPA) only accounted for ∼0.45% of the ingested DEHA. Importantly, the measurements of adipic acid, a non-specific metabolite of DEHA, proved to be important in model calibration. Discussion: The very prominent trends in the urinary excretion of the metabolites, 5cx-MEPA and 5OH-MEHA allowed the important absorption mechanisms of DEHA to be modelled. The model should be useful for the study of exposure to DEHA of the general human population.

Development, testing, parameterisation, and calibration of a human PBPK model for the plasticiser, di-(2-ethylhexyl) terephthalate (DEHTP) using in silico, in vitro and human biomonitoring data

A physiologically based pharmacokinetic model for di-(2-ethylhexyl) terephthalate (DEHTP) based on a refined model for di-(2-propylheptyl) phthalate (DPHP) was developed to interpret the metabolism and biokinetics of DEHTP following a single oral dose of 50 mg to three male volunteers. In vitro and in silico methods were used to generate parameters for the model. For example, measured intrinsic hepatic clearance scaled from in vitro to in vivo and plasma unbound fraction and tissue:blood partition coefficients (PCs) were predicted algorithmically. Whereas the development and calibration of the DPHP model was based upon two data streams, blood concentrations of parent chemical and first metabolite and the urinary excretion of metabolites, the model for DEHTP was calibrated against a single data stream, the urinary excretion of metabolites. Despite the model form and structure being identical significant quantitative differences in lymphatic uptake between the models were observed. In contrast to DPHP the fraction of ingested DEHTP entering lymphatic circulation was much greater and of a similar magnitude to that entering the liver with evidence for the dual uptake mechanisms discernible in the urinary excretion data. Further, the absolute amounts absorbed by the study participants, were much higher for DEHTP relative to DPHP. The in silico algorithm for predicting protein binding performed poorly with an error of more than two orders of magnitude. The extent of plasma protein binding has important implications for the persistence of parent chemical in venous blood-inferences on the behaviour of this class of highly lipophilic chemicals, based on calculations of chemical properties, should be made with extreme caution. Attempting read across for this class of highly lipophilic chemicals should be undertaken with caution since basic adjustments to PCs and metabolism parameters would be insufficient, even when the structure of the model itself is appropriate. Therefore, validation of a model parameterized entirely with in vitro and in silico derived parameters would need to be calibrated against several human biomonitoring data streams to constitute a data rich source chemical to afford confidence for future evaluations of other similar chemicals using the read-across approach.

Advancing New Approach Methodologies (NAMs) for Tobacco Harm Reduction: Synopsis from the 2021 CORESTA SSPT-NAMs Symposium

New approach methodologies (NAMs) are emerging chemical safety assessment tools consisting of in vitro and in silico (computational) methodologies intended to reduce, refine, or replace (3R) various in vivo animal testing methods traditionally used for risk assessment. Significant progress has been made toward the adoption of NAMs for human health and environmental toxicity assessment. However, additional efforts are needed to expand their development and their use in regulatory decision making. A virtual symposium was held during the 2021 Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) Smoke Science and Product Technology (SSPT) conference (titled "Advancing New Alternative Methods for Tobacco Harm Reduction"), with the goals of introducing the concepts and potential application of NAMs in the evaluation of potentially reduced-risk (PRR) tobacco products. At the symposium, experts from regulatory agencies, research organizations, and NGOs shared insights on the status of available tools, strengths, limitations, and opportunities in the application of NAMs using case examples from safety assessments of chemicals and tobacco products. Following seven presentations providing background and application of NAMs, a discussion was held where the presenters and audience discussed the outlook for extending the NAMs toxicological applications for tobacco products. The symposium, endorsed by the CORESTA In Vitro Tox Subgroup, Biomarker Subgroup, and NextG Tox Task Force, illustrated common ground and interest in science-based engagement across the scientific community and stakeholders in support of tobacco regulatory science. Highlights of the symposium are summarized in this paper.

Toward Realistic Dosimetry In Vitro: Determining Effective Concentrations of Test Substances in Cell Culture and Their Prediction by an In Silico Mass Balance Model

Nominal concentrations (C_Nom) in cell culture media are routinely used to define concentration-effect relationships in the in vitro toxicology. The actual concentration in the medium (C_Medium) can be affected by adsorption processes, evaporation, or degradation of chemicals. Therefore, we measured the total and free concentration of 12 chemicals, covering a wide range of lipophilicity (log K_OW -0.07-6.84), in the culture medium (C_Medium) and cells (C_Cell) after incubation with Balb/c 3T3 cells for up to 48 h. Measured values were compared to predictions using an as yet unpublished in silico mass balance model that combined relevant equations from similar models published by others. The total C_Medium for all chemicals except tamoxifen (TAM) were similar to the C_Nom. This was attributed to the cellular uptake of TAM and accumulation into lysosomes. The free (i.e., unbound) C_Medium for the low/no protein binding chemicals were similar to the C_Nom, whereas values of all moderately to highly protein-bound chemicals were less than 30% of the C_Nom. Of the 12 chemicals, the two most hydrophilic chemicals, acetaminophen (APAP) and caffeine (CAF), were the only ones for which the C_Cell was the same as the C_Nom. The C_Cell for all other chemicals tended to increase over time and were all 2- to 274-fold higher than C_Nom. Measurements of C_Cytosol, using a digitonin method to release cytosol, compared well with C_Cell (using a freeze-thaw method) for four chemicals (CAF, APAP, FLU, and KET), indicating that both methods could be used. The mass balance model predicted the total C_Medium within 30% of the measured values for 11 chemicals. The free C_Medium of all 12 chemicals were predicted within 3-fold of the measured values. There was a poorer prediction of C_Cell values, with a median overprediction of 3- to 4-fold. In conclusion, while the number of chemicals in the study is limited, it demonstrates the large differences between C_Nom and total and free C_Medium and C_Cell, which were also relatively well predicted by the mass balance model.

Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis

Data from a high-throughput human adrenocortical carcinoma assay (HT-H295R) for steroid hormone biosynthesis are available for >2000 chemicals in single concentration and 654 chemicals in multi-concentration (mc). Previously, a metric describing the effect size of a chemical on the biosynthesis of 11 hormones was derived using mc data referred to as the maximum mean Mahalanobis distance (maxmMd). However, mc HT-H295R assay data remain unavailable for many chemicals. This work leverages existing HT-H295R assay data by constructing structure-activity relationships to make predictions for data-poor chemicals, including: (1) identification of individual structural descriptors, known as ToxPrint chemotypes, associated with increased odds of affecting estrogen or androgen synthesis; (2) a random forest (RF) classifier using physicochemical property descriptors to predict HT-H295R maxmMd binary (positive or negative) outcomes; and, (3) a local approach to predict maxmMd binary outcomes using nearest neighbors (NNs) based on two types of chemical fingerprints (chemotype or Morgan). Individual chemotypes demonstrated high specificity (85-98%) for modulators of estrogen and androgen synthesis but with low sensitivity. The best RF model for maxmMd classification included 13 predicted physicochemical descriptors, yielding a balanced accuracy (BA) of 71% with only modest improvement when hundreds of structural features were added. The best two NN models for binary maxmMd prediction demonstrated BAs of 85 and 81% using chemotype and Morgan fingerprints, respectively. Using an external test set of 6302 chemicals (lacking HT-H295R data), 1241 were identified as putative estrogen and androgen modulators. Combined results across the three classification models (global RF model and two local NN models) predict that 1033 of the 6302 chemicals would be more likely to affect HT-H295R bioactivity. Together, these in silico approaches can efficiently prioritize thousands of untested chemicals for screening to further evaluate their effects on steroid biosynthesis.

Investigating the uncertainty of prediction accuracy for the application of physiologically based pharmacokinetic models to animal-free risk assessment of cosmetic ingredients

Physiologically based pharmacokinetic (PBPK) models are considered useful tools in animal-free risk assessment. To utilize PBPK models for risk assessment, it is necessary to compare their reliability with in vivo data. However, obtaining in vivo pharmacokinetics data for cosmetic ingredients is difficult, complicating the utilization of PBPK models for risk assessment. In this study, to utilize PBPK models for risk assessment without accuracy evaluation, we proposed a novel concept-the modeling uncertainty factor (MUF). By calculating the prediction accuracy for 150 compounds, we established that using in vitro data for metabolism-related parameters and limiting the applicability domain increase the prediction accuracy of a PBPK model. Based on the 97.5th percentile of prediction accuracy, MUF was defined at 10 for the area under the plasma concentration curve and 6 for C_max. A case study on animal-free risk assessment was conducted for bisphenol A using these MUFs. As this study was conducted mainly on pharmaceuticals, further investigation using cosmetic ingredients is pivotal. However, since internal exposure is essential in realizing animal-free risk assessment, our concept will serve as a useful tool to predict plasma concentrations without using in vivo data.

Physiologically Based Toxicokinetic Modeling of Bisphenols in Zebrafish (Danio rerio) Accounting for Variations in Metabolic Rates, Brain Distribution, and Liver Accumulation

Bisphenol A (BPA) is an industrial chemical, which has raised human health and environmental concerns due to its endocrine-disrupting properties. BPA analogues are less well-studied despite their wide use in consumer products. These analogues have been detected in water and aquatic organisms around the world, with some analogues showing toxic effects in various species including fish. Here, we present novel organ-specific time-course distribution data of bisphenol Z (BPZ) in female zebrafish (Danio rerio), including concentrations in the ovaries, liver, and brain, a rarely sampled organ with high toxicological relevance. Furthermore, fish-specific in vitro biotransformation rates were determined for 11 selected bisphenols. A physiologically based toxicokinetic (PBTK) model was adapted for four of these bisphenols, which was able to predict levels in the gonads, liver, and brain as well as the whole body within a 2-5-fold error with respect to experimental data, covering several important target organs of toxicity. In particular, predicted liver concentrations improved compared to currently available PBTK models. Predicted data indicate that studied bisphenols mainly distribute to the carcass and gonads and less to the brain. Our model provides a tool to increase our understanding on the distribution and kinetics of a group of emerging pollutants.

The Evolution of Regulatory Toxicology: Where is the Gardener?

There is a need for paradigm change in the methodology employed for toxicological testing and assessment. It could be said that this change is well on its way, through an evolutionary progress analogous to that of natural selection. Darwin's Theory of Evolution has defined the idea of evolution and descendancy since the last third of the 19th century. Increasingly, this concept of 'evolution' is being applied beyond the field of biology. This Comment article discusses the progress of toxicological testing in the context of 'evolutionary pressure' and deliberates how this process can help foster the development, implementation and acceptance of mechanistic and human-relevant methods in this field. By comparing the current regulatory landscape in toxicity testing and assessment to specific elements in Charles Darwin's evolutionary theory, we aim to better understand the needs and requirements for the future.

Chemical and biological assessments of environmental mixtures: A review of current trends, advances, and future perspectives

Considering the chemical complexity and toxicity data gaps of environmental mixtures, most studies evaluate the chemical risk individually. However, humans are usually exposed to a cocktail of chemicals in real life. Mixture health assessment remains to be a research area having significant knowledge gaps. Characterization of chemical composition and bioactivity/toxicity are the two critical aspects of mixture health assessments. This review seeks to introduce the recent progress and tools for the chemical and biological characterization of environmental mixtures. The state-of-the-art techniques include the sampling, extraction, rapid detection methods, and the in vitro, in vivo, and in silico approaches to generate the toxicity data of an environmental mixture. Application of these novel methods, or new approach methodologies (NAMs), has increased the throughput of generating chemical and toxicity data for mixtures and thus refined the mixture health assessment. Combined with computational methods, the chemical and biological information would shed light on identifying the bioactive/toxic components in an environmental mixture.

Next Generation Risk Assessment of the Anti-Androgen Flutamide Including the Contribution of Its Active Metabolite Hydroxyflutamide

In next generation risk assessment (NGRA), non-animal approaches are used to quantify the chemical concentrations required to trigger bioactivity responses, in order to assure safe levels of human exposure. A limitation of many in vitro bioactivity assays, which are used in an NGRA context as new approach methodologies (NAMs), is that toxicokinetics, including biotransformation, are not adequately captured. The present study aimed to include, as a proof of principle, the bioactivity of the metabolite hydroxyflutamide (HF) in an NGRA approach to evaluate the safety of the anti-androgen flutamide (FLU), using the AR-CALUX assay to derive the NAM point of departure (PoD). The NGRA approach applied also included PBK modelling-facilitated quantitative in vitro to in vivo extrapolation (QIVIVE). The PBK model describing FLU and HF kinetics in humans was developed using GastroPlus™ and validated against human pharmacokinetic data. PBK model-facilitated QIVIVE was performed to translate the in vitro AR-CALUX derived concentration-response data to a corresponding in vivo dose-response curve for the anti-androgenicity of FLU, excluding and including the activity of HF (-HF and +HF, respectively). The in vivo benchmark dose 5% lower confidence limits (BMDL05) derived from the predicted in vivo dose-response curves for FLU, revealed a 440-fold lower BMDL05 when taking the bioactivity of HF into account. Subsequent comparison of the predicted BMDL05 values to the human therapeutic doses and historical animal derived PoDs, revealed that PBK modelling-facilitated QIVIVE that includes the bioactivity of the active metabolite is protective and provides a more appropriate PoD to assure human safety via NGRA, whereas excluding this would potentially result in an underestimation of the risk of FLU exposure in humans.

In utero exposure to a mixture of the perfluoroalkyl-isopropyl pesticide pyrifluquinazon with dibutyl phthalate cumulatively disrupts male rat reproductive development via different mechanisms of action

Administration of individual chemicals and mixtures during sexual differentiation that disrupt the androgen signaling pathway can induce reproductive abnormalities in male rats. In the current study, we co-administered the heptafluoroisopropyl pesticide pyrifluquinazon (PFQ), and dibutyl phthalate (DBP) to pregnant rats during sexual differentiation of the reproductive tract. Both chemicals have been shown to disrupt reproductive tract differentiation in a dose-related manner reducing male anogenital distance (AGD), permanently reducing androgen-dependent tissue weights and sperm counts, and inducing reproductive malformations in male offspring, albeit by different mechanisms of action that converge downstream in the androgen signaling pathway on a common key event. Rats were orally dosed from gestation days 14-18 with dilutions of PFQ and DBP at 0, 12.5, 25, 50, 75 and 100% of the top dose (100 mg/kg PFQ and 750 mg/kg DBP). The mixture ratio was selected such that each chemical would contribute equally to multiple effects on the male offspring reproductive tract and the dose range was designed to determine if the mixture produced additive effects predicted by dose addition or response addition models, or whether significant interactions occurred. Observed data were compared to dose and response addition model predictions. As hypothesized, the mixture reduced F1 male AGD, reproductive organ weights and sperm counts and induced hypospadias with dose addition consistently providing a better prediction of the observed effects than response addition. These results support our hypothesis that chemicals that disrupt the androgen signaling pathway induce dose-additive male reproductive abnormalities regardless of the specific mechanism of action.

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.

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

The goal of the present study was to assess the predictive performance of a minimal generic rat physiologically based kinetic (PBK) model based on in vitro and in silico input data to predict peak plasma concentrations (Cmax) upon single oral dosing. To this purpose, a dataset was generated of 3960 Cmax predictions for 44 compounds, applying different combinations of in vitro and in silico approaches for chemical parameterization, and comparison of the predictions to reported in vivo data. Best performance was obtained when (1) the hepatic clearance was parameterized based on in vitro measured intrinsic clearance values, (2) the method of Rodgers and Rowland for calculating partition coefficients, and (3) in silico calculated fraction unbound plasma and Papp values (the latter especially for very lipophilic compounds). Based on these input data, the median Cmax of 32 compounds could be predicted within 10-fold of the observed Cmax, with 22 out of these 32 compounds being predicted within 5-fold, and 8 compounds within 2-fold. Overestimations of more than 10-fold were observed for 12 compounds, whereas no underestimations of more than 10-fold occurred. Median Cmax predictions were frequently found to be within 10-fold of the observed Cmax when the scaled unbound hepatic intrinsic clearance (Clint,u) was either higher than 20 l/h or lower than 1 l/h. Similar findings were obtained with a test set of 5 in-house BASF compounds. Overall, this study provides relevant insights in the predictive performance of a minimal PBK model based on in vitro and in silico input data.

The use of in vitro methods in assessing human health risks associated with short-chain perfluoroalkyl and polyfluoroalkyl substances (PFAS)

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a large class of industrial chemicals with a ubiquitous and persistent presence in the environment. Of the thousands of PFAS used by consumers and industry, very few have been thoroughly characterized for potential adverse effects. This is especially true for the novel short-chain (C < 8) alternatives that replaced legacy PFAS. Perfluoroalkyl and polyfluoroalkyl substances have revealed inconsistencies in the toxicokinetics predicted by animal models and empirical findings in humans. To adequately assess the possible health effects of short-chain PFAS, there is a need for robust aggregated data sets on the mechanistic underpinnings and physiochemical properties of these alternatives. Acquiring relevant data on the health effects of short-chain PFAS can be achieved through high-throughput methods supported by in vitro human cell-based models. This review briefly summarizes some of the toxicity data obtained using human cells in vitro, discusses the advantages and limitations of cell-based models, and provides insights on potential solutions to challenges presented with the use of these methods for use in safety assessments.

Screening of 6000 Compounds for Uncoupling Activity: A Comparison Between a Mechanistic Biophysical Model and the Structural Alert Profiler Mitotox

Protonophoric uncoupling of phosphorylation is an important factor when assessing chemicals for their toxicity, and has recently moved into focus in pharmaceutical research with respect to the treatment of diseases such as cancer, diabetes, or obesity. Reliably identifying uncoupling activity is thus a valuable goal. To that end, we screened more than 6000 anionic compounds for in vitro uncoupling activity, using a biophysical model based on ab initio COSMO-RS input parameters with the molecular structure as the only external input. We combined these results with a model for baseline toxicity (narcosis). Our model identified more than 1250 possible uncouplers in the screening dataset, and identified possible new uncoupler classes such as thiophosphoric acids. When tested against 423 known uncouplers and 612 known inactive compounds in the dataset, the model reached a sensitivity of 83% and a specificity of 96%. In a direct comparison, it showed a similar specificity than the structural alert profiler Mitotox (97%), but much higher sensitivity than Mitotox (47%). The biophysical model thus allows for a more accurate screening for uncoupling activity than existing structural alert profilers. We propose to use our model as a complementary tool to screen large datasets for protonophoric uncoupling activity in drug development and toxicity assessment.

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.

Enzymes Present in Neutrophil Extracellular Traps May Stimulate the Fibrogenic PGF2α Pathway in the Mare Endometrium

Simple Summary

Endometrosis is a fibrotic disease in mare endometrium whose pathological mechanisms remain obscure. Prostaglandin (PG)F_2α, despite modulating reproductive physiological processes, may also provoke local pathological collagen deposition (fibrogenesis). Neutrophil extracellular traps (NETs) released during inflammation have been linked to fibrogenesis in several tissues. We have previously shown that enzymes found in NETs increase in vitro collagen production in mare endometrium. In this study, activation of PGF_2α-pathway in equine endometrial explants challenged in vitro by enzymes found in NETs is shown. Our results indicate that both endocrine microenvironment (estrous cycle phase) and healthy or pathological conditions of endometrial tissues play an important role in PGF_2α-pathway activation. In the endometrium of the follicular phase, we have observed both high production of PGF_2α and/or PGF2α receptor gene transcription under the action of enzymes found in NETs, both conditions associated with fibrogenesis in other tissues. Nevertheless, transcription of the PGF_2α receptor gene does not appear to be hormone-dependent, albeit their levels seem to be dependent on endometrial category in the mid-luteal phase. This study suggests that enzymes existing in NETs may instigate changes on PGF_2α mediators, which may become an additional mechanism of fibrogenesis in mare endometrium.

Abstract

Endometrosis, a fibrotic disease of mare endometrium, impairs uterine function. Prostaglandins (PG), despite modulating reproductive physiological functions, may also cause local pathological collagen deposition (fibrogenesis). We have previously shown that neutrophil extracellular traps (NETs) may also favor mare endometrosis. The aim of this study was to investigate the effect of enzymes present in NETs on PGF_2α-pathway activation. Kenney and Doig’s type I/IIA and IIB/III mare endometria, from follicular phase (FLP) and mid-luteal (MLP) phase, were cultured in vitro in the presence of NETs enzymes (elastase, cathepsin-G or myeloperoxidase). Production of PGF_2α (EIA) and transcription (qPCR) of its synthases (PTGS2, AKR1C3) and receptor (PTGFR) genes were evaluated. PGF_2α and PTGFR were influenced by endometrial category and estrous cycle phase. In FLP endometrium, NETs enzymes induced both high PGF_2α production and/or PTGFR transcription. In MLP type I/IIA tissues, down-regulation of PTGFR transcripts occurred. However, in MLP type IIB/III endometrium, high levels of PTGFR transcripts were induced by NETs enzymes. As PGF2α-pathway activation facilitates fibrogenesis in other tissues, PGF2α may be involved in endometrosis pathogenesis. In the mare, the endocrine microenvironment of healthy and pathological endometrium might modulate the PGF_2α pathway, as well as fibrosis outcome on endometrium challenged by NETs enzymes.

Quantification of the Uncertainties in Extrapolating From In Vitro Androgen Receptor Antagonism to In Vivo Hershberger Assay Endpoints and Adverse Reproductive Development in Male Rats

Multiple molecular initiating events exist that disrupt male sexual differentiation in utero including androgen receptor (AR) antagonism and inhibition of synthesis, and metabolism of fetal testosterone. Disruption of androgen signaling by AR antagonists in utero reduces anogenital distance (AGD) and induces malformations in F1 male rat offspring. We are developing a quantitative network of adverse outcome pathways that includes multiple molecular initiating events and key events linking anti-AR activities to permanent reproductive abnormalities. Here, our objective was to determine how accurately the EC50s for AR antagonism in vitro or ED50s for reduced tissue growth in the Hershberger assay (HA) (key events in the adverse outcome pathway) predict the ED50s for reduced AGD in male rats exposed in utero to AR antagonists. This effort included in-house data and published studies from the last 60 years on AR antagonism in vitro and in vivo effects in the HA and on AGD after in utero exposure. In total, more than 250 studies were selected and included in the analysis with data from about 60 potentially antiandrogenic chemicals. The ability to predict ED50s for key events and adverse developmental effects from the in vitro EC50s displays considerable uncertainty with R2 values for HA and AGD of < 6%. In contrast, there is considerably less uncertainty in extrapolating from the ED50s in the HA to the ED50s for AGD (R2 value of about 85%). In summary, the current results suggest that the key events measured in the HA can be extrapolated with reasonable certainty to predict the ED50s for the adverse in utero effects of antiandrogenic chemicals on male rat offspring.

Quantitative In Vitro-to-In Vivo Extrapolation: Nominal versus Freely Dissolved Concentration

Discussions are ongoing on which dose metric should be used for quantitative in vitro-to-in vivo extrapolation (QIVIVE) of in vitro bioassay data. The nominal concentration of the test chemicals is most commonly used and easily accessible, while the concentration freely dissolved in the assay medium is considered to better reflect the bioavailable concentration but is tedious to measure. The aim of this study was to elucidate how much QIVIVE results will differ when using either nominal or freely dissolved concentrations. QIVIVE_nom and QIVIVE_free ratios, that is, the ratios of plasma concentrations divided by in vitro effect concentrations, were calculated for 10 pharmaceuticals using previously published nominal and freely dissolved effect concentrations for the activation of the peroxisome proliferator-activated receptor gamma (PPARγ) and the activation of oxidative stress response. The QIVIVE_nom ratios were higher than QIVIVE_free ratios by up to a factor of 60. The risk of in vivo effects was classified as being high or low for four chemicals using the QIVIVE_nom and for three chemicals using QIVIVE_free ratios. Unambiguous classification was possible for nine chemicals by combining the QIVIVE_nom or QIVIVE_free ratios with the respective specificity ratios (SR_nom or SR_free) of the in vitro effect data, which helps to identify whether the specific effect was influenced by cytotoxicity. QIVIVE_free models should be preferred as they account for differences in bioavailability between in vitro and in vivo, but QIVIVE_nom may still be useful for screening the effects of large numbers of chemicals because it is generally more conservative. The use of SR of the in vitro effect data as a second classification factor is recommended for QIVIVE_nom and QIVIVE_free models because a clearer picture can be obtained with respect to the likelihood that a biological effect will occur and that it is not caused by nonspecific cytotoxicity.

Incorporating renal excretion via the OCT2 transporter in physiologically based kinetic modelling to predict in vivo kinetics of mepiquat in rat

The present study aimed at incorporating active renal excretion via the organic cation transporter 2 (OCT2) into a generic rat physiologically based kinetic (PBK) model using an in vitro human renal proximal tubular epithelial cell line (SA7K) and mepiquat chloride (MQ) as the model compound. The Vmax (10.5 pmol/min/mg protein) and Km (20.6 μM) of OCT2 transport of MQ were determined by concentration-dependent uptake in SA7K cells using doxepin as inhibitor. PBK model predictions incorporating these values in the PBK model were 6.7-8.4-fold different from the reported in vivo data on the blood concentration of MQ in rat. Applying an overall scaling factor that also corrects for potential differences in OCT2 activity in the SA7K cells and in vivo kidney cortex and species differences resulted in adequate predictions for in vivo kinetics of MQ in rat (2.3-3.2-fold). The results indicate that using SA7K cells to define PBK parameters for active renal OCT2 mediated excretion with adequate scaling enables incorporation of renal excretion via the OCT2 transporter in PBK modelling to predict in vivo kinetics of mepiquat in rat. This study demonstrates a proof-of-principle on how to include active renal excretion into generic PBK models.

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.

Preparation of solid dispersion systems for enhanced dissolution of poorly water soluble diacerein: In-vitro evaluation, optimization and physiologically based pharmacokinetic modeling

Diacerein (DCN), a BCS II compound, suffers from poor aqueous solubility and limited bioavailability. Solid dispersion systems (SD) of DCN were prepared by solvent evaporation, using hydrophilic polymers. In-vitro dissolution studies were performed and dissolution parameters were evaluated. I-Optimal factorial design was employed to study the effect of formulation variables (drug:polymer ratio and polymer type) on the measured responses including; drug content (DC) (%), dissolution efficiency at 15 min (DE _{(15 min)}%) and 60 min (DE _{(60 min)}%) and mean dissolution time (MDT) (min). The optimized SD was selected, prepared and evaluated, allowing 10.83 and 3.42 fold increase in DE _{(15 min)}%, DE _{(60 min)}%, respectively and 6.07 decrease in MDT, compared to plain drug. DSC, XRD analysis and SEM micrographs confirmed complete amorphization of DCN within the optimized SD. Physiologically based pharmacokinetic (PBPK) modeling was employed to predict PK parameters of DCN in middle aged healthy adults and geriatrics. Simcyp^® software established in-vivo plasma concentration time curves of the optimized SD, compared to plain DCN. Relative bioavailability of the optimized SD compared to plain drug was 229.52% and 262.02% in healthy adults and geriatrics, respectively. Our study reports the utility of PBPK modeling for formulation development of BCS II APIs, via predicting their oral bio-performance.

Myeloperoxidase Inhibition Decreases the Expression of Collagen and Metallopeptidase in Mare Endometria under In Vitro Conditions

Neutrophils can originate neutrophil extracellular traps (NETs). Myeloperoxidase (MPO) is a peroxidase found in NETs associated to equine endometrosis and can be inhibited by 4-aminobenzoic acid hydrazide (ABAH). Metallopeptidases (MMPs) participate in extracellular matrix stability and fibrosis development. The objectives of this in vitro work were to investigate, in explants of mare's endometrium, (i) the ABAH capacity to inhibit MPO-induced collagen type I (COL1) expression; and (ii) the action of MPO and ABAH on the expression and gelatinolytic activity of MMP-2/-9. Explants retrieved from the endometrium of mares in follicular or mid-luteal phases were treated with MPO, ABAH, or their combination, for 24 or 48 h. The qPCR analysis measured the transcription of COL1A2, MMP2, and MMP9. Western blot and zymography were performed to evaluate COL1 protein relative abundance and gelatinolytic activity of MMP-2/-9, respectively. Myeloperoxidase elevated COL1 relative protein abundance at both treatment times in follicular phase (p < 0.05). The capacity of ABAH to inhibit MPO-induced COL1 was detected in follicular phase at 48 h (p < 0.05). The gelatinolytic activity of activated MMP-2 augmented in mid-luteal phase at 24 h after MPO treatment, but it was reduced with MPO+ABAH treatment. The activity of MMP-9 active form augmented in MPO-treated explants. However, this effect was inhibited by ABAH in the follicular phase at 48 h (p < 0.05). By inhibiting the pro-fibrotic effects of MPO, it might be possible to reduce the development of endometrosis. Metallopeptidase-2 might be involved in an acute response to MPO in the mid-luteal phase, while MMP-9 might be implicated in a prolonged exposition to MPO in the follicular phase.

Novel testing strategy for prediction of rat biliary excretion of intravenously administered estradiol-17β glucuronide

The aim of the present study was to develop a generic rat physiologically based kinetic (PBK) model that includes a novel testing strategy where active biliary excretion is incorporated using estradiol-17β glucuronide (E217βG) as the model substance. A major challenge was the definition of the scaling factor for the in vitro to in vivo conversion of the PBK-model parameter Vmax. In vitro values for the Vmax and Km for transport of E217βG were found in the literature in four different studies based on experiments with primary rat hepatocytes. The required scaling factor was defined based on fitting the PBK model-based predicted values to reported experimental data on E217βG blood levels and cumulative biliary E217βG excretion. This resulted in a scaling factor of 129 mg protein/g liver. With this scaling factor the PBK model predicted the in vivo data for blood and cumulative biliary E217βG levels with on average of less than 1.8-fold deviation. The study provides a proof of principle on how biliary excretion can be included in a generic PBK model using primary hepatocytes to define the kinetic parameters that describe the biliary excretion.

Identification of potential therapeutic target of naringenin in breast cancer stem cells inhibition by bioinformatics and in vitro studies

Cancer therapy is a strategic measure in inhibiting breast cancer stem cell (BCSC) pathways. Naringenin, a citrus flavonoid, was found to increase breast cancer cells' sensitivity to chemotherapeutic agents. Bioinformatics study and 3D tumorsphere in vitro modeling in breast cancer (mammosphere) were used in this study, which aims to explore the potential therapeutic targets of naringenin (PTTNs) in inhibiting BCSCs. Bioinformatic analyses identified direct target proteins (DTPs), indirect target proteins (ITPs), naringenin-mediated proteins (NMPs), BCSC regulatory genes, and PTTNs. The PTTNs were further analyzed for gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction (PPI) networks, and hub protein selection. Mammospheres were cultured in serum-free media. The effects of naringenin were measured by MTT-based cytotoxicity, mammosphere forming potential (MFP), colony formation, scratch wound-healing assay, and flow cytometry-based cell cycle analyses and apoptosis assays. Gene expression analysis was performed using real-time quantitative polymerase chain reaction (q-RT PCR). Bioinformatics analysis revealed p53 and estrogen receptor alpha (ERα) as PTTNs, and KEGG pathway enrichment analysis revealed that TGF-ß and Wnt/ß-catenin pathways are regulated by PTTNs. Naringenin demonstrated cytotoxicity and inhibited mammosphere and colony formation, migration, and epithelial to mesenchymal transition in the mammosphere. The mRNA of tumor suppressors P53 and ERα were downregulated in the mammosphere, but were significantly upregulated upon naringenin treatment. By modulating the P53 and ERα mRNA, naringenin has the potential of inhibiting BCSCs. Further studies on the molecular mechanism and formulation of naringenin in BCSCs would be beneficial for its development as a BCSC-targeting drug.

In vitro-in silico-based probabilistic risk assessment of combined exposure to bisphenol A and its analogues by integrating ToxCast high-throughput in vitro assays with in vitro to in vivo extrapolation (IVIVE) via physiologically based pharmacokinetic (PBPK) modeling

Combined risk assessment of endocrine effects of bisphenol A (BPA) and its analogues, such as bisphenols S, F, and AF (BPS, BPF, and BPAF), is challenging due to lack of related common toxicity metrics. This study conducted a population-based in vitro-to-in vivo extrapolation using physiologically based pharmacokinetic (PBPK) models coupled with Monte Carlo simulations to convert ToxCast in vitro estrogen receptor (ER) assays to human equivalent doses (HEDs). The ER pathway-based HEDs were compared with HEDs from animal studies and used to assess the combined risks for different populations across different countries/regions in a probabilistic manner. The estimated ER pathway-based HEDs for the four bisphenols (BPs) matched the animal-derived HEDs. The HEDs for the ER gene transcription (the common biological process target among BPs) were 0.40 (2.5th-97.5th percentiles: 0.06-5.42), 4.43 (0.69-53.84), 3.30 (0.51-626.57), and 1.12 (0.16-9.73) mg/kg/day for BPA, BPS, BPF, and BPAF, respectively. Results suggest a potentially moderate concern for combined risks of activating the ER pathway for toddlers and adults with high dietary exposures. This study presents in vitro-based credible HEDs for the four BPs and represents an advancement in the application of in vitro-in silico-based alternative approaches in human health risk assessment.

Quantitative in Vitro to in Vivo Extrapolation (QIVIVE) for Predicting Reduced Anogenital Distance Produced by Anti-Androgenic Pesticides in a Rodent Model for Male Reproductive Disorders

BACKGROUND

Many pesticides can antagonize the androgen receptor (AR) or inhibit androgen synthesis in vitro but their potential to cause reproductive toxicity related to disruption of androgen action during fetal life is difficult to predict. Currently no approaches for using in vitro data to anticipate such in vivo effects exist. Prioritization schemes that limit unnecessary in vivo testing are urgently needed.

OBJECTIVES

The aim was to develop a quantitative in vitro to in vivo extrapolation (QIVIVE) approach for predicting in vivo anti-androgenicity arising from gestational exposures and manifesting as a shortened anogenital distance (AGD) in male rats.

METHODS

We built a physiologically based pharmacokinetic (PBK) model to simulate concentrations of chemicals in the fetus resulting from maternal dosing. The predicted fetal levels were compared with analytically determined concentrations, and these were judged against in vitro active concentrations for AR antagonism and androgen synthesis suppression.

RESULTS

We first evaluated our model by using in vitro and in vivo anti-androgenic data for procymidone, vinclozolin, and linuron. Our PBK model described the measured fetal concentrations of parent compounds and metabolites quite accurately (within a factor of five). We applied the model to nine current-use pesticides, all with in vitro evidence for anti-androgenicity but missing in vivo data. Seven pesticides (fludioxonil, cyprodinil, dimethomorph, imazalil, quinoxyfen, fenhexamid, o -phenylphenol) were predicted to produce a shortened AGD in male pups, whereas two (λ -cyhalothrin , pyrimethanil) were anticipated to be inactive. We tested these expectations for fludioxonil, cyprodinil, and dimethomorph and observed shortened AGD in male pups after gestational exposure. The measured fetal concentrations agreed well with PBK-modeled predictions.

DISCUSSION

Our QIVIVE model newly identified fludioxonil, cyprodinil, and dimethomorph as in vivo anti-androgens. With the examples investigated, our approach shows great promise for predicting in vivo anti-androgenicity (i.e., AGD shortening) for chemicals with in vitro activity and for minimizing unnecessary in vivo testing. https://doi.org/10.1289/EHP6774.

Multicellular Systems to Translate Somatic Cell Genome Editors to Humans

As genome editors move into clinical trials, there is a need to establish ex vivo multicellular systems to rapidly assess and predict toxic effects of genome editors in physiologically relevant human models. Advancements in organoid and organs-on-chip technologies offer the possibility to create multicellular systems that replicate the cellular composition and metabolic function of native tissues. Some multicellular systems have been validated in multiple applications for drug discovery and could be easily adapted to test genome editors; other models, especially those of the adaptive immune system, will require validation before being used as benchmarks for testing genome editors. Likewise, protocols to assess immunogenicity, to detect off-target effects, and to predict ex vivo to in vivo translation will need to be established and validated. This review will discuss key aspects to consider when designing, building, and/or adopting in vitro human multicellular systems for testing genome editors.

Assessing Toxicity with Human Cell-Based In Vitro Methods

In toxicology, there is a strong push towards replacing animal experiments with alternative methods, which include cell-based in vitro methods for the assessment of adverse health effects in humans. High-throughput methods are of central interest due to the large and steadily growing numbers of compounds that require assessment. Tremendous progress has been made during the last decade in developing and applying such methods. Innovative technologies for addressing complex biological interactions include induced pluripotent stem cell- and organoid-based approaches, organotypic coculture systems, and microfluidic 'multiorgan' chips. Combining in vitro methods with bioinformatics and in silico modeling generates new powerful tools for toxicity assessment, and the rapid progress in the field is expected to continue.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part I: Cattle and swine

Physiologically based pharmacokinetic (PBPK) models for chemicals in food animals are a useful tool in estimating chemical tissue residues and withdrawal intervals. Physiological parameters such as organ weights and blood flows are an important component of a PBPK model. The objective of this study was to compile PBPK‐related physiological parameter data in food animals, including cattle and swine. Comprehensive literature searches were performed in PubMed, Google Scholar, ScienceDirect, and ProQuest. Relevant literature was reviewed and tables of relevant parameters such as relative organ weights (% of body weight) and relative blood flows (% of cardiac output) were compiled for different production classes of cattle and swine. The mean and standard deviation of each parameter were calculated to characterize their variability and uncertainty and to allow investigators to conduct population PBPK analysis via Monte Carlo simulations. Regression equations using weight or age were created for parameters having sufficient data. These compiled data provide a comprehensive physiological parameter database for developing PBPK models of chemicals in cattle and swine to support animal‐derived food safety assessment. This work also provides a basis to compile data in other food animal species, including goats, sheep, chickens, and turkeys.

Potential of ToxCast Data in the Safety Assessment of Food Chemicals

Tox21 and ToxCast are high-throughput in vitro screening programs coordinated by the U.S. National Toxicology Program and the U.S. Environmental Protection Agency, respectively, with the goal of forecasting biological effects in vivo based on bioactivity profiling. The present study investigated whether mechanistic insights in the biological targets of food-relevant chemicals can be obtained from ToxCast results when the chemicals are grouped according to structural similarity. Starting from the 556 direct additives that have been identified in the ToxCast database by Karmaus et al. [Karmaus, A. L., Trautman, T. D., Krishan, M., Filer, D. L., and Fix, L. A. (2017). Curation of food-relevant chemicals in ToxCast. Food Chem. Toxicol. 103, 174-182.], the results showed that, despite the limited number of assays in which the chemical groups have been tested, sufficient results are available within so-called "DNA binding" and "nuclear receptor" target families to profile the biological activities of the defined chemical groups for these targets. The most obvious activity identified was the estrogen receptor-mediated actions of the chemical group containing parabens and structurally related gallates, as well the chemical group containing genistein and daidzein (the latter 2 being particularly active toward estrogen receptor β as a potential health benefit). These group effects, as well as the biological activities of other chemical groups, were evaluated in a series of case studies. Overall, the results of the present study suggest that high-throughput screening data could add to the evidence considered for regulatory risk assessment of food chemicals and to the evaluation of desirable effects of nutrients and phytonutrients. The data will be particularly useful for providing mechanistic information and to fill data gaps with read-across.

Liver toxicity of anthraquinones: A combined in vitro cytotoxicity and in silico reverse dosimetry evaluation

Anthraquinones are found in a variety of consumer products such as dietary supplements, traditional Chinese medicines, and drugs. Along with their widespread use, potential safety concerns have emerged, especially liver toxicity. Therefore, there is a need to conduct rapid and inexpensive safety assessment for anthraquinones due to a lack of animal and human toxicological data. Here, a combined in vitro cytotoxicity and in silico reverse dosimetry approach was adopted to consider the potential human liver toxicity of 16 anthraquinones and derivatives. First, cytotoxicity (EC₅₀) in two human liver cell lines (HepG2/C3A and HuH-7) was measured under two conditions (single and repeated dosing, 72 h). Second, toxic doses (D_tox) required to yield plasma steady-state concentrations (C_ss) equal to in vitro EC₅₀ values were predicted by reverse dosimetry simulation using a PBPK model. Finally, D_tox was compared to literature-derived estimated daily intake (EDI) of anthraquinones to assess safety. Among the 16 anthraquinones, rhein was identified as a potential hepatotoxicant due to a combination of cytotoxicity, plasma concentration, and daily intake level. These in vitro and in silico findings provide preliminary data and guidance for further animal and clinical studies to confirm liver toxicity of anthraquinones.

A Conflicted Tale of Two Novel AR Antagonists In Vitro and In Vivo: Pyrifluquinazon Versus Bisphenol C

Chemicals that disrupt androgen receptor (AR) function in utero induce a cascade of adverse effects in male rats including reduced anogenital distance, retained nipples, and reproductive tract malformations. The objective of this study was to compare the in vitro and in utero activities of two novel AR antagonists, bisphenol C (BPC) and pyrifluquinazon (PFQ). In vitro, BPC was as potent an AR antagonist as hydroxyflutamide. Furthermore, BPC inhibited fetal testis testosterone production and testis gene expression ex vivo. However, when BPC was administered at 100 and 200 mg/kg/d in utero, the reproductive tract of the male offspring was minimally affected. None of the males displayed reproductive malformations. For comparison, in utero administration of flutamide has been shown to induce malformations in 100% of males at 6 mg/kg/d. In vitro, PFQ was several orders of magnitude less potent than BPC, vinclozolin, or procymidone. However, in utero administration of 12.5, 25, 50, and 100 mg PFQ/kg/d on GD 14-18 induced antiandrogenic effects at all dosage levels and 91% of the males displayed reproductive malformation in the high dose group. Overall, BPC was ∼380-fold more potent than PFQ in vitro, whereas PFQ was far more potent than BPC in utero. Incorporating toxicokinetic and toxicodynamic data into in vitro to in vivo extrapolations would reduce the discordance between the in vitro and in utero effects of PFQ and BPC and combining in vitro results with a short-term Hershberger assay would reduce the uncertainty in predicting the in utero effects of antiandrogenic chemicals.