A science-based agenda for health-protective chemical assessments and decisions: overview and consensus statement.

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.

Current practice and recommendations for advancing how human variability and susceptibility are considered in chemical risk assessment.

A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors.This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs.Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors.We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

Options for basing Dietary Reference Intakes (DRIs) on chronic disease endpoints: report from a joint US-/Canadian-sponsored working group.

Dietary Reference Intakes (DRIs) are used in Canada and the United States in planning and assessing diets of apparently healthy individuals and population groups. The approaches used to establish DRIs on the basis of classical nutrient deficiencies and/or toxicities have worked well. However, it has proved to be more challenging to base DRI values on chronic disease endpoints; deviations from the traditional framework were often required, and in some cases, DRI values were not established for intakes that affected chronic disease outcomes despite evidence that supported a relation. The increasing proportions of elderly citizens, the growing prevalence of chronic diseases, and the persistently high prevalence of overweight and obesity, which predispose to chronic disease, highlight the importance of understanding the impact of nutrition on chronic disease prevention and control. A multidisciplinary working group sponsored by the Canadian and US government DRI steering committees met from November 2014 to April 2016 to identify options for addressing key scientific challenges encountered in the use of chronic disease endpoints to establish reference values. The working group focused on 3 key questions: 1) What are the important evidentiary challenges for selecting and using chronic disease endpoints in future DRI reviews, 2) what intake-response models can future DRI committees consider when using chronic disease endpoints, and 3) what are the arguments for and against continuing to include chronic disease endpoints in future DRI reviews? This report outlines the range of options identified by the working group for answering these key questions, as well as the strengths and weaknesses of each option.

The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions.

BACKGROUND: The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions. OBJECTIVE: Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures. METHODS: New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling. DISCUSSION: NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams. CONCLUSIONS: While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

Addressing human variability in next-generation human health risk assessments of environmental chemicals.

BACKGROUND: Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment. OBJECTIVE: Our goal was to explore how next-generation human health risk assessments may better characterize variability in the context of the conceptual framework for the source-to-outcome continuum. METHODS: This review was informed by a National Research Council workshop titled "Biological Factors that Underlie Individual Susceptibility to Environmental Stressors and Their Implications for Decision-Making." We considered current experimental and in silico approaches, and emerging data streams (such as genetically defined human cells lines, genetically diverse rodent models, human omic profiling, and genome-wide association studies) that are providing new types of information and models relevant for assessing interindividual variability for application to human health risk assessments of environmental chemicals. DISCUSSION: One challenge for characterizing variability is the wide range of sources of inherent biological variability (e.g., genetic and epigenetic variants) among individuals. A second challenge is that each particular pair of health outcomes and chemical exposures involves combinations of these sources, which may be further compounded by extrinsic factors (e.g., diet, psychosocial stressors, other exogenous chemical exposures). A third challenge is that different decision contexts present distinct needs regarding the identification-and extent of characterization-of interindividual variability in the human population. CONCLUSIONS: Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing interindividual variability in a range of decision-making contexts.

Evaluation of the cardiovascular effects of methylmercury exposures: current evidence supports development of a dose-response function for regulatory benefits analysis.

BACKGROUND: The U.S. Environmental Protection Agency (U.S. EPA) has estimated the neurological benefits of reductions in prenatal methylmercury (MeHg) exposure in past assessments of rules controlling mercury (Hg) emissions. A growing body of evidence suggests that MeHg exposure can also lead to increased risks of adverse cardiovascular impacts in exposed populations. DATA EXTRACTION: The U.S. EPA assembled the authors of this article to participate in a workshop, where we reviewed the current science concerning cardiovascular health effects of MeHg exposure via fish and seafood consumption and provided recommendations concerning whether cardiovascular health effects should be included in future Hg regulatory impact analyses. DATA SYNTHESIS: We found the body of evidence exploring the link between MeHg and acute myocardial infarction (MI) to be sufficiently strong to support its inclusion in future benefits analyses, based both on direct epidemiological evidence of an MeHg-MI link and on MeHg's association with intermediary impacts that contribute to MI risk. Although additional research in this area would be beneficial to further clarify key characteristics of this relationship and the biological mechanisms that underlie it, we consider the current epidemiological literature sufficiently robust to support the development of a dose- response function. CONCLUSIONS: We recommend the development of a dose- response function relating MeHg exposures with MIs for use in regulatory benefits analyses of future rules targeting Hg air emissions.

State-of-the-science workshop report: issues and approaches in low-dose-response extrapolation for environmental health risk assessment.

Low-dose extrapolation model selection for evaluating the health effects of environmental pollutants is a key component of the risk assessment process. At a workshop held in Baltimore, Maryland, on 23-24 April 2007, sponsored by U.S. Environmental Protection Agency and Johns Hopkins Risk Sciences and Public Policy Institute, a multidisciplinary group of experts reviewed the state of the science regarding low-dose extrapolation modeling and its application in environmental health risk assessments. Participants identified discussion topics based on a literature review, which included examples for which human responses to ambient exposures have been extensively characterized for cancer and/or noncancer outcomes. Topics included the need for formalized approaches and criteria to assess the evidence for mode of action (MOA), the use of human versus animal data, the use of MOA information in biologically based models, and the implications of interindividual variability, background disease processes, and background exposures in threshold versus nonthreshold model choice. Participants recommended approaches that differ from current practice for extrapolating high-dose animal data to low-dose human exposures, including categorical approaches for integrating information on MOA, statistical approaches such as model averaging, and inference-based models that explicitly consider uncertainty and interindividual variability.

Database for physiologically based pharmacokinetic (PBPK) modeling: physiological data for healthy and health-impaired elderly.

Physiologically based pharmacokinetic (PBPK) models have increasingly been employed in chemical health risk assessments. By incorporating individual variability conferred by genetic polymorphisms, health conditions, and physiological changes during development and aging, PBPK models are ideal for predicting chemical disposition in various subpopulations of interest. In order to improve the parameterization of PBPK models for healthy and health-impaired elderly (herein defined as those aged 65 yr and older), physiological parameter values were obtained from the peer-reviewed literature, evaluated, and entered into a Microsoft ACCESS database. Database records include values for key age-specific model inputs such as ventilation rates, organ volumes and blood flows, glomerular filtration rates, and other clearance-related processes. In total, 528 publications were screened for relevant data, resulting in the inclusion of 155 publications comprising 1051 data records for healthy elderly adults and 115 data records for elderly with conditions such as diabetes, chronic obstructive pulmonary disease (COPD), obesity, heart disease, and renal disease. There are no consistent trends across parameters or their associated variance with age; the gross variance in body weight decreased with advancing age, whereas there was no change in variance for brain weight. The database contains some information to inform ethnic and gender differences in parameters; however, the majority of the published data pertain to Asian (mostly Japanese) and Caucasian males. As expected, the number of records tends to decrease with advancing age. In addition to a general lack of data for parameters in the elderly with various health conditions, there is also a dearth of information on blood and tissue composition in all elderly groups. Importantly, there are relatively few records for alveolar ventilation rate; therefore, the relationship between this parameter and cardiac output (usually assumed to be 1:1) in the elderly is not well informed by the database. Despite these limitations, the database represents a potentially useful resource for parameterizing PBPK models for the elderly to facilitate the prediction of dose metrics in older populations for application in risk assessment.

The influence of genetic polymorphisms on population variability in six xenobiotic-metabolizing enzymes.

This review provides variability statistics for polymorphic enzymes that are involved in the metabolism of xenobiotics. Six enzymes were evaluated: cytochrome P-450 (CYP) 2D6, CYP2E1, aldehyde dehydrogenase-2 (ALDH2), paraoxonase (PON1), glutathione transferases (GSTM1, GSTT1, and GSTP1), and N-acetyltransferases (NAT1 and NAT2). The polymorphisms were characterized with respect to (1) number and type of variants, (2) effects of polymorphisms on enzyme function, and (3) frequency of genotypes within specified human populations. This information was incorporated into Monte Carlo simulations to predict the population distribution and describe interindividual variability in enzyme activity. The results were assessed in terms of (1) role of these enzymes in toxicant activation and clearance, (2) molecular epidemiology evidence of health risk, and (3) comparing enzyme variability to that commonly assumed for pharmacokinetics. Overall, the Monte Carlo simulations indicated a large degree of interindividual variability in enzyme function, in some cases characterized by multimodal distributions. This study illustrates that polymorphic metabolizing systems are potentially important sources of pharmacokinetic variability, but there are a number of other factors including blood flow to liver and compensating pathways for clearance that affect how a specific polymorphism will alter internal dose and toxicity. This is best evaluated with the aid of physiologically based pharmacokinetic (PBPK) modeling. The population distribution of enzyme activity presented in this series of articles serves as inputs to such PBPK modeling analyses.

Genetic polymorphism in cytochrome P450 2D6 (CYP2D6): Population distribution of CYP2D6 activity.

Cytochrome P-450 2D6 (CYP2D6) is involved in the metabolism of many therapeutic drugs even though the enzyme represents a small proportion of the total CYP content of human liver. In vivo phenotyping with probe drug substrates such as debrisoquine and dextromethorphan showed a clear separation between poor metabolizers (PM) and extensive metabolizers (EM). This polymorphism may affect susceptibility to environmental disease, as suggested by molecular epidemiologic studies that found an association between CYP2D6 metabolizer phenotype and cancer risk; however, this association is not consistent. There are only a few examples of CYP2D6 involvement in toxicant mechanism of action, but this has not been extensively studied. Gene probe studies documented a number of genetic polymorphisms that underlie CYP2D6 metabolizer phenotypes. The EM group carries the wild-type (*1) or active (*2) variant alleles, while the PM group carries the *3, *4, *5, or *6 alleles, all of which code for a protein that has lower or null CYP2D6 activity. The current analysis characterizes (a) influence of genotype on phenotype based upon in vivo metabolism studies of probe drugs and (b) frequency of the major genotypes in different population groups is also characterized. These data were then incorporated into Monte Carlo modeling to simulate population distributions of CYP2D6 activity. This analysis reproduced the bimodal distributions commonly seen in phenotyping studies of Caucasians and found extensive population variability in enzyme activity, as indicated by the 9- to 56-fold difference between the PM modal median and the total population median CYP2D6 activity. This substantial degree of interindividual variability in CYP function indicates that assessments involving CYP2D6 substrates need to consider the full distribution of enzyme activity in refining estimates of internal dose in health assessments of xenobiotics.

Genetic polymorphism in CYP2E1: Population distribution of CYP2E1 activity.

Cytochrome P-450 2E1 (CYP2E1) is a key enzyme in the metabolic activation of a variety of toxicants including nitrosamines, benzene, vinyl chloride, and halogenated solvents such as trichloroethylene. CYP2E1 is also one of the enzymes that metabolizes ethanol to acetaldehyde, and is induced by recent ethanol ingestion. There is evidence that interindividual variability in the expression and functional activity of this cytochrome (CYP) may be considerable. Genetic polymorphisms in CYP2E1 were identified and linked to altered susceptibility to hepatic cirrhosis induced by ethanol and esophageal and other cancers in some epidemiological studies. Therefore, it is important to evaluate how such polymorphisms affect CYP2E1 function and whether it is possible to construct a population distribution of CYP2E1 activity based upon the known effects of these polymorphisms and their frequency in the population. This analysis is part of the genetic polymorphism database project described in the lead article in this series and followed the approach described in that article (Ginsberg et al., 2009, this issue). Review of the literature found that there are a variety of CYP2E1 variant alleles but the functional significance of these variants is still unclear. Some, but not all, studies suggest that several upstream 5' flanking mutations affect gene expression and response to inducers such as ethanol or obesity. None of the coding-region variants consistently affects enzyme function. Part of the reason for conflicting evidence regarding genotype effect on phenotype may be due to the wide variety of exposures such as ethanol or dietary factors and physiological factors including body weight or diabetes that modulate CYP2E1 expression. In conclusion, evidence is too limited to support the development of a population distribution of CYP2E1 enzyme activity based upon genotypes. Health risk assessments may best rely upon data reporting interindividual variability in CYP2E1 function for input into physiologically based pharmacokinetic (PBPK) models involving CYP2E1 substrates.

Genetic polymorphism in N-Acetyltransferase (NAT): Population distribution of NAT1 and NAT2 activity.

N-Acetyltransferases (NAT) are key enzymes in the conjugation of certain drugs and other xenobiotics with an arylamine structure. Polymorphisms in NAT2 have long been recognized to modulate toxicity produced by the anti-tubercular drug isoniazid, with molecular epidemiologic studies suggesting a link between acetylator phenotype and increased risk for bladder cancer. Recent evidence indicates that the other major NAT isozyme, NAT1, is also polymorphic. The current analysis characterizes the main polymorphisms in both NAT2 and NAT1 in terms of their effect on enzyme activity and frequency in the population. Multiple NAT2 alleles (NAT2*5, *6, *7, and *14) have substantially decreased acetylation activity and are common in Caucasians and populations of African descent. In these groups, most individuals carry at least one copy of a slow acetylator allele, and less than 10% are homozygous for the wild type (fast acetylator) trait. Incorporation of these data into a Monte Carlo modeling framework led to a population distribution of NAT2 activity that was bimodal and associated with considerable variability in each population assessed. The ratio of the median to the first percentile of NAT2 activity ranged from 7 in Caucasians to 18 in the Chinese population. This variability indicates the need for more quantitative approaches (e.g., physiologically based pharmacokinetic [PBPK] modeling) to assess the full distribution of internal dose and adverse responses to aromatic amines and other NAT2 substrates. Polymorphisms in NAT1 are generally associated with relatively minor effects on acetylation function, with Monte Carlo analysis indicating less interindividual variability than seen in NAT2 analysis.

Genetic Polymorphism in Glutathione Transferases (GST): Population distribution of GSTM1, T1, and P1 conjugating activity.

Glutathione transferases (GST) catalyze the conjugation of glutathione (GSH) with electrophiles, many of which may otherwise interact with protein or DNA. In select cases such as halogenated solvents, GST-mediated conjugation may lead to a more toxic or mutagenic metabolite. Polymorphisms that exert substantial effects on GST function were noted in human populations for several isozymes. This analysis focuses on three well-characterized isozymes, GSTM1, T1, and P1, in which polymorphisms were extensively studied with respect to DNA adducts and cancer in molecular epidemiologic studies. The current review and analysis focused upon how polymorphisms in these GST contributed to population variability in GST function. The first step in developing this review was to characterize the influence of genotype on phenotype (enzyme function) and the frequency of the polymorphisms across major population groups for all three GST. This information was then incorporated into Monte Carlo simulations to develop population distributions of enzyme function. These simulations were run separately for GSTM1, T1, and P1, and also for the combination of these isozymes, to assess the possibility of overlapping substrate specificity. Monte Carlo simulations indicated large interindividual variability for GSTM1 and T1 due to the presence of the null (zero activity) genotype, which is common in all populations studied. Even for GSTM1 or T1 non-null individuals, there was considerable interindividual variability with a bimodal distribution of enzyme activity evident. GSTP1 polymorphisms are associated with somewhat less variability due to the absence of null genotypes. However, in all cases simulated, the estimated variability is sufficiently large to warrant consideration of GST function distributions in assessments involving GST-mediated activation or detoxification of xenobiotics. Ideally, such assessments would involve physiologically based toxicokinetic (PBTK) modeling to assess population variability in internal dose.

Genetic polymorphism in paraoxonase 1 (PON1): Population distribution of PON1 activity.

Paraoxonase-1 (PON1) is a serum esterase that hydrolyzes the activated oxon form of several organophosphates. The central role of PON1 in detoxification of organophosphate (OP) pesticides was demonstrated in knockout mouse studies, suggesting that human variability in PON1 needs to be considered in health risk assessments involving exposure to these pesticides. The current analysis focused on two genetic loci in which polymorphisms demonstrated to affect PON1 activity. Detailed kinetic studies and population studies found that the *192Q (wild type) allele is more active toward some substrates (such as sarin, soman, and diazoxon) and less active toward others (such as paraoxon or chlorpyrifos) relative to the variant *192R allele. Another allele that affects activity is *55M; PON1 enzyme quantity, rather than specific activity or substrate preference, is altered. The *192R variant occurs commonly with a frequency of 25-64% across the populations analyzed. The *55M allele is less common, occurring in 5-40% of individuals depending upon the ethnic group studied. These activity and allele frequency data were incorporated into Monte Carlo simulations in which the frequency of both variant alleles was simultaneously modeled in Caucasian, African American, and Japanese populations. The resulting Monte Carlo activity distributions were bimodal for the substrate paraoxon with approximately fourfold differences between low- and high-activity modal medians. Differences in activity between total population median and 1st percentile were five- to sixfold. When sarin metabolic variability was simulated, the population distributions were unimodal. However, there was an even greater degree of interindividual variability (median to 1st percentile difference >20-fold). These results show that the combined effects of two PON1 allelic variants yielded a population distribution that is associated with a considerable degree of interindividual variability in enzyme activity. This indicates that assessments involving PON1 substrates need to evaluate polymorphism-related variability in enzyme activity to display the distribution of internal doses and adverse responses. This may best be achieved via physiologically based pharmacokinetic (PBPK) models that input PON1 activity distributions, such as those generated in this analysis, to simulate the range of oxon internal doses possible across the population.

Meeting report: moving upstream-evaluating adverse upstream end points for improved risk assessment and decision-making.

BACKGROUND: Assessing adverse effects from environmental chemical exposure is integral to public health policies. Toxicology assays identifying early biological changes from chemical exposure are increasing our ability to evaluate links between early biological disturbances and subsequent overt downstream effects. A workshop was held to consider how the resulting data inform consideration of an "adverse effect" in the context of hazard identification and risk assessment. OBJECTIVES: Our objective here is to review what is known about the relationships between chemical exposure, early biological effects (upstream events), and later overt effects (downstream events) through three case studies (thyroid hormone disruption, antiandrogen effects, immune system disruption) and to consider how to evaluate hazard and risk when early biological effect data are available. DISCUSSION: Each case study presents data on the toxicity pathways linking early biological perturbations with downstream overt effects. Case studies also emphasize several factors that can influence risk of overt disease as a result from early biological perturbations, including background chemical exposures, underlying individual biological processes, and disease susceptibility. Certain effects resulting from exposure during periods of sensitivity may be irreversible. A chemical can act through multiple modes of action, resulting in similar or different overt effects. CONCLUSIONS: For certain classes of early perturbations, sufficient information on the disease process is known, so hazard and quantitative risk assessment can proceed using information on upstream biological perturbations. Upstream data will support improved approaches for considering developmental stage, background exposures, disease status, and other factors important to assessing hazard and risk for the whole population.

Potential new approaches for children's inhalation risk assessment.

The U.S. Environmental Protection Agency (EPA) practice of risk assessment is moving toward more thoroughly considering children's unique susceptibilities and exposure potential. Childhood is assessed as a sequence of life stages that reflects the fact that as humans develop, windows of susceptibility may appear that lead to enhanced sensitivity to exposure of environmental agents, while changes in behavior and physiology may increase exposure and dose. The U.S. EPA developed guidance in the past few years that addresses some aspects of increased susceptibility and exposure and dose. However, when it comes to considering inhalation exposure, dose, and risk, current U.S. EPA practice does not explicitly address children. The purpose here is to begin studying the adequacy of practice for children's health and to explore possible next steps in developing new methods to more accurately assess life-stage-specific differences. The existing guidelines and policies used to address potentially unique susceptibilities of children for inhaled environmental chemicals were considered, as well as what may be learned from examples of approaches that have been applied by state agencies (such as the California Environmental Protection Agency) or in the literature, to incorporate potentially unique susceptibilities and exposures to children. Finally, there is a discussion of possible approaches for considering inhalation exposure and susceptibility in U.S. EPA risk assessments.