Incorporation of in vitro metabolism data and physiologically based pharmacokinetic modeling in a risk assessment for chloroprene

Overview of in vitro-in vivo extrapolation approaches for the risk assessment of nanomaterial toxicity

Nanomaterials are increasingly used in many applications due to their enhanced properties. To ensure their safety for humans and the environment, nanomaterials need to be evaluated for their potential risk. The risk assessment analysis on the nanomaterials based on animal or in vivo studies is accompanied by several concerns, including animal welfare, time and cost needed for the studies. Therefore, incorporating in vitro studies in the risk assessment process is increasingly considered. To be able to analyze the potential risk of nanomaterial to human health, there are factors to take into account. Utilizing in vitro data in the risk assessment analysis requires methods that can be used to translate in vitro data to predict in vivo phenomena (in vitro-in vivo extrapolation (IVIVE) methods) to be incorporated, to obtain a more accurate result. Apart from the experiments and species conversion (for example, translation between the cell culture, animal and human), the challenge also includes the unique properties of nanomaterials that might cause them to behave differently compared to the same materials in a bulk form. This overview presents the IVIVE techniques that are developed to extrapolate pharmacokinetics data or doses. A brief example of the IVIVE methods for chemicals is provided, followed by a more detailed summary of available IVIVE methods applied to nanomaterials. The IVIVE techniques discussed include the comparison between in vitro and in vivo studies, methods to rene the dose metric or the in vitro models, allometric approach, mechanistic modeling, Multiple-Path Particle Dosimetry (MPPD), methods using organ burden data and also approaches that are currently being developed.

Physiologically based toxicokinetic modelling of Tri(2-chloroethyl) phosphate (TCEP) in mice accounting for multiple exposure routes

Exposure routes are important for health risk assessment of chemical risks. The application of physiologically based toxicokinetic (PBTK) models to predict concentrations in vivo can determine the effects of harmful substances and tissue accumulation on the premise of saving experimental costs. In this study, Tri(2-chloroethyl) phosphate (TCEP), an organophosphate ester (OPE), was used as an example to study the PBTK model of mice exposed to different exposure doses by multiple routes. Different routes of exposure (gavage and intradermal injection) can cause differences in the concentration of chemicals in the organs. TCEP that enters the body through the mouth is mainly concentrated in the gastrointestinal tract and liver. However, the concentrations of chemicals that enter the skin into the mice are higher in skin, rest of body, and blood. In addition, TCEP was absorbed and accumulated very rapidly in mice, within half an hour after a single exposure. We have successfully established a mouse PBTK model of the TCEP accounting for multiple exposure Routes and obtained a series of kinetic parameters. The model includes blood, liver, kidney, stomach, intestine, skin, and rest of body compartments. Oral and dermal exposure route was considered for PBTK model. The PBTK model established in this study has a good predictive ability. More than 70% of the predicted values deviated from the measured values by less than 5-fold. In addition, we extrapolated the model to humans. A human PBTK model is built. We performed a health risk assessment for world populations based on human PBTK model. The risk of TCEP in dust is greater through mouth than through skin. The risk of TCEP in food of Chinese population is greater than dust.

Using available in vitro metabolite identification and time course kinetics for β-chloroprene and its metabolite, (1-chloroethenyl) oxirane, to include reactive oxidative metabolites and glutathione depletion in a PBPK model for β-chloroprene

Introduction: ß-chloroprene (2-chloro-1,3-butadiene; CP) causes lung tumors after inhalation exposures in rats and mice. Mice develop these tumors at lower exposures than rats. In rats CP exposures cause depletion of lung glutathione (GSH). Methods: PBPK models developed to relate the appearance of mouse lung tumors with rates of CP metabolism to reactive metabolites or total amounts metabolized during exposures have been expanded to include production of reactive metabolites from CP. The extended PBPK model describes both the unstable oxirane metabolite, 2-CEO, and metabolism of the more stable oxirane, 1-CEO, to reactive metabolites via microsomal oxidation to a diepoxide, and linked production of these metabolites to a PK model predicting GSH depletion with increasing CP exposure. Key information required to develop the model were available from literature studies identifying: 1) microsomal metabolites of CP, and 2) in vitro rates of clearance of CP and 1-CEO from active microsomal preparations from mice, rats, hamsters and humans. Results: Model simulation of concentration dependence of disproportionate increases in reactive metabolite concentrations as exposures increases and decreases in tissue GSH are consistent with the dose-dependence of tumor formation. At the middle bioassay concentrations with a lung tumor incidence, the predicted tissue GSH is less than 50% background. These simulations of reduction in GSH are also consistent with the gene expression results showing the most sensitive pathways are Nrf2-regulation of oxidative stress and GSH metabolism. Discussion: The PBPK model is used to correlate predicted tissue exposure to reactive metabolites with toxicity and carcinogenicity of CP.

New Approach Methodologies for the Endocrine Activity Toolbox: Environmental Assessment for Fish and Amphibians

Multiple in vivo test guidelines focusing on the estrogen, androgen, thyroid, and steroidogenesis pathways have been developed and validated for mammals, amphibians, or fish. However, these tests are resource-intensive and often use a large number of laboratory animals. Developing alternatives for in vivo tests is consistent with the replacement, reduction, and refinement principles for animal welfare considerations, which are supported by increasing mandates to move toward an "animal-free" testing paradigm worldwide. New approach methodologies (NAMs) hold great promise to identify molecular, cellular, and tissue changes that can be used to predict effects reliably and more efficiently at the individual level (and potentially on populations) while reducing the number of animals used in (eco)toxicological testing for endocrine disruption. In a collaborative effort, experts from government, academia, and industry met in 2020 to discuss the current challenges of testing for endocrine activity assessment for fish and amphibians. Continuing this cross-sector initiative, our review focuses on the current state of the science regarding the use of NAMs to identify chemical-induced endocrine effects. The present study highlights the challenges of using NAMs for safety assessment and what work is needed to reduce their uncertainties and increase their acceptance in regulatory processes. We have reviewed the current NAMs available for endocrine activity assessment including in silico, in vitro, and eleutheroembryo models. New approach methodologies can be integrated as part of a weight-of-evidence approach for hazard or risk assessment using the adverse outcome pathway framework. The development and utilization of NAMs not only allows for replacement, reduction, and refinement of animal testing but can also provide robust and fit-for-purpose methods to identify chemicals acting via endocrine mechanisms. Environ Toxicol Chem 2023;42:757-777. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Addressing systemic problems with exposure assessments to protect the public's health

BACKGROUND

Understanding, characterizing, and quantifying human exposures to environmental chemicals is critical to protect public health. Exposure assessments are key to determining risks to the general population and for specific subpopulations given that exposures differ between groups. Exposure data are also important for understanding where interventions, including public policies, should be targeted and the extent to which interventions have been successful. In this review, we aim to show how inadequacies in exposure assessments conducted by polluting industries or regulatory agencies have led to downplaying or disregarding exposure concerns raised by communities; that underestimates of exposure can lead regulatory agencies to conclude that unacceptable risks are, instead, acceptable, allowing pollutants to go unregulated; and that researchers, risk assessors, and policy makers need to better understand the issues that have affected exposure assessments and how appropriate use of exposure data can contribute to health-protective decisions.

METHODS

We describe current approaches used by regulatory agencies to estimate human exposures to environmental chemicals, including approaches to address limitations in exposure data. We then illustrate how some exposure assessments have been used to reach flawed conclusions about environmental chemicals and make recommendations for improvements.

RESULTS

Exposure data are important for communities, public health advocates, scientists, policy makers, and other groups to understand the extent of environmental exposures in diverse populations. We identify four areas where exposure assessments need to be improved due to systemic sources of error or uncertainty in exposure assessments and illustrate these areas with examples. These include: (1) an inability of regulatory agencies to keep pace with the increasing number of chemicals registered for use or assess their exposures, as well as complications added by use of 'confidential business information' which reduce available exposure data; (2) the failure to keep assessments up-to-date; (3) how inadequate assumptions about human behaviors and co-exposures contribute to underestimates of exposure; and (4) that insufficient models of toxicokinetics similarly affect exposure estimates.

CONCLUSION

We identified key issues that impact capacity to conduct scientifically robust exposure assessments. These issues must be addressed with scientific or policy approaches to improve estimates of exposure and protect public health.

PBPK modeling to evaluate maximum tolerated doses: A case study with 3-chloroallyl alcohol

Introduction: A physiologically based pharmacokinetic (PBPK) model for 3-chloroallyl alcohol (3-CAA) was developed and used to evaluate the design of assays for the in vivo genotoxicity of 3-CAA. Methods: Model development was supported by read across from a published PBPK model for ethanol. Read across was motivated by the expectation that 3-CAA, which like ethanol is a primary alcohol, is metabolized largely by hepatic alcohol dehydrogenases. The PBPK model was used to evaluate how two metrics of tissue dosimetry, maximum blood concentration (Cmax; mg/L) and area under the curve (AUC; mg-hr/L) vary with dose of 3-CAA and with dose route (oral gavage, drinking water). Results: The model predicted that oral gavage results in a 6-fold higher Cmax than the same dose administered in drinking water, but in similar AUCs. Predicted Cmax provided the best correlation with severe toxicity (e.g., lethality) from 3-CAA, consistent with the production of a reactive metabolite. Therefore, drinking water administration can achieve higher sustained concentration without severe toxicity in vivo. Discussion: This evaluation is significant because cytotoxicity is a potential confounder of mutagenicity testing. The PBPK model can be used to ensure that studies meet OECD and USEPA test guidelines and that the highest dose used is not associated with severe toxicity. In addition, PBPK modeling provides assurance of target tissue (e.g., bone marrow) exposure even in the absence of laboratory data, by defining the relationship between applied dose and target tissue dose based on accepted principles of pharmacokinetics, relevant physiology and biochemistry of the dosed animals, and chemical-specific information.

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.

Using quantitative modeling tools to assess pharmacokinetic bias in epidemiological studies showing associations between biomarkers and health outcomes at low exposures

Biomarkers of exposure can be measured at lower and lower levels due to advances in analytical chemistry. Using these sensitive methods, some epidemiology studies report associations between biomarkers and health outcomes at biomarker levels much below those associated with effects in animal studies. While some of these low exposure associations may arise from increased sensitivity of humans compared with animals or from species-specific responses, toxicology studies with drugs, commodity chemicals and consumer products have not generally indicated significantly greater sensitivity of humans compared with test animals for most health outcomes. In some cases, these associations may be indicative of pharmacokinetic (PK) bias, i.e., a situation where a confounding factor or the health outcome itself alters pharmacokinetic processes affecting biomarker levels. Quantitative assessment of PK bias combines PK modeling and statistical methods describing outcomes across large numbers of individuals in simulated populations. Here, we first provide background on the types of PK models that can be used for assessing biomarker levels in human population and then outline a process for considering PK bias in studies intended to assess associations between biomarkers and health outcomes at low levels of exposure. After providing this background, we work through published examples where these PK methods have been applied with several chemicals/chemical classes - polychlorinated biphenyls (PCBs), perfluoroalkyl substances (PFAS), polybrominated biphenyl ethers (PBDE) and phthalates - to assess the possibility of PK bias. Studies of the health effects of low levels of exposure will be improved by developing some confidence that PK bias did not play significant roles in the observed associations.

Application of physiologically based pharmacokinetic models to promote the development of veterinary drugs with high efficacy and safety

Physiologically based pharmacokinetic (PBPK) models have become important tools for the development of novel human drugs. Food-producing animals and pets comprise an important part of human life, and the development of veterinary drugs (VDs) has greatly impacted human health. Owing to increased affordability of and demand for drug development, VD manufacturing companies should have more PBPK models required to reduce drug production costs. So far, little attention has been paid on applying PBPK models for the development of VDs. This review begins with the development processes of VDs; then summarizes case studies of PBPK models in human or VD development; and analyzes the application, potential, and advantages of PBPK in VD development, including candidate screening, formulation optimization, food effects, target-species safety, and dosing optimization. Then, the challenges of applying the PBPK model to VD development are discussed. Finally, future opportunities of PBPK models in designing dosing regimens for intracellular pathogenic infections and for efficient oral absorption of VDs are further forecasted. This review will be relevant to readers who are interested in using a PBPK model to develop new VDs.

Extended Analysis and Evidence Integration of Chloroprene as a Human Carcinogen

β-Chloroprene is used in the production of polychloroprene, a synthetic rubber. In 2010, Environmental Protection Agency (EPA) published the Integrated Risk Information System "Toxicological Review of Chloroprene," concluding that chloroprene was "likely to be carcinogenic to humans." This was based on findings from a 1998 National Toxicology Program (NTP) study showing multiple tumors within and across animal species; results from occupational epidemiological studies; a proposed mutagenic mode of action; and structural similarities with 1,3-butadiene and vinyl chloride. Using mouse data from the NTP study and assuming a mutagenic mode of action, EPA calculated an inhalation unit risk (IUR) for chloroprene of 5 × 10^-4 per µg/m³ . This is among the highest IURs for chemicals classified by IARC or EPA as known or probable human carcinogens and orders of magnitude higher than the IURs for carcinogens such as vinyl chloride, benzene, and 1,3-butadiene. Due to differences in pharmacokinetics, mice appear to be uniquely responsive to chloroprene exposure compared to other animals, including humans, which is consistent with the lack of evidence of carcinogenicity in robust occupational epidemiological studies. We evaluated and integrated all lines of evidence for chloroprene carcinogenicity to assess whether the 2010 EPA IUR could be scientifically substantiated. Due to clear interspecies differences in carcinogenic response to chloroprene, we applied a physiologically based pharmacokinetic model for chloroprene to calculate a species-specific internal dose (amount metabolized/gram of lung tissue) and derived an IUR that is over 100-fold lower than the 2010 EPA IUR. Therefore, we recommend that EPA's IUR be updated.