Pharmacokinetics (PK) of xenobiotics can differ widely between children and adults due to physiological differences and the immaturity of enzyme systems and clearance mechanisms. This makes extrapolation of adult dosimetry estimates to children uncertain, especially at early postnatal ages. While there is very little PK data for environmental toxicants in children, there is a wealth of such data for therapeutic drugs. Using published literature, a Children's PK Database has been compiled which compares PK parameters between children and adults for 45 drugs. This has enabled comparison of child and adult PK function across a number of cytochrome P450 (CYP) pathways, as well as certain Phase II conjugation reactions and renal elimination. These comparisons indicate that premature and full-term neonates tend to have 3 to 9 times longer half-life than adults for the drugs included in the database. This difference disappears by 2-6 months of age. Beyond this age, half-life can be shorter than in adults for specific drugs and pathways. The range of neonate/adult half-life ratios exceeds the 3.16-fold factor commonly ascribed to interindividual PK variability. Thus, this uncertainty factor may not be adequate for certain chemicals in the early postnatal period. The current findings present a PK developmental profile that is relevant to environmental toxicants metabolized and cleared by the pathways represented in the current database. The manner in which this PK information can be applied to the risk assessment of children includes several different approaches: qualitative (e.g., enhanced discussion of uncertainties), semiquantitative (age group-specific adjustment factors), and quantitative (estimation of internal dosimetry in children via physiologically based PK modeling).

BackgroundThe 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 extractionThe 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 synthesisWe 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.ConclusionsWe 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.

Children's risks can differ from those in adults for numerous reasons, one being differences in the pharmacokinetic handling of chemicals. Immature metabolism and a variety of other factors in neonates can affect chemical disposition and clearance. These factors can be incorporated into physiologically based pharmacokinetic (PBPK) models that simulate the fate of environmental toxicants in both children and adults. PBPK models are most informative when supported by empirical data, but typically pediatric pharmacokinetic data for toxicants are not available. In contrast, pharmacokinetic data in children are readily available for therapeutic drugs. The current analysis utilizes data for caffeine and theophylline, closely related xanthines that are both cytochrome P-450 (CYP) 1A2 substrates, in developing PBPK models for neonates and adults. Model development involved scale-up of in vitro metabolic parameters to whole liver and adjusting metabolic function for the ontological pattern of CYP1A2 and other CYPs. Model runs were able to simulate the large differences in half-life and clearance between neonates and adults. Further, the models were able to reproduce the faster metabolic clearance of theophylline relative to caffeine in neonates. This differential between xanthines was found to be due primarily to an extra metabolic pathway available to theophylline, back-methylation to caffeine, that is not available to caffeine itself. This pathway is not observed in adults exemplifying the importance of secondary or novel routes of metabolism in the immature liver. Greater CYP2E1 metabolism of theophylline relative to caffeine in neonates also occurs. Neonatal PBPK models developed for these drugs may be adapted to other CYP1A2 substrates (e.g., arylamine toxicants). A stepwise approach for modeling environmental toxicants in children is proposed.

Differential exposure to mixtures of environmental agents, including biological, chemical, physical, and psychosocial stressors, can contribute to increased vulnerability of human populations and ecologic systems. Cumulative risk assessment is a tool for organizing and analyzing information to evaluate the probability and seriousness of harmful effects caused by either simultaneous and/or sequential exposure to multiple environmental stressors. In this article we focus on elucidating key challenges that must be addressed to determine whether and to what degree differential exposure to environmental mixtures contributes to increased vulnerability of exposed populations. In particular, the emphasis is on examining three fundamental and interrelated questions that must be addressed as part of the process to assess cumulative risk: a) Which mixtures are most important from a public health perspective? and b) What is the nature (i.e., duration, frequency, timing) and magnitude (i.e., exposure concentration and dose) of relevant cumulative exposures for the population of interest? c) What is the mechanism (e.g., toxicokinetic or toxicodynamic) and consequence (e.g., additive, less than additive, more than additive) of the mixture’s interactive effects on exposed populations? The focus is primarily on human health effects from chemical mixtures, and the goal is to reinforce the need for improved assessment of cumulative exposure and better understanding of the biological mechanisms that determine toxicologic interactions among mixture constituents.

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.

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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.

In recent years the U.S. Environmental Protection Agency has been challenged both externally and internally to move beyond its traditional conservative single-point treatment of various input parameters in risk assessments. In the first section, we assess when more involved distribution-based analyses might be indicated for such common types of risk assessment applications as baseline assessments of Superfund sites. Then in two subsequent sections, we give an overview with some case studies of technical analyses of (A) variabilityheterogeneity and (B) uncertainty. By "interindividual variability" is meant the real variation among individuals in exposure-producing behavior, in exposures, or some other parameter (such as differences among individual municipal solid waste incinerators in emissions). In contrast, "uncertainty" is a description of the imperfection in knowledge of the true value of a particular parameter or its real variability in an individual or a group. In general uncertainty is reducible by additional information-gathering or analysis activities (better data, better models), whereas real variability will not change (although it may be more accurately known) as a result of better or more extensive measurements. The purpose of the rather long-winded exposition of these two final sections is to show the differences between analyses of these two different things, both of which are described using the language of probability distributions.