Benchmark dose risk assessment for formaldehyde using airflow modeling and a single-compartment, DNA-protein cross-link dosimetry model to estimate human equivalent doses

An updated mode of action and human relevance framework evaluation for Formaldehyde-Related nasal tumors

Formaldehyde is a reactive aldehyde naturally present in all plant and animal tissues and a critical component of the one-carbon metabolism pathway. It is also a high production volume chemical used in the manufacture of numerous products. Formaldehyde is also one of the most well-studied chemicals with respect to environmental fate, biology, and toxicology-including carcinogenic potential, and mode of action (MOA). In 2006, a published MOA for formaldehyde-induced nasal tumors in rats concluded that nasal tumors were most likely driven by cytotoxicity and regenerative cell proliferation, with possible contributions from direct genotoxicity. In the past 15 years, new research has better informed the MOA with the publication of in vivo genotoxicity assays, toxicogenomic analyses, and development of ultra-sensitive methods to measure endogenous and exogenous formaldehyde-induced DNA adducts. Herein, we review and update the MOA for nasal tumors, with particular emphasis on the numerous studies published since 2006. These new studies further underscore the involvement of cytotoxicity and regenerative cell proliferation, and further inform the genotoxic potential of inhaled formaldehyde. The data lend additional support for the use of mechanistic data for the derivation of toxicity criteria and/or scientifically supported approaches for low-dose extrapolation for the risk assessment of formaldehyde.

Bayesian model-averaged benchmark dose analysis via reparameterized quantal-response models

An important objective in biomedical and environmental risk assessment is estimation of minimum exposure levels that induce a pre-specified adverse response in a target population. The exposure points in such settings are typically referred to as benchmark doses (BMDs). Parametric Bayesian estimation for finding BMDs has grown in popularity, and a large variety of candidate dose-response models is available for applying these methods. Each model can possess potentially different parametric interpretation(s), however. We present reparameterized dose-response models that allow for explicit use of prior information on the target parameter of interest, the BMD. We also enhance our Bayesian estimation technique for BMD analysis by applying Bayesian model averaging to produce point estimates and (lower) credible bounds, overcoming associated questions of model adequacy when multimodel uncertainty is present. An example from carcinogenicity testing illustrates the calculations.

Small molecule metabolite biomarker candidates in urine from mice exposed to formaldehyde

Formaldehyde (FA) is a ubiquitous compound used in a wide variety of industries, and is also a major indoor pollutant emitted from building materials, furniture, etc. Because FA is rapidly metabolized and endogenous to many materials, specific biomarkers for exposure have not been identified. In this study, we identified small metabolite biomarkers in urine that might be related FA exposure. Mice were allowed to inhale FA (0, 4, 8 mg/m³) 6 h per day for 7 consecutive days, and urine samples were collected on the 7th day of exposure. Liquid chromatography coupled with time of flight-mass spectrometry and principal component analysis (PCA) was applied to determine alterations of endogenous metabolites in urine. Additionally, immune toxicity studies were conducted to ensure that any resultant toxic effects could be attributed to inhalation of FA. The results showed a significant decrease in the relative rates of T lymphocyte production in the spleen and thymus of mice exposed to FA. Additionally, decreased superoxide dismutase activity and increased reactive oxygen species levels were found in the isolated spleen cells of exposed mice. A total of 12 small molecules were found to be altered in the urine, and PCA analysis showed that urine from the control and FA exposed groups could be distinguished from each other based on the altered molecules. Hippuric acid and cinnamoylglycine were identified in urine using exact mass and fragment ions. Our results suggest that the pattern of metabolites found in urine is significantly changed following FA inhalation, and hippuric acid and cinnamoylglycine might represent potential biomarker candidates for FA exposure.

Benchmark Dose Analysis via Nonparametric Regression Modeling

Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose-response modeling. It is a well-known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low-dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal-response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap-based confidence limits for the BMD. We explore the confidence limits' small-sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty.

Nonparametric estimation of benchmark doses in environmental risk assessment

An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits' small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations.

Identifying an indoor air exposure limit for formaldehyde considering both irritation and cancer hazards

Formaldehyde is a well-studied chemical and effects from inhalation exposures have been extensively characterized in numerous controlled studies with human volunteers, including asthmatics and other sensitive individuals, which provide a rich database on exposure concentrations that can reliably produce the symptoms of sensory irritation. Although individuals can differ in their sensitivity to odor and eye irritation, the majority of authoritative reviews of the formaldehyde literature have concluded that an air concentration of 0.3 ppm will provide protection from eye irritation for virtually everyone. A weight of evidence-based formaldehyde exposure limit of 0.1 ppm (100 ppb) is recommended as an indoor air level for all individuals for odor detection and sensory irritation. It has recently been suggested by the International Agency for Research on Cancer (IARC), the National Toxicology Program (NTP), and the US Environmental Protection Agency (US EPA) that formaldehyde is causally associated with nasopharyngeal cancer (NPC) and leukemia. This has led US EPA to conclude that irritation is not the most sensitive toxic endpoint and that carcinogenicity should dictate how to establish exposure limits for formaldehyde. In this review, a number of lines of reasoning and substantial scientific evidence are described and discussed, which leads to a conclusion that neither point of contact nor systemic effects of any type, including NPC or leukemia, are causally associated with exposure to formaldehyde. This conclusion supports the view that the equivocal epidemiology studies that suggest otherwise are almost certainly flawed by identified or yet to be unidentified confounding variables. Thus, this assessment concludes that a formaldehyde indoor air limit of 0.1 ppm should protect even particularly susceptible individuals from both irritation effects and any potential cancer hazard.

Guidance for the classification of carcinogens under the Globally Harmonised System of Classification and Labelling of Chemicals (GHS)

The United Nations Conference on Environment and Development (UNCED) has developed criteria for a globally harmonised system of classification and labelling of chemicals (GHS). With regard to carcinogenicity, GHS distinguishes between Category 1 ('known or presumed human carcinogens') and Category 2 ('suspected human carcinogens'). Category 1 carcinogens are divided into Category 1A ('known to have carcinogenic potential for humans'), based largely on human evidence, and 1B ('presumed to have carcinogenic potential for humans'), based largely on experimental animal data. Concerns have been raised that the criteria for applying these carcinogenicity classifications are not sufficiently well defined and potentially allow different conclusions to be drawn. The current document describes an attempt to reduce the potential for diverse conclusions resulting from the GHS classification system through the application of a series of questions during the evaluation of data from experiments with rodents; epidemiological data, which could lead to Category 1A, have not been considered. Answers to each question can lead either to a classification decision or to the next question, but this process should only be implemented in an environment of informed scientific opinion. The scheme is illustrated with five case studies. These questions are: (1) Has a relevant form of the substance been tested? (2) Is the study design relevant to human exposure? (3) Is there a substance-related response? (4) Is the target tissue exposure relevant to humans? (5) Can a mode of action be established? (6) Is the mode of action relevant to humans? (7) What is the potency?

Bootstrap methods for simultaneous benchmark analysis with quantal response data

A primary objective in quantitative risk assessment is the characterization of risk which is defined to be the likelihood of an adverse effect caused by an environmental toxin or chemcial agent. In modern risk-benchmark analysis, attention centers on the "benchmark dose" at which a fixed benchmark level of risk is achieved, with a lower confidence limits on this dose being of primary interest. In practice, a range of benchmark risks may be under study, so that the individual lower confidence limits on benchmark dose must be corrected for simultaneity in order to maintain a specified overall level of confidence. For the case of quantal data, simultaneous methods have been constructed that appeal to the large sample normality of parameter estimates. The suitability of these methods for use with small sample sizes will be considered. A new bootstrap technique is proposed as an alternative to the large sample methodology. This technique is evaluated via a simulation study and examples from environmental toxicology.

Determinants of whether or not mixtures of disinfection by-products are similar

Reactive chemicals have been used to disinfect drinking waters for over a century. In the 1970s, it was first observed that the reaction of these chemicals with the natural organic matter (NOM) in source waters results in the production of variable, complex mixtures of disinfection by-products (DBP). Because limited toxicological and epidemiological data are available to assess potential human health risks from complex DBP mixture exposures, methods are needed to determine when health effects data on a specific DBP mixture may be used as a surrogate for evaluating another environmental DBP mixture of interest. Before risk assessors attempt such efforts, a set of criteria needs to be in place to determine whether two or more DBP mixtures are similar in composition and toxicological potential. This study broadly characterizes the chemical and toxicological measures that may be used to evaluate similarities among DBP mixtures. Variables are discussed that affect qualitative and quantitative shifts in the types of DBP that are formed, including disinfectants used, their reactions with NOM and with bromide/iodide, pH, temperature, time, and changes in the water distribution system. The known toxicological activities of DBP mixtures and important single DBPs are also presented in light of their potential for producing similar toxicity. While DBP exposures are associated with a number of health effects, this study focuses on (1) mutagenic activity of DBP mixtures, (2) DBP cancer epidemiology, and (3) toxicology studies to evaluate similarity among DBP mixtures. Data suggest that further chemical characterization of DBP mixtures and more systematic study of DBP toxicology will improve the quality and usefulness of similarity criteria.

Pitfalls and Related Improvements of In Vivo Gas Uptake Pharmacokinetic Experimental Systems

Gas uptake chamber studies have been widely used to study inhalation pharmacokinetics (PKs) in rodents, often for the ultimate purpose of developing physiologically-based pharmacokinetic (PBPK) models that can be used to describe human PKs and to support risk assessment for the chemical. In the course of our studies of gasoline PKs, we revisited several important issues heretofore not thoroughly addressed. Here, we report several refinements which will significantly improve future studies with this type of system, relating to the understanding of loss rates, the importance of carbon dioxide removal, and sampling of blood and chamber air at the same time. Losses of chemicals in gas uptake systems consist of leakage, adsorption to system components, and adsorption to the hair and skin (fur) of experimental animals. The loss rates were experimentally determined for a series of chemicals and mixtures including n-hexane, benzene, toluene, ethylbenzene, o-xylene, gasoline, and other gasoline components. The rate of loss to the animals' fur was similar to loss rates to system components and involved absorption to both hair and skin. Most of the absorption to fur was reversible when the chamber concentration was low enough. The amount of chemical that desorbed from the animal after an experiment was significant when compared to the amount of chemical in the chamber at the end of a gas uptake experiment, indicating that the rate of decline in concentrations can be influenced by a decrease in the fur absorption rate or desorption of chemicals. A modified gas uptake system design is described in which a steel ring improved the connections to an autosampler and allowed insertion of probes to monitor gases, such as carbon dioxide (CO2), in the chamber. When CO2 absorbent efficiency was inadequate, CO2 concentrations rose to levels that significantly affected the animals' ventilation rate. Using a real-time CO2 probe, an absorbent system was developed that adequately controlled CO2 levels in the chamber. Attention to details of absorptive loss and CO2 scrubbing can improve the reliability of kinetic constants inferred from closed chamber studies. We then describe a method for extending gas uptake experiments by simultaneously collecting blood to be analyzed for chemicals and/or metabolites.

Approaches for applications of physiologically based pharmacokinetic models in risk assessment

Physiologically based pharmacokinetic (PBPK) models are particularly useful for simulating exposures to environmental toxicants for which, unlike pharmaceuticals, there is often little or no human data available to estimate the internal dose of a putative toxic moiety in a target tissue or an appropriate surrogate. This article reviews the current state of knowledge and approaches for application of PBPK models in the process of deriving reference dose, reference concentration, and cancer risk estimates. Examples drawn from previous U.S. Environmental Protection Agency (EPA) risk assessments and human health risk assessments in peer-reviewed literature illustrate the ways and means of using PBPK models to quantify the pharmacokinetic component of the interspecies and intraspecies uncertainty factors as well as to conduct route to route, high dose to low dose and duration extrapolations. The choice of the appropriate dose metric is key to the use of the PBPK models for the various applications in risk assessment. Issues related to whether uncertainty factors are most appropriately applied before or after derivation of human equivalent dose (or concentration) continue to be explored. Scientific progress in the understanding of life stage and genetic differences in dosimetry and their impacts on variability in susceptibility, as well as ongoing development of analytical methods to characterize uncertainty in PBPK models, will make their use in risk assessment increasingly likely. As such, it is anticipated that when PBPK models are used to express adverse tissue responses in terms of the internal target tissue dose of the toxic moiety rather than the external concentration, the scientific basis of, and confidence in, risk assessments will be enhanced.

Genomic signatures and dose-dependent transitions in nasal epithelial responses to inhaled formaldehyde in the rat

Repeated and acute exposure studies assessed time and concentration-dependencies of nasal responses to formaldehyde. Exposures were to 0, 0.7, 2, and 6 ppm for 6 h/day, 5 days/week for up to 3 weeks. Neither cell proliferation nor histopathology was observed at 0.7 ppm. At 6 ppm, cell proliferation increased at the end of the first week (day 5), but not at the end of week 3 (day 15). Squamous metaplasia occurred at day 5; epithelial hyperplasia occurred at both day 5 and day 15. In microarray studies, no genes were altered at 0.7 ppm. At 2 ppm, 15 genes were changed on day 5; only half of them were changed at 6 ppm. No genes were changed significantly at 2 ppm at day 15. The pattern of gene changes at 2 and 6 ppm, with transient squamous metaplasia at day 5, indicated tissue adaptation and reduced tissue sensitivity by day 15. The acute study included an additional concentration (15 ppm) and an instillation group (40 microl, 400 mM per nostril). Three times more genes were affected by instillation than inhalation. U-shaped dose responses were noted in the acute study for many genes that were also altered at 2 ppm on day 5. On the basis of cellular component gene ontology benchmark dose analysis, the most sensitive changes were for genes were associated with extracellular components and plasma membrane. With formaldehyde, there are temporal and concentration-dependent transitions in epithelial responses and genomic signatures between 0.7 and 6 ppm. Low concentrations primarily affect extracellular matrix or external plasma membrane portions of the epithelium.

Simultaneous Confidence Bands for Abbott-Adjusted Quantal Response Models

We study use of a Scheffé-style simultaneous confidence band as applied to low-dose risk estimation with quantal response data. We consider two formulations for the dose-response risk function, an Abbott-adjusted Weibull model and an Abbott-adjusted log-logistic model. Using the simultaneous construction, we derive methods for estimating upper confidence limits on predicted extra risk and, by inverting the upper bands on risk, lower bounds on the benchmark dose, or BMD, at which a specific level of 'benchmark risk' is attained. Monte Carlo evaluations explore the operating characteristics of the simultaneous limits.

Derivation of an inhalation reference concentration based upon olfactory neuronal loss in male rats following subchronic acetaldehyde inhalation

Acetaldehyde inhalation induces neoplastic and nonneoplastic responses in the rodent nasal cavity. This experiment further characterizes the dose-response relationship for nasal pathology, nasal epithelial cell proliferation, and DNA-protein cross-link formation in F-344 rats exposed subchronically to acetaldehyde. Animals underwent whole-body exposure to 0, 50, 150, 500, or 1500 ppm acetaldehyde for 6 h/day, 5 days/wk for up to 65 exposure days. Respiratory tract histopathology was evaluated after 4, 9, 14, 30, and 65 exposure days. Acetaldehyde exposure was not associated with reduced body weight gain or other evidence of systemic toxicity. Histologic evaluation of the nasal cavity showed an increased incidence of olfactory neuronal loss (ONL) following acute to subchronic exposure to > or = 150 ppm acetaldehyde and increased olfactory epithelial cell proliferation following exposure to 1500 ppm acetaldehyde. The severity of the ONL demonstrated dose- and temporal-dependent behaviors, with minimal effects noted at 150-500 ppm acetaldehyde and moderately severe lesions seen in the highest exposure group, with increased lesion severity and extent as the exposure duration increased. Acetaldehyde exposure was also associated with inflammation, hyperplasia, and squamous metaplasia of the respiratory epithelium. These responses were seen in animals exposed to > or = 500 ppm acetaldehyde. Acetaldehyde exposure was not associated with increased DNA-protein cross-link formation in the respiratory or olfactory epithelium. A model of acetaldehyde pharmacokinetics in the nose was used to derive an inhalation reference concentration (RfC) of 0.4 ppm, based on the no-observed-adverse-effect level (NOAEL) of 50 ppm for the nasal pathology seen in this study.

Benchmark analysis for quantifying urban vulnerability to terrorist incidents

We describe a quantitative methodology to characterize the vulnerability of U.S. urban centers to terrorist attack, using a place-based vulnerability index and a database of terrorist incidents and related human casualties. Via generalized linear statistical models, we study the relationships between vulnerability and terrorist events, and find that our place-based vulnerability metric significantly describes both terrorist incidence and occurrence of human casualties from terrorist events in these urban centers. We also introduce benchmark analytic technologies from applications in toxicological risk assessment to this social risk/vulnerability paradigm, and use these to distinguish levels of high and low urban vulnerability to terrorism. It is seen that the benchmark approach translates quite flexibly from its biological roots to this social scientific archetype.

Statistics for risk assessment of chemical carcinogens

Risk assessment is a scientific process of evaluation of potential health risks of chemical exposures to humans from available information. It involves analysis of the relationship between exposure and health related outcomes to derive an allowable exposure level. Because of lack of human exposure data, the major source of information for studying potential health effects of chemicals on humans is generally obtained from animal dose response experiments. Animal data are often evaluated in two aspects via statistical analysis: qualitative testing and quantitative estimation. The qualitative testing is to determine if the chemical causes an adverse health effect, i.e., if there is a statistically significant difference between treated and control animals. Quantitative estimation involves fitting a dose-response model to derive an allowable exposure level for humans. This paper reviews statistical principles and procedures for qualitative and quantitative approaches to human risk assessment.

A method to integrate benchmark dose estimates with genomic data to assess the functional effects of chemical exposure

The use of genomic technology for assessing health risks associated with chemical exposure has significant potential, but its direct application has proven to be challenging for the toxicology and risk assessment communities. In this study, a method was established for analyzing dose-response microarray data using benchmark dose (BMD) calculations and gene ontology (GO) classification. Gene expression changes in the rat nasal epithelium following acute formaldehyde exposure were used as a case study. The gene expression data were first analyzed using a one-way ANOVA to identify genes that showed significant dose-response behavior. These genes were then fit to a series of four statistical models (linear, second-degree polynomial, third-degree polynomial, and power models) and the least complex model that best described the data was selected. The genes were matched to their associated GO categories, and the average BMD and benchmark dose lower confidence limit (BMDL) were calculated for each GO category. The results were used to identify doses at which individual cellular processes were altered. For the formaldehyde exposures, the BMD estimates for the GO categories related to cell proliferation and DNA damage were similar to those measured in previous studies using cell labeling indices and DNA-protein cross-links and consistent with the BMD estimated for rat nasal tumors. The method represents a significant advance in applying genomic information to risk assessment by allowing a comprehensive survey of molecular changes associated with chemical exposure and providing the capability to identify reference doses at which particular cellular processes are altered.

SIMULTANEOUS CONFIDENCE BOUNDS FOR LOW-DOSE RISK ASSESSMENT WITH NONQUANTAL DATA

We study the use of simultaneous confidence bounds for making low-dose inferences in quantitative risk analysis. Confidence limits are constructed for outcomes measured on a continuous scale, assuming a simple linear model for the observed response. From the simultaneous confidence bounds, simultaneous lower limits on the benchmark dose associated with a particular risk are also constructed.

Formaldehyde and glutaraldehyde and nasal cytotoxicity: case study within the context of the 2006 IPCS Human Framework for the Analysis of a cancer mode of action for humans

Formaldehyde and glutaraldehyde cause toxicity to the nasal epithelium of rats and mice upon inhalation. In addition, formaldehyde above certain concentrations induces dose-related increases in nasal tumors in rats and mice, but glutaraldehyde does not. Using the 2006 IPCS human framework for the analysis of cancer mode of action (MOA), an MOA for formaldehyde was formulated and its relevance was tested against the properties of the noncarcinogenic glutaraldehyde. These compounds produce similar patterns of response in histopathology and in genotoxicity tests (although formaldehyde has been much more extensively tested studied). The MOA is based on the induction of sustained cytotoxicity and reparative cell proliferation induced by formaldehyde at concentrations that also induce nasal tumors upon long-term exposure. Data on dose dependency and temporal relationships of key events are consistent with this MOA. While a genotoxic MOA can never be ruled out for a compound that is clearly genotoxic, at least in vitro, the nongenotoxic properties fundamental to the proposed MOA can explain the neoplastic response in the nose and may be more informative than genotoxicity in risk assessment. It is not yet fully explained why glutaraldehyde remains noncarcinogenic upon inhalation, but its greater inherent toxicity may be a key factor. The dual aldehyde functions in glutaraldehyde are likely to produce damage resulting in fewer kinetic possibilities (particularly for proteins involved in differentiation control) and lower potential for repair (nucleic acids) than would be the case for formaldehyde. While there have been few studies of possible glutaraldehyde-associated cancer, the evidence that formaldehyde is a human carcinogen is strong for nasopharyngeal cancers, although less so for sinonasal cancers. This apparent discrepancy could be due in part to the classification of human nasal tumors with tumors of the sinuses, which would receive much less exposure to inhaled formaldehyde. Evaluation of the human relevance of the proposed MOA of formaldehyde in rodents is restricted by human data limitations, although the key events are plausible. It is clear that the human relevance of the formaldehyde MOA in rodents cannot be excluded on either kinetic or dynamic grounds.

Nasal dosimetry of inhaled gases and particles: where do inhaled agents go in the nose?

The anatomical structure of the nasal passages differs significantly among species, affecting airflow and the transport of inhaled gases and particles throughout the respiratory tract. Since direct measurement of local nasal dose is often difficult, 3-dimensional, anatomically accurate, computational models of the rat, monkey, and human nasal passages were developed to estimate regional transport and dosimetry of inhaled material. The computational models predicted that during resting breathing, a larger portion of inspired air passed through olfactory-lined regions in the rat than in the monkey or human. The models also predicted that maximum wall mass flux (mass per surface area per time) of inhaled formaldehyde in the nonsquamous epithelium was highest in monkeys (anterior middle turbinate) and similar in rats and humans (dorsal medial meatus in the rat and mid-septum in the human, near the squamous/nonsquamous epithelial boundary in both species). For particles that are 5 microm in aerodynamic diameter, preliminary simulations at minute volume flow rates predicted nasal deposition efficiencies of 92%, 11% and 25% in the rat, monkey, and human, respectively, with more vestibular deposition in the rat than in the monkey or human. Estimates such as these can be used to test hypotheses about mechanisms of toxicity and supply species-specific information for risk assessment, thus reducing uncertainty in extrapolating animal data to humans.

Hierarchical models for probabilistic dose–response assessment

Probabilistic risk assessment is gaining acceptance as the most appropriate way to characterize and communicate uncertainties in estimates of human health risk and/or reference levels of exposure such as benchmark doses. Although probabilistic techniques are well established in the exposure-assessment component of the National Research Council's risk-assessment paradigm, they are less well developed in the dose-response-assessment component. This paper proposes the use of hierarchical statistical models as tools for implementing probabilistic dose-response assessments, in that such models provide a natural connection between the pharmacokinetic (PK) and pharmacodynamic (PD) components of dose-response models. The results show that incorporating internal dose information into dose-response assessments via the coupling of PK and PD models in a hierarchical structure can reduce the uncertainty in the dose-response assessment of risk. However, information on the mean of the internal dose distribution is sufficient; having information on the variance of internal dose does not affect the uncertainty in the resulting estimates of excess risks or benchmark doses. In addition, the complexity of a PK model of internal dose does not affect how the variability in risk is measured via the ultimate endpoint.

The role of the benchmark dose in a regulatory context

The use of no observed adverse effect levels (NOAELs) as a way of interpreting toxicology studies carries a number of problems, and the benchmark dose (BMD), or its lower confidence limit have been proposed as potential replacements. In practice, the theoretical advantages of the BMD approach are often outweighed by the practical disadvantages posed in a regulatory context. Attempts to seek consensus for the routine use of BMD methodology tend to involve diluting its potential advantages as much as they address the disadvantages, resulting in a relatively complex interpolation tool that delivers little more than the NOAEL. It is time to recognise that the BMD will never entirely replace the NOAEL. The two methods can have complementary roles. The NOAEL is well suited as a routine simple summary of effects in toxicology studies, whilst the BMD can be a higher tier approach for the interpretation of the most critical studies in a regulatory data package.

Benchmark analysis: shopping with proper confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.

ADVANCES IN RISK ASSESSMENT AND COMMUNICATION

Risk analysis continues to evolve. There is increasing depth and breadth to each component of the four-step risk-assessment paradigm of hazard identification, dose-response analysis, exposure assessment, and risk characterization. Basic conceptual approaches to understanding how people perceive risk are being tested against a growing body of empirical observations, many involving stakeholders. Emerging ideas such as the precautionary principle have provided challenges that have led to a rethinking of the role of risk assessment in environmental health. Newer problems, such as intergenerational issues posed by long-lasting radiation pollution, environmental justice, and the assessment and communication of risks related to terrorism, have spurred innovative approaches to risk analysis.

Multiplicity-Adjusted Inferences in Risk Assessment: Benchmark Analysis with Quantal Response Data

A primary objective in quantitative risk or safety assessment is characterization of the severity and likelihood of an adverse effect caused by a chemical toxin or pharmaceutical agent. In many cases data are not available at low doses or low exposures to the agent, and inferences at those doses must be based on the high-dose data. A modern method for making low-dose inferences is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this short note, we discuss approaches for doing so with quantal response data.

A mathematical model for the absorption and metabolism of formaldehyde vapour by humans

Epidemiological studies of occupational exposure to formaldehyde gas (HCHO) have suggested possible links between concentration and duration of exposure, and elevated risks of leukaemia and other cancers at sites distant from the site of contact. Formaldehyde is a highly water soluble gas which, when inhaled, reacts rapidly at the site of contact and is quickly metabolised by enzymes in the respiratory tissue. Inhaled formaldehyde is almost entirely absorbed in the respiratory tract and, for formaldehyde induced toxicity to occur at distant sites, HCHO must enter the blood and be transported to systemic tissues via the circulatory system. A mathematical model describing the absorption and removal of inhaled formaldehyde in the nasal tissue is therefore formulated to predict the proportion of formaldehyde entering into the blood. Accounting for the spatial distribution of the formaldehyde concentration and the metabolic activity within the mucosa, the concentration of formaldehyde in the mucus, the epithelium and the blood has been determined and was found to attain a steady-state profile within a few seconds of exposure. The increase of the formaldehyde concentration in the blood was predicted to be insignificant compared with the existing pre-exposure levels in the body, indicating that formaldehyde is rapidly removed in the nasal tissue. The results of the model thus suggest that it is highly unlikely that following inhalation by the nose, formaldehyde itself will cause toxicity at sites other than the initial site of contact in the respiratory tract.

Physiologically-based pharmacokinetic and toxicokinetic models in cancer risk assessment

Physiologically-based pharmacokinetic (PBPK) and toxicokinetic models are increasingly being used for the conduct of high dose to low dose and interspecies extrapolations required in cancer risk assessment. These models, by simulating tissue dose of toxic chemicals, help address the uncertainty associated with the default approaches for interspecies and high dose to low dose extrapolations. The applicability of PBPK models in cancer risk assessment has been demonstrated with a number of chemicals (e.g., acrylonitrile, 2-butoxyethanol, chloroform, 1,4-dioxane, methyl chloroform, methylene chloride, styrene, trichloroethylene, tetrachloroethylene, vinyl chloride, vinyl acetate). Recent advances in PBPK modeling facilitate the consideration of population distribution of parameter values, age-dependent changes in physiology and metabolism, multi-route exposures as well as multichemical interactions for application in cancer risk assessment. Whereas the average values for various input parameters have been used to evaluate the age-dependency of tissue dose, the Markov Chain Monte Carlo technique can be applied to address variability and uncertainty in parameter estimates, thus facilitating a more accurate estimation of cancer risk in the population. The PBPK models also uniquely facilitate the simulation of tissue dose, and thereby cancer risks, associated with multi-route and multichemical exposure situations. Overall, the recent advances reviewed in this article point to the continued enhancement of the scientific basis and applicability of PBPK models in cancer risk assessment.