Data-derived safety factors for the evaluation of food additives and environmental contaminants

Propiedades tecnológicas y regulación de los edulcorantes de alta intensidad en la Unión Europea Technological properties and regulatory status of high intensity sweeteners in the European Union

The European regulation of sweeteners has recently been changed with the publication and implementation by Member States of Directive 94/35/EC, which authorizes the use of six bulk sweeteners and six intense sweeteners for the formulation of reduced energy and/or non-sugar-added foods. An update of the technological properties of the high intensity sweeteners presently authorized in the EU is presented. We also report on the use of sweetener combinations as a means to optimize the sensory properties of the finished product and reduce sweetening costs.

A harmonization effort for acceptable daily exposure derivation - Considerations for application of adjustment factors

Acceptable daily exposures (ADEs) are established to determine the quantity of one drug substance that can contaminate another drug product without causing harm to the patient. An important part in setting an ADE for a drug substance, after identification of the unwanted critical effect(s) of the compound (see Bercu et al., 2016, this issue), is the determination of an appropriate overall margin of safety that is need to be maintained below the dose causing a certain critical effect (i.e., the point of departure or PoD). The overall margin of safety used to protect the general patient population from critical effects is derived as the product (i.e., composite adjustment factor) of various individual factors that account for variability and uncertainty in extrapolating from the PoD to an ADE. These factors address the considerations of interindividual variability, interspecies extrapolation, LOAEL-to-NOAEL extrapolation, exposure duration adjustment, effect severity, and database completeness. The factors are considered individually, but are not necessarily independent and their interdependence should be identified, with subsequent adjustment to the composite factor, as appropriate. It is important to identify all sources of variability and uncertainty pertinent to the derivation of the ADE and ensure each is considered in the assessment, at least by one of the adjustment factors. This manuscript highlights the basis for and selection of factors that address variability and uncertainty as used in the guidance documents on setting ADEs or other related health-based limits.

Predicting points of departure for risk assessment based on in vitro cytotoxicity data and physiologically based kinetic (PBK) modeling: The case of kidney toxicity induced by aristolochic acid I

Aristolochic acids are naturally occurring nephrotoxins. This study aims to investigate whether physiologically based kinetic (PBK) model-based reverse dosimetry could convert in vitro concentration-response curves of aristolochic acid I (AAI) to in vivo dose response-curves for nephrotoxicity in rat, mouse and human. To achieve this extrapolation, PBK models were developed for AAI in these different species. Subsequently, concentration-response curves obtained from in vitro cytotoxicity models were translated to in vivo dose-response curves using PBK model-based reverse dosimetry. From the predicted in vivo dose-response curves, points of departure (PODs) for risk assessment could be derived. The PBK models elucidated species differences in the kinetics of AAI with the overall catalytic efficiency for metabolic conversion of AAI to aristolochic acid Ia (AAIa) being 2-fold higher for rat and 64-fold higher for mouse than human. Results show that the predicted PODs generally fall within the range of PODs derived from the available in vivo studies. This study provides proof of principle for a new method to predict a POD for in vivo nephrotoxicity by integrating in vitro toxicity testing with in silico PBK model-based reverse dosimetry.

Uncertainty and variability in human exposure limits - a chemical-specific approach for ciprofloxacin and methotrexate

Human exposure limits (HELs) for chemicals with a toxicological threshold are traditionally derived using default assessment factors that account for variations in exposure duration, species sensitivity and individual sensitivity. The present paper elaborates a probabilistic approach for human hazard characterization and the derivation of HELs. It extends the framework for evaluating and expressing uncertainty in hazard characterization recently proposed by WHO-IPCS, i.e. by the incorporation of chemical-specific data on human variability in toxicokinetics. The incorporation of human variability in toxicodynamics was based on the variation between adverse outcome pathways (AOPs). Furthermore, sources of interindividual variability and uncertainty are propagated separately throughout the derivation process. The outcome is a two-dimensional human dose distribution that quantifies the population fraction exceeding a pre-selected critical effect level with an estimate of the associated uncertainty. This enables policy makers to set separate standards for the fraction of the population to be protected and the confidence level of the assessment. The main sources of uncertainty in the human dose distribution can be identified in order to plan new research for reducing uncertainty. Additionally, the approach enables quantification of the relative risk for specific subpopulations. The approach is demonstrated for two pharmaceuticals, i.e. the antibiotic ciprofloxacin and the antineoplastic methotrexate. For both substances, the probabilistic HEL is mainly influenced by uncertainty originating from: (1) the point of departure (PoD), (2) extrapolation from sub-acute to chronic toxicity and (3) interspecies extrapolation. However, when assessing the tails of the two-dimensional human dose distributions, i.e. the section relevant for the derivation of human exposure limits, interindividual variability in toxicodynamics also becomes important.

Uncertainties in human health risk assessment of environmental contaminants: A review and perspective

Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an 'adequate' protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making.

Evaluation of the experimental basis for assessment factors to protect individuals with asthma from health effects during short-term exposure to airborne chemicals

BACKGROUND

Asthmatic individuals constitute a large sub-population that is often considered particularly susceptible to the deleterious effects of inhalation of airborne chemicals. However, for most such chemicals information on asthmatics is lacking and inter-individual assessment factors (AFs) of 3-25 have been proposed for use in the derivation of health-based guideline values.

OBJECTIVE

To evaluate available information in attempt to determine whether a general difference in airway response during short-term exposure between healthy and asthmatic individuals can be identified, and whether current AFs for inter-individual variability provide sufficient protection for asthmatics.

METHODS

After performing systematic review of relevant documents and the scientific literature estimated differential response factors (EDRF) were derived as the ratio between the lowest observed adverse effect levels for healthy and asthmatic subjects based on studies in which both groups were tested under the same conditions. Thereafter, the concentration-response relationships for healthy and asthmatic subjects exposed separately to four extensively tested chemicals (nitrogen dioxide, ozone, sulfuric acid, sulfur dioxide) were compared on the basis of combined data. Finally, a Benchmark Concentration (BMC) analysis was performed for sulfur dioxide.

RESULTS

We found evidence of higher sensitivity among asthmatics (EDRF > 1) to 8 of 19 tested chemicals, and to 3 of 11 mixtures. Thereafter, we confirmed the higher sensitivity of asthmatics to sulfuric acid and sulfur dioxide. No difference was observed in the case of ozone and nitrogen dioxide. Finally, our BMC analysis of sulfur dioxide indicated a ninefold higher sensitivity among asthmatics.

CONCLUSION

Although experimental data are often inconclusive, our analyses suggest that an AF of 10 is adequate to protect asthmatics from the deleterious respiratory effects of airborne chemicals.

Towards a non-animal risk assessment for anti-androgenic effects in humans

Toxicology testing is undergoing a transformation from a system based on high-dose studies in laboratory animals to one founded primarily on in vitro methods that evaluate changes in normal cellular signalling pathways using human-relevant cells or tissues. We review the tools and approaches that could be used to develop a non-animal safety assessment for anti-androgenic effects in humans, with a focus on the molecular initiating events (MIEs) that human disorders indicate critical for normal functioning of the hypothalamus-pituitary-testicular (HPT) axis. In vitro test systems exist which can be used to characterize the effects of test chemicals on some MIEs such as androgen receptor antagonism, inhibition of steroidogenic enzymes or 5α-reductase inhibition. When used alongside information describing the pharmacokinetics of a specific chemical exposure, these could be used to inform a pathways-based safety assessment. However, some parts of the HPT axis such as events occurring in the hypothalamus or pituitary are not well represented by accepted in vitro methods. In vitro tools to characterize perturbations in these events need to be developed before a fully integrated model of the HPT axis can be described. Knowledge gaps also exist which prevent us from using in vitro data to predict the type and severity of in vivo effect(s) that could arise from a given level of in vitro anti-androgenic activity. This means that more work is needed to reliably link an MIE with an adverse outcome. However, especially for chemicals with low anti-androgenic activity, human exposure data can be used to put in vitro mode of action data into context for risk-based safety decision-making.

Interspecies uncertainty in molecular responses and toxicity of mixtures

Most of the experimental toxicity testing data for chemicals are generated through the use of laboratory animals, namely, rodents such as rats and mice or other species. Interspecies extrapolation is needed to nullify the differences between species so as to use such data for human health/risk assessment. Thus, understanding of interspecies differences is important in extrapolating the laboratory results to humans and conducting human risk assessments based on current credible scientific knowledge. Major causes of interspecies differences in anatomy and physiology, toxicokinetics, injury repair, molecular receptors, and signal transduction pathways responsible for variations in responses to toxic chemicals are outlined. In the risk assessment process, uncertainty associated with data gaps in our knowledge is reflected by application of uncertainty factors for interspecies differences. Refinement of the risk assessment methods is the ultimate goal as we strive to realistically evaluate the impact of toxic chemicals on human populations. Using specific examples from current risk assessment practice, this chapter illustrates the integration of interspecies differences in evaluation of individual chemicals and chemical mixtures.

Assessment of health risks resulting from early-life exposures: Are current chemical toxicity testing protocols and risk assessment methods adequate?

Abstract Over the last couple of decades, the awareness of the potential health impacts associated with early-life exposures has increased. Global regulatory approaches to chemical risk assessment are intended to be protective for the diverse human population including all life stages. However, questions persist as to whether the current testing approaches and risk assessment methodologies are adequately protective for infants and children. Here, we review physiological and developmental differences that may result in differential sensitivity associated with early-life exposures. It is clear that sensitivity to chemical exposures during early-life can be similar, higher, or lower than that of adults, and can change quickly within a short developmental timeframe. Moreover, age-related exposure differences provide an important consideration for overall susceptibility. Differential sensitivity associated with a life stage can reflect the toxicokinetic handling of a xenobiotic exposure, the toxicodynamic response, or both. Each of these is illustrated with chemical-specific examples. The adequacy of current testing protocols, proposed new tools, and risk assessment methods for systemic noncancer endpoints are reviewed in light of the potential for differential risk to infants and young children.

The Scientific Basis of Uncertainty Factors Used in Setting Occupational Exposure Limits

The uncertainty factor concept is integrated into health risk assessments for all aspects of public health practice, including by most organizations that derive occupational exposure limits. The use of uncertainty factors is predicated on the assumption that a sufficient reduction in exposure from those at the boundary for the onset of adverse effects will yield a safe exposure level for at least the great majority of the exposed population, including vulnerable subgroups. There are differences in the application of the uncertainty factor approach among groups that conduct occupational assessments; however, there are common areas of uncertainty which are considered by all or nearly all occupational exposure limit-setting organizations. Five key uncertainties that are often examined include interspecies variability in response when extrapolating from animal studies to humans, response variability in humans, uncertainty in estimating a no-effect level from a dose where effects were observed, extrapolation from shorter duration studies to a full life-time exposure, and other insufficiencies in the overall health effects database indicating that the most sensitive adverse effect may not have been evaluated. In addition, a modifying factor is used by some organizations to account for other remaining uncertainties-typically related to exposure scenarios or accounting for the interplay among the five areas noted above. Consideration of uncertainties in occupational exposure limit derivation is a systematic process whereby the factors applied are not arbitrary, although they are mathematically imprecise. As the scientific basis for uncertainty factor application has improved, default uncertainty factors are now used only in the absence of chemical-specific data, and the trend is to replace them with chemical-specific adjustment factors whenever possible. The increased application of scientific data in the development of uncertainty factors for individual chemicals also has the benefit of increasing the transparency of occupational exposure limit derivation. Improved characterization of the scientific basis for uncertainty factors has led to increasing rigor and transparency in their application as part of the overall occupational exposure limit derivation process.

Risk Assessment of residual monomer migrating from acrylic polymers and causing Allergic Contact Dermatitis during normal handling and use

Acrylic, Poly Methyl Methacrylate (PMMA) based polymers are found in many industrial, professional and consumer products and are of low toxicity, but do contain very low levels of residual monomers and process chemicals that can leach out during handling and use. Methyl Methacrylate, the principle monomer is of low toxicity, but is a recognized weak skin sensitizer. The risk of induction of contact allergy in consumers was determined using a method based upon the Exposure-based Quantitative Risk Assessment approach developed for fragrance ingredients. The No Expected Sensitization Induction Level (NESIL) was based on the threshold to induction of sensitization (EC3) in the Local Lymph Node Assay (LLNA) since no Human Repeat Insult Patch Test (HRIPT) data were available. Categorical estimation of Consumer Exposure Level was substituted with a worst case assumption based upon the quantitative determination of MMA monomer migration into simulants. Application of default and Chemical-Specific Adjustment Factors results in a Risk Characterization Ratio (RCR) of 10,000 and a high Margin of Safety for induction of Allergic Contact Dermatitis (ACD) in consumers handling polymers under conservative exposure conditions. Although there are no data available to derive a RCR for elicitation of ACD it is likely to be lower than that for induction.

Risk assessment of shellfish toxins

Complex secondary metabolites, some of which are highly toxic to mammals, are produced by many marine organisms. Some of these organisms are important food sources for marine animals and, when ingested, the toxins that they produce may be absorbed and stored in the tissues of the predators, which then become toxic to animals higher up the food chain. This is a particular problem with shellfish, and many cases of poisoning are reported in shellfish consumers each year. At present, there is no practicable means of preventing uptake of the toxins by shellfish or of removing them after harvesting. Assessment of the risk posed by such toxins is therefore required in order to determine levels that are unlikely to cause adverse effects in humans and to permit the establishment of regulatory limits in shellfish for human consumption. In the present review, the basic principles of risk assessment are described, and the progress made toward robust risk assessment of seafood toxins is discussed. While good progress has been made, it is clear that further toxicological studies are required before this goal is fully achieved.

Characterization of the human kinetic adjustment factor for the health risk assessment of environmental contaminants

A default uncertainty factor of 3.16 (√10) is applied to account for interindividual variability in toxicokinetics when performing non-cancer risk assessments. Using relevant human data for specific chemicals, as WHO/IPCS suggests, it is possible to evaluate, and replace when appropriate, this default factor by quantifying chemical-specific adjustment factors for interindividual variability in toxicokinetics (also referred to as the human kinetic adjustment factor, HKAF). The HKAF has been determined based on the distributions of pharmacokinetic parameters (e.g., half-life, area under the curve, maximum blood concentration) in relevant populations. This article focuses on the current state of knowledge of the use of physiologically based algorithms and models in characterizing the HKAF for environmental contaminants. The recent modeling efforts on the computation of HKAF as a function of the characteristics of the population, chemical and its mode of action (dose metrics), as well as exposure scenario of relevance to the assessment are reviewed here. The results of these studies, taken together, suggest the HKAF varies as a function of the sensitive subpopulation and dose metrics of interest, exposure conditions considered (route, duration, and intensity), metabolic pathways involved and theoretical model underlying its computation. The HKAF seldom exceeded the default value of 3.16, except in very young children (i.e., <≈ 3 months) and when the parent compound is the toxic moiety. Overall, from a public health perspective, the current state of knowledge generally suggest that the default uncertainty factor is sufficient to account for human variability in non-cancer risk assessments of environmental contaminants.

Advancing human health risk assessment: integrating recent advisory committee recommendations

Over the last dozen years, many national and international expert groups have considered specific improvements to risk assessment. Many of their stated recommendations are mutually supportive, but others appear conflicting, at least in an initial assessment. This review identifies areas of consensus and difference and recommends a practical, biology-centric course forward, which includes: (1) incorporating a clear problem formulation at the outset of the assessment with a level of complexity that is appropriate for informing the relevant risk management decision; (2) using toxicokinetics and toxicodynamic information to develop Chemical Specific Adjustment Factors (CSAF); (3) using mode of action (MOA) information and an understanding of the relevant biology as the key, central organizing principle for the risk assessment; (4) integrating MOA information into dose-response assessments using existing guidelines for non-cancer and cancer assessments; (5) using a tiered, iterative approach developed by the World Health Organization/International Programme on Chemical Safety (WHO/IPCS) as a scientifically robust, fit-for-purpose approach for risk assessment of combined exposures (chemical mixtures); and (6) applying all of this knowledge to enable interpretation of human biomonitoring data in a risk context. While scientifically based defaults will remain important and useful when data on CSAF or MOA to refine an assessment are absent or insufficient, assessments should always strive to use these data. The use of available 21st century knowledge of biological processes, clinical findings, chemical interactions, and dose-response at the molecular, cellular, organ and organism levels will minimize the need for extrapolation and reliance on default approaches.

Dispelling urban myths about default uncertainty factors in chemical risk assessment--sufficient protection against mixture effects?

Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an incentive to generate better data and recommend adopting a pragmatic, but scientifically better founded approach to mixture risk assessment.

Fish, contaminants and human health: quantifying and weighing benefits and risks

This paper describes a quantitative risk-benefit assessment of fish consumption. We compare the net health effect expressed in DALYs of two scenarios. The reference scenario is the current fish intake of the Dutch population, which is less than what is recommended by the health authorities. The alternative scenario describes the health effects if the population consumes 200g of fish per week, which is close to the recommendation. All health effects due to fish consumption for which there is convincing evidence are incorporated in the assessment. The QALIBRA software (www.qalibra.eu) is used to simulate the two scenarios. The results show there is a net benefit for the population if it consumes 200g of fish each week.

Assessing the application of acute toxic gas standards

OBJECTIVE

In this paper, we compare acute toxic gas standards developed for occupational, military, and civilian use that predict or establish guidelines for limiting exposure to inhaled toxic gases.

CONTEXT

Large disparities between guidelines exist for similar exposure scenarios, raising questions about why differences exist, as well as the applicability of each standard. The motivation and rationale behind the development of the standards is explored with emphasis on the experimental data used to set the standards.

METHODS

The Toxic Gas Assessment Software (TGAS) is used to quantitatively compare current acute exposure standards, such as: Acute Exposure Guidelines (AEGL), Immediate Danger to Life or Health (IDLH), Purser, International Organization for Standardization (ISO 13571), and Federal Aviation Administration (FAA). The TGAS software does this by calculating the body-mass-normalized internal doses of each gas exposure in each standard, which is then plotted on a cumulative distribution function for a normal or susceptible population to visualize the relationship of the standards to each other. To focus the comparison, acute toxic gas standards for five common fire gases, carbon monoxide (CO), hydrogen cyanide (HCN), hydrogen chloride (HCl), nitrogen dioxide (NO₂), and acrolein (C₃H₄O), are explored.

RESULTS

It was found that differences between standards can be reconciled when the target population, effect endpoint, and incidence level are taken into account.

CONCLUSION

By analyzing the standards with respect to these factors, we can acquire a better understanding of the applicability of each.

State of the art in benefit-risk analysis: food and nutrition

Benefit-risk assessment in food and nutrition is relatively new. It weighs the beneficial and adverse effects that a food (component) may have, in order to facilitate more informed management decisions regarding public health issues. It is rooted in the recognition that good food and nutrition can improve health and that some risk may be acceptable if benefit is expected to outweigh it. This paper presents an overview of current concepts and practices in benefit-risk analysis for food and nutrition. It aims to facilitate scientists and policy makers in performing, interpreting and evaluating benefit-risk assessments. Historically, the assessments of risks and benefits have been separate processes. Risk assessment is mainly addressed by toxicology, as demanded by regulation. It traditionally assumes that a maximum safe dose can be determined from experimental studies (usually in animals) and that applying appropriate uncertainty factors then defines the 'safe' intake for human populations. There is a minor role for other research traditions in risk assessment, such as epidemiology, which quantifies associations between determinants and health effects in humans. These effects can be both adverse and beneficial. Benefit assessment is newly developing in regulatory terms, but has been the subject of research for a long time within nutrition and epidemiology. The exact scope is yet to be defined. Reductions in risk can be termed benefits, but also states rising above 'the average health' are explored as benefits. In nutrition, current interest is in 'optimal' intake; from a population perspective, but also from a more individualised perspective. In current approaches to combine benefit and risk assessment, benefit assessment mirrors the traditional risk assessment paradigm of hazard identification, hazard characterization, exposure assessment and risk characterization. Benefit-risk comparison can be qualitative and quantitative. In a quantitative comparison, benefits and risks are expressed in a common currency, for which the input may be deterministic or (increasingly more) probabilistic. A tiered approach is advocated, as this allows for transparency, an early stop in the analysis and interim interaction with the decision-maker. A general problem in the disciplines underlying benefit-risk assessment is that good dose-response data, i.e. at relevant intake levels and suitable for the target population, are scarce. It is concluded that, provided it is clearly explained, benefit-risk assessment is a valuable approach to systematically show current knowledge and its gaps and to transparently provide the best possible science-based answer to complicated questions with a large potential impact on public health.

Proposal of new uncertainty factor application to derive tolerable daily intake

We propose new uncertainty factors (UFs) and a new subdivision of default factors in chemical risk assessment using a probabilistic approach based on the latest applicable information. Rounded values of 150 for mice, 100 for hamsters and rats, and 40 for rabbits, monkeys and dogs for inter- and intra-species differences (UF(AH)) were derived from the probabilistic combination of two log-normal distributions. Further calculation of additional UFs when chronic data (UF(S)) or NOAEL (UF(L)) are lacking was conducted using available log-normal distribution information. The alternative UF(S) and UF(L) values of 4 are considered to be appropriate for both cases where data are lacking. The default contributions of inter-species difference (UF(A)) and intra-species difference (UF(H)) to the UF(AH) of 100 for hamsters and rats as an example are considered to be 25 and 4, respectively. The UF(A) of 25 was subdivided into 25(0.6) (i.e., 7.0) for pharmacokinetics (PK) (UF(A,PK)) and 25(0.4) (i.e., 3.6) for pharmacodynamics (PD) (UF(A,PD)), and the UF(H) of 4 was evenly subdivided into 4(0.5) (i.e., 2) (UF(H,PK) and UF(H,PD)), to account for chemical-specific difference data between humans and laboratory animals for PK and/or PD. These default UFs, which come from actual experimental data, may be more appropriate than previous default UFs to derive tolerable daily intake values.

Characterizing the noncancer toxicity of mixtures using concepts from the TTC and quantitative models of uncertainty in mixture toxicity

This article explores the use of an approach for setting default values for the noncancer toxicity, developed as part of the Threshold of Toxicological Concern (TTC), for the evaluation of the chronic noncarcinogenic effects of certain chemical mixtures. Individuals are exposed to many mixtures where there are little or no toxicological data on some or all of the mixture components. The approach developed in the TTC can provide a basis for conservative estimates of the toxicity of the mixture components when compound-specific data are not available. The application of this approach to multiple chemicals in a mixture, however, has implications for the statistical assumptions made in developing component-based estimates of mixtures. Specifically, conservative assumptions that are appropriate for one compound may become overly conservative when applied to all components of a mixture. This overestimation can be investigated by modeling the uncertainty in toxicity standards. In this article the approach is applied to both hypothetical and actual examples of chemical mixtures and the potential for overestimation is investigated. The results indicate that the use of the approach leads to conservative estimates of mixture toxicity and therefore its use is most appropriate for screening assessments of mixtures.

Physiological modeling and derivation of the rat to human toxicokinetic uncertainty factor for the carbamate pesticide aldicarb

Aldicarb (ALD, 2-methyl-2-(methylthio)-propionalaldehyde O-(methyl-carbamoyl) oxime, Temik) is widely used as an insecticide, nematocide and acaricide and it is oxidized to aldicarb sulfoxide (ALX) and aldicarb sulfone (ALU). Neither a toxicokinetic model nor an estimate of the target tissue dose of ALD and its metabolites in exposed organisms is available. The objective of this study was: (i) to develop a physiologically based toxicokinetic (PBTK) model for ALD in the rat and humans, and (ii) to determine the interspecies toxicokinetic uncertainty factor (UF(AH-TK)) of ALD. The model consists of a series of mass balance differential equations that describe the time course behavior of ALD in blood, liver, kidney, lungs, brain, fat, and rest of the body compartments. The physiological parameters of the model (blood flow rates, cardiac output, and tissue volumes) were obtained from the literature, while the maximum velocity (mg/kg/min) and the Michaelis constant (mg/l) for ALD oxidation in rats and humans were determined by in vitro AH-TK microsomal assays. The estimation of the tissue:blood partition coefficient was accomplished within the PBTK model by representing the tissues as a composite of neutral lipids, phospholipids and water, and providing the vegetable oil:water partition coefficient as input parameter. The validity of the rat PBTK model was assessed by comparing the model simulations of ALX time course blood concentrations and the inhibition patterns of acetylcholinesterase (AChE) in erythrocytes and plasma obtained by administering rats ALD (0.1 and 0.4 mg/kg, iv). The human PBTK model was validated by comparing the simulations of AChE inhibition patterns in blood with human experimental data obtained from oral administrations of ALD. The UF(AH-TK) for ALD was determined by dividing the areas under the blood and brain concentration vs time curve (AUCCV, AUCCBR) for ALD and ALX in the rat and in human exposed to the same dose. The results indicate that with respect to parent chemical, equivalent applied doses in rats and humans result in a 9.5-fold difference in the AUC(CV) and AUC(AH-TK) respectively, in the two species, and 17-fold difference in the AUC(CV) and AUC(CBR) with respect to the metabolite. In other words, in order to have toxicokinetic equivalence in rats and humans, the former species must be exposed to a dose that is 9.5 and 17 times higher than the human with respect to the parent chemical and the metabolite respectively. Overall, the present study demonstrates the applicability of PBTK models in the quantitative evaluation of UH(AH-TK), and shows that their current default values are inaccurate, at least with respect to ALD, which has potential negative implications in the alleged protection of risk estimates derived from them.

Mycotoxins and child health: the need for health risk assessment

The occurrences of mycotoxins as food contaminants in different localities particularly in developing countries and the inevitable exposure of populations and children to these toxins with probable adverse outcomes need be scientifically and systematically assessed. Health risk assessment developed in the 1980s is separate from risk management, both with risk communication form the risk analysis framework adopted by the World Health Organization. The process contributes increasingly to policy development, public health decision making, the establishment of mycotoxin regulations and research planning. However, the exercise of the risk assessment structured approach is not simple and is faced up to lack of data, capable infrastructure facilities and need for trained personnel and resources. Furthermore, adopted methodologies need be developed focusing on child characteristics and health concerns.

Transport and dynamics of toxic pollutants in the natural environment and their effect on human health: research gaps and challenge

The source-pathway-receptor (SPR) approach to human exposure and risk assessment contains considerable uncertainty when using the refined modelling approaches to pollutant transport and dispersal, not least in how compounds of concern might be prioritized, proxy or indicator substances identified and the basic environmental and toxicological data collected. The impact of external environmental variables, urban systems and lifestyle is still poorly understood. This determines exposure of individuals and there are a number of methods being developed to provide more reliable spatial assessments. Within the human body, the dynamics of pollutants and effects on target organs from diffuse, transient sources of exposure sets ambitious challenges for traditional risk assessment approaches. Considerable potential exists in the application of, e.g. physiologically based pharmacokinetic (PBPK) models. The reduction in uncertainties associated with the effects of contaminants on humans, transport and dynamics influencing exposure, implications of adult versus child exposure and lifestyle and the development of realistic toxicological and exposure data are all highlighted as urgent research needs. The potential to integrate environmental with toxicological models provides the next phase of research opportunity and should be used to drive empirical and model assessments.

Interspecies extrapolation in environmental exposure standard setting: A Bayesian synthesis approach

Currently the extrapolation of evidence from studies of non-human species to the setting of environmental exposure standards for humans includes the imposition of a variety of uncertainty factors reflecting unknown aspects of the procedure, including the relevance of evidence from one species to impacts in another. This paper develops and explores more flexible modelling of aspects of this extrapolation, using models proposed by DuMouchel [DuMouchel, W.H., Harris, J.E., 1983. Bayes methods for combining the results of cancer studies in humans and other species (with comment). J. Am. Statist. Assoc. 78, 293-308.] The approaches are based on Bayesian meta-analysis methods involving explicit modelling of relevance in the prior distributions, estimated using Markov chain Monte Carlo (MCMC) methods. The methods are applied to evidence relating chlorinated by-products exposure to adverse reproductive health effects. The relative merits of various approaches are discussed, and developments and next steps are outlined.

On the incorporation of chemical-specific information in risk assessment

This paper describes the evolution of chemical risk assessment from its early dependence on generic default approaches to the current situation in which mechanistic and biokinetic data are routinely incorporated to support a more chemical-specific approach. Two methodologies that have played an important role in this evolution are described: mode-of-action evaluation and physiologically based biokinetic (PBBK) modelling. When used together, these techniques greatly increase the opportunity for the incorporation of biokinetic and mechanistic data in risk assessment. The resulting risk assessment approaches are more appropriately tailored to the specific chemical and are more likely to provide an accurate assessment of the potential hazards associated with human exposures. The appropriate application of PBBK models in risk assessment demands well-formulated statements about the chemical mode of action. It is this requirement for an explicit, mechanistic hypothesis that gives biologically motivated models their power, but at the same time serves as the greatest impediment to the acceptance of a chemical-specific risk assessment approach by regulators. The chief impediment to the regulatory acceptance and application of PBBK models in risk assessment is concern about uncertainties associated with their use. To some extent such concerns can be addressed by the development of generally accepted approaches for model evaluation and quantitative uncertainty analysis. In order to assure the protection of public health while limiting the economic and social consequences of over-regulation, greater dialogue between researchers and regulators is crucially needed to foster an increased use of emerging scientific information and innovative methods in chemical risk assessments.

Computational models of ethanol-induced neurodevelopmental toxicity across species: Implications for risk assessment

Computational, systems-based approaches can provide a quantitative construct for evaluating risk in the context of mechanistic data. Previously, we developed computational models for the rat, mouse, rhesus monkey, and human, describing the acquisition of adult neuron number in the neocortex during the key neurodevelopmental processes of neurogenesis and synaptogenesis. Here we apply mechanistic data from the rat describing ethanol-induced toxicity in the developing neocortex to evaluate the utility of these models for analyzing neurodevelopmental toxicity across species. Our model can explain long-term neocortical neuronal loss in the rodent model after in utero exposure to ethanol based on inhibition of proliferation during neurogenesis. Our human model predicts a significant neuronal deficit after daily peak BECs reaching 10-20 mg/dl, which is the approximate BEC reached after drinking one standard drink within one hour. In contrast, peak daily BECs of 100 mg/dl are necessary to predict similar deficits in the rat. Our model prediction of increased sensitivity of primate species to ethanol-induced inhibition of proliferation is based on application of in vivo experimental data from primates showing a prolonged rapid growth period in the primate versus rodent neuronal progenitor population. To place our predictions into a broader context, we evaluate the evidence for functional low-dose effects across rats, monkeys, and humans. Results from this critical evaluation suggest subtle effects are evident at doses causing peak BECs of approximately 20 mg/dl daily, corroborating our model predictions. Our example highlights the utility of a systems-based modeling approach in risk assessment.

Estimation of interindividual pharmacokinetic variability factor for inhaled volatile organic chemicals using a probability-bounds approach

The derivation of reference concentrations (RfCs) for systemically acting volatile organic chemicals (VOCs) uses a default factor of 10 to account for the interindividual variability in pharmacokinetics (PK) and pharmacodynamics (PD). The magnitude of the PK component of the interindividual variability factor (IVF; also referred to as human kinetic adjustment factor (HKAF)) has previously been estimated using Monte Carlo approaches and physiologically based pharmacokinetic (PBPK) models. Since the RfC derivation considers continuous lifetime human exposure to VOCs in the environment, algorithms to compute steady-state internal dose (SS-ID), such as steady-state arterial blood concentration (Ca) and the steady-state rate of amount metabolized (RAM), can be used to derive IVF-PKs. In this context, probability-bounds (P-bounds) approach is potentially useful for computing an interval of probability distribution of SS-ID from knowledge of population distribution of input parameters. The objective of this study was therefore to compute IVF-PK using the P-bounds approach along with an algorithm for SS-ID in an adult population exposed to VOCs. The existing steady-state algorithms, derived from PBPK models, were rewritten such that SS-ID could be related, without any interdependence, to the following input parameters: alveolar ventilation (Qp), hepatic blood flow (Ql), intrinsic clearance (CL(int)) and blood:air partition coefficient (Pb). The IVF-PK was calculated from the P-bounds of SS-ID corresponding to the 50th and 95th percentiles. Following either specification of probability distribution-free bounds (characterized by minimal, maximal, and mean values) or distribution-defined values (mean, standard deviation and shape of probability distribution where: Qp=lognormal, Ql=lognormal, CL(int)=lognormal and Pb=normal) in RAMAS Risk Calc software version 3.0 (Applied Biomathematics, Setauket, NY), the P-bound estimates of SS-ID for benzene, carbon tetrachloride, chloroform and methyl chloroform were obtained for low level exposures (1ppm). Using probability distribution-defined inputs, the IVF-PK for benzene, carbon tetrachloride, chloroform and methyl chloroform were, respectively, 1.18, 1.28, 1.24, and 1.18 (based on P-bounds for Ca), and 1.31, 1.58, 1.30, and 1.24 (based on P-bounds for RAM). A validation of the P-bounds computation was performed by comparing the results with those obtained using Monte Carlo simulation of the steady-state algorithms. In data-poor situations, when the statistical distributions for all input parameters were not known or available, the P-bounds approach allowed the estimation of IVF-PK. The use of P-bounds method along with steady-state algorithms, as done in this study for the first time, is a practical and scientifically sound way of computing IVF-PKs for systemically acting VOCs.

Assessment factors--applications in health risk assessment of chemicals

We review the scientific basis for default assessment factors used in risk assessment of nongenotoxic chemicals including the use of chemical- and pathways specific assessment factors, and extrapolation approaches relevant to species differences, age and gender. One main conclusion is that the conventionally used default factor of 100 does not cover all inter-species and inter-individual differences. We suggest that a species-specific default factor based on allometric scaling should be used for inter-species extrapolation (basal metabolic rate). Regarding toxicodynamic and remaining toxicokinetic differences we suggest that a percentile from a probabilistic distribution is chosen to derive the assessment factor. Based on the scarce information concerning the human-to-human variability it is more difficult to suggest a specific assessment factor. However, extra emphasis should be put on sensitive populations such as neonates and genetically sensitive subgroups, and also fetuses and children which may be particularly vulnerable during development and maturation. Factors that also need to be allowed for are possible gender differences in sensitivity, deficiencies in the databases, nature of the effect, duration of exposure, and route-to-route extrapolation. Since assessment factors are used to compensate for lack of knowledge we feel that it is prudent to adopt a "conservative" approach, erring on the side of protectiveness.