Evaluation of a rapid, generic human gestational dose model

The environmental neuroactive chemicals list of prioritized substances for human biomonitoring and neurotoxicity testing: A database and high-throughput toxicokinetics approach

There is a diversity of chemicals to which humans are potentially exposed. Few of these chemicals have linked human biomonitoring data, and most have very limited neurotoxicity testing. Of particular concern are environmental exposures impacting children, who constitute a population of heightened susceptibility due to rapid neural growth and plasticity, yet lack biomonitoring data compared to other age/population subgroups. This study set out to develop a prioritized list of neuroactive substances, titled the Environmental NeuRoactIve CHemicals (ENRICH) list, to be used as a defined screening library in the evaluation of human biological samples, with emphasis on early childhood-relevant environmental exposures. In silico database mining approaches were used to prioritize chemicals based upon likelihood of neuroactivity, human exposure, and feasible detection in biological samples. Evidence of neuroactivity was compiled across in vitro high-throughput screening, animal testing, and/or human epidemiological findings. Chemicals were considered for their likelihood of human exposure and detection presence in biological samples (including metabolites), with additional evidence indicating presence within child-relevant products. The resulting list of 1827 chemicals were ranked using a Chemical Prioritization Index. Manual inclusion/exclusion criteria were employed for the top-ranking chemical candidates to ensure that chemicals were within the study's scope (i.e., environmentally relevant) and, for the purposes of biomonitoring, had properties amenable to mass spectrometry methods. These elements were combined to produce the ENRICH list of 250 top-ranking chemicals, spanning pesticides and those used in home maintenance, personal care, cleaning products, vehicles, arts and crafts, and consumer electronics, among other sources. Chemicals were additionally evaluated for high-throughput toxicokinetics to predict how much of a chemical and/or its metabolite(s) may reach urine, as an example biological matrix for practical use in biomonitoring efforts. This novel study couples databases and in silico-based predictions to prioritize chemicals in the environment with potential neurological impacts for future study.

Developmental neurotoxicity evaluation of acrylamide based on in vitro to in vivo extrapolation by pregnancy PBTK modelling

Acrylamide (ACR) is a known neurotoxicant that can pass the placenta and has been detected in breast milk. Some in vivo and in vitro studies indicate that ACR exposure might lead to developmental neurotoxicity (DNT). Here, we have developed a physiologically-based toxicokinetic model for a pregnant human population using PK-Sim. We performed an in vitro to in vivo extrapolation (IVIVE) of data collected from human neuroblastoma SH-SY5Y cells exposed during differentiation to ACR. The developed PBTK model was successfully evaluated and predicted fetal plasma concentrations in the low nM range after exposing the model to an estimated average daily intake for pregnant women. The IVIVE showed that low concentrations of ACR (fM-nM) that induced attenuated differentiation of the SH-SY5Y neuronal cell model, were relevant for human exposure to ACR from oral intake. However, doses estimated in the IVIVE from concentrations in the µM range, were found to be unrealistic by exposure through food intake for an average daily intake. However, in case of exposure due to environmental pollution or occupational exposure, these concentrations may be reached in fetal plasma. The findings in this study raise the concern regarding ACR exposure during pregnancy as well as the relevance of testing concentrations in vitro that are several orders of magnitude higher than the predicted fetal plasma concentrations.

Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies

The merging of physiology and toxicokinetics, or pharmacokinetics, with computational modeling to characterize dosimetry has led to major advances for both the chemical and pharmaceutical research arenas. Driven by the mutual need to estimate internal exposures where in vivo data generation was simply not possible, the application of toxicokinetic modeling has grown exponentially in the past 30 years. In toxicology the need has been the derivation of quantitative estimates of toxicokinetic and toxicodynamic variability to evaluate the suitability of the tenfold uncertainty factor employed in risk assessment decision-making. Consideration of a host of physiologic, ontogenetic, genetic, and exposure factors are all required for comprehensive characterization. Fortunately, the underlying framework of physiologically based toxicokinetic models can accommodate these inputs, in addition to being amenable to capturing time-varying dynamics. Meanwhile, international interest in advancing new approach methodologies has fueled the generation of in vitro toxicity and toxicokinetic data that can be applied in in vitro-in vivo extrapolation approaches to provide human-specific risk-based information for historically data-poor chemicals. This review will provide a brief introduction to the structure and evolution of toxicokinetic and physiologically based toxicokinetic models as they advanced to incorporate variability and a wide range of complex exposure scenarios. This will be followed by a state of the science update describing current and emerging experimental and modeling strategies for population and life-stage variability, including the increasing application of in vitro-in vivo extrapolation with physiologically based toxicokinetic models in pharmaceutical and chemical safety research. The review will conclude with case study examples demonstrating novel applications of physiologically based toxicokinetic modeling and an update on its applications for regulatory decision-making. Physiologically based toxicokinetic modeling provides a sound framework for variability evaluation in chemical risk assessment.

Investigating open access new approach methods (NAM) to assess biological points of departure: A case study with 4 neurotoxic pesticides

Open access new approach methods (NAM) in the US EPA ToxCast program and NTP Integrated Chemical Environment (ICE) were used to investigate activities of four neurotoxic pesticides: endosulfan, fipronil, propyzamide and carbaryl. Concordance of in vivo regulatory points of departure (POD) adjusted for interspecies extrapolation (AdjPOD) to modelled human Administered Equivalent Dose (AEDHuman) was assessed using 3-compartment or Adult/Fetal PBTK in vitro to in vivo extrapolation. Model inputs were from Tier 1 (High throughput transcriptomics: HTTr, high throughput phenotypic profiling: HTPP) and Tier 2 (single target: ToxCast) assays. HTTr identified gene expression signatures associated with potential neurotoxicity for endosulfan, propyzamide and carbaryl in non-neuronal MCF-7 and HepaRG cells. The HTPP assay in U-2 OS cells detected potent effects on DNA endpoints for endosulfan and carbaryl, and mitochondria with fipronil (propyzamide was inactive). The most potent ToxCast assays were concordant with specific components of each chemical mode of action (MOA). Predictive adult IVIVE models produced fold differences (FD) < 10 between the AEDHuman and the measured in vivo AdjPOD. The 3-compartment model was concordant (i.e., smallest FD) for endosulfan, fipronil and carbaryl, and PBTK was concordant for propyzamide. The most potent AEDHuman predictions for each chemical showed HTTr, HTPP and ToxCast were mainly concordant with in vivo AdjPODs but assays were less concordant with MOAs. This was likely due to the cell types used for testing and/or lack of metabolic capabilities and pathways available in vivo. The Fetal PBTK model had larger FDs than adult models and was less predictive overall.

From Cohort to Cohort: A Similar Mixture Approach (SMACH) to Evaluate Exposures to a Mixture Leading to Thyroid-Mediated Neurodevelopmental Effects Using NHANES Data

Prenatal exposure to a mixture (MIX N) of eight endocrine-disrupting chemicals has been associated with language delay in children in a Swedish pregnancy cohort. A novel approach was proposed linking this epidemiological association with experimental evidence, where the effect of MIX N on thyroid hormone signaling was assessed using the Xenopus eleuthero-embryonic thyroid assay (XETA OECD TG248). From this experimental data, a point of departure (PoD) was derived based on OECD guidance. Our aim in the current study was to use updated toxicokinetic models to compare exposures of women of reproductive age in the US population to MIX N using a Similar Mixture Approach (SMACH). Based on our findings, 66% of women of reproductive age in the US (roughly 38 million women) had exposures sufficiently similar to MIX N. For this subset, a Similar Mixture Risk Index (SMRI_HI) was calculated comparing their exposures to the PoD. Women with SMRI_HI > 1 represent 1.1 million women of reproductive age. Older women, Mexican American and other/multi race women were less likely to have high SMRI_HI values compared to Non-Hispanic White women. These findings indicate that a reference mixture of chemicals identified in a Swedish cohort-and tested in an experimental model for establishment of (PoDs)-is also of health relevance in a US population.