Human variability in the renal elimination of foreign compounds and renal excretion-related uncertainty factors for risk assessment

Distributions for time, inter‐ and intraspecies extrapolation for deriving occupational exposure limits

This work aimed at improving the empirical database of time (i.e., exposure duration), interspecies and intraspecies extrapolation when deriving occupational exposure limits (OELs). For each extrapolation step, a distribution was derived, which can be used to model the associated uncertainties. For time and interspecies extrapolation, distributions of ratios of dose descriptors were derived from studies of different length or species. National Toxicology Program (NTP) study data were manually assessed, and data from REACH (Registration, Evaluation and Authorisation of Chemicals) registration dossiers were evaluated semi‐automatically. Intraspecies extrapolation was investigated by compiling published studies on human toxicokinetic and toxicodynamic variability. A new database was established for toxicokinetic differences in interindividual susceptibility, including many inhalation studies. Using NTP data produced more reliable results than using REACH data. The geometric mean (GM) for time extrapolation subacute/chronic agreed with previous evaluations (GM = 4.11), whereas the GM for subchronic/chronic extrapolation was slightly higher (GM = 2.93) than the GMs found by others. No significant differences were observed between systemically and locally acting substances. Observed interspecies differences confirmed the suitability of allometric scaling, with the derived distribution describing remaining uncertainty. Distributions of intraspecies variability at the 1% and 5% incidence level had medians of 7.25 and 3.56, respectively. When compared with assessment factors (AFs) currently used in the EU, probabilities that these AFs are protective enough span a wide range from 10% to 95%, depending on the extrapolation step. These results help to select AFs in a transparent and informed way and, by allowing to compare protection levels achieved, to harmonise methods for deriving OELs.

This work aimed at improving the empirical database of time (i.e., exposure duration), interspecies and intraspecies extrapolation. Distributions were derived, which can be used to model the associated uncertainties. When compared with assessment factors (AFs) currently used in the EU, probabilities that these AFs are protective enough span a wide range from 10% to 95%, depending on the extrapolation step. These results help to select AFs in a transparent and informed way and to harmonise methods for deriving OELs.

Estimation of toluene exposure in air from BMA (S-benzylmercapturic acid) urinary measures using a reverse dosimetry approach based on physiologically pharmacokinetic modeling

This study aimed to use a reverse dosimetry PBPK modeling approach to estimate toluene atmospheric exposure from urinary measurements of S-benzylmercapturic acid (BMA) in a small group of individuals and to evaluate the uncertainty associated to urinary spot-sampling compared to 24-h collected urine samples. Each exposure assessment technique was developed namely to estimate toluene air exposure from BMA measurements in 24-h urine samples (24-h-BMA) and from distributions of daily urinary BMA spot measurements (DUBSM). Model physiological parameters were described based upon age, weight, size and sex. Monte Carlo simulations with the PBPK model allowed converting DUBSM distribution (and 24-h-BMA) into toluene air levels. For the approach relying on DUBSM distribution, the ratio between the 95% probability of predicted toluene concentration and its 50% probability in each individual varied between 1.2 and 1.4, while that based on 24-h-BMA varied between 1.0 and 1.1. This suggests more variability in estimated exposure from spot measurements. Thus, estimating toluene exposure based on DUBSM distribution generated about 20% more uncertainty. Toluene levels estimated (0.0078-0.0138 ppm) are well below Health Canada's maximum chronic air guidelines. PBPK modeling and reverse dosimetry may be combined to interpret urinary metabolites data of VOCs and assess related uncertainties.

Inter-phenotypic differences in CYP2C9 and CYP2C19 metabolism: Bayesian meta-regression of human population variability in kinetics and application in chemical risk assessment

Quantifying variability in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. In this context, genetic polymorphisms in cytochromes P450 (CYPs) drive inter-phenotypic differences and may result in reduction or increase in metabolism of drugs or other xenobiotics. Here, an extensive literature search was performed to identify PK data for probe substrates of the human polymorphic isoforms CYP2C9 and CYP2C19. Relevant data from 158 publications were extracted for markers of chronic exposure (clearance and area under the plasma concentration-time curve) and analysed using a Bayesian meta-regression model. Enzyme function (EF), driven by inter-phenotypic differences across a range of allozymes present in extensive and poor metabolisers (EMs and PMs), and fraction metabolised (Fm), were identified as exhibiting the highest impact on the metabolism. The Bayesian meta-regression model provided good predictions for such inter-phenotypic differences. Integration of population distributions for inter-phenotypic differences and estimates for EF and Fm allowed the derivation of CYP2C9- and CYP2C19-related UFs which ranged from 2.7 to 12.7, and were above the default factor for human variability in TK (3.16) for PMs and major substrates (Fm >60%). These results provide population distributions and pathway-related UFs as conservative in silico options to integrate variability in CYP2C9 and CYP2C19 metabolism using in vitro kinetic evidence and in the absence of human data. The future development of quantitative extrapolation models is discussed with particular attention to integrating human in vitro and in vivo PK or TK data with pathway-related variability for chemical risk assessment.

Precision Dosing Management with Intelligent Computing in Digital Health

Pediatric dosing is not only critical for successful pediatric trials in drug development but also paramount to safety and effective treatment at bedside. Due to the complex pharmacokinetic of children compared to adults, several challenges are posed in managing dosing precisely during drug development and after drug approval to clinicians. In particular, given the real-world practice, understanding the impact of development on the dose-exposure-response relationship is essential in optimizing the dosing to children of different ages. In this paper we propose a novel intelligent computing framework to examine how the growth and maturation create size- and age-dependent variability in pharmacokinetics and pharmacodynamics, and summarize the use of modeling-based approaches for dose finding in pediatric drug development, allowing clinicians to anticipate probable treatment effects and to have a higher likelihood of achieving optimal dose regimens early, as well as reducing the drug development cycling time and cost.

A Physiologically Based Pharmacokinetic Model of Ertapenem in Pediatric Patients With Renal Impairment

Ertapenem is a widely used antibiotic; however, its pharmacokinetics has not been fully evaluated in children with renal impairment. A physiologically based pharmacokinetic (PBPK) model of ertapenem was established and validated to simulate its disposition in the healthy population and adults with renal impairment, as well as to predict the exposure in pediatric patients with renal impairment. The simulated PBPK modeling results and the observed data of ertapenem after intravenous administration of various regimens were consistent according to the fold error values of less than 2. Furthermore, %T > MIC of ertapenem was evaluated using the PBPK model. The C_max was not significantly changed in pediatric patients with renal impairment compared to healthy children. However, the AUC was 1.42-fold, 1.84-fold, 2.37-fold, and 3.52-fold higher in mild, moderate, severe renal impairment, and end-stage renal disease, respectively, than that in healthy children and the doses of ertapenem were reduced to 13 mg/kg b.i.d, 9 mg/kg b.i.d, 6 mg/kg b.i.d, and 5 mg/kg b.i.d, respectively. The probability of achieving 40%T > MIC (MIC ≤ 4 μg/mL) was nearly 100% throughout the recommended dosing interval. In conclusion, our model can be used as a tool to generate better predictions for the most effective ertapenem dosing in pediatric patients.

Reverse dosimetry modeling of toluene exposure concentrations based on biomonitoring levels from the Canadian health measures survey

Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for age- and gender-related variability in internal dose. The objective of this study was to reconstruct air concentrations consistent with blood toluene measures reported in the third Canadian Health Measures Survey using reverse dosimetry PBPK modeling techniques. Population distributions of model's physiological parameters were described based upon age, weight, and size for four subpopulations (12-19, 20-39, 40-59, and 60-79 years old). Monte Carlo simulations applied to PBPK modeling allowed converting the distributions of venous blood measures of toluene obtained from CHMS into related air levels. Based upon blood levels observed at the 50^th, 90^th and 95^th percentiles, corresponding air toluene concentrations were estimated for teenagers aged 12-19 years as being, respectively, 0.009, 0.04 and 0.06 ppm. Similarly, values were computed for adults aged 20-39 years (0.007, 0.036, and 0.06 ppm), 40-59 years (0.007, 0.036 and 0.06 ppm) and 60-79 years (0.006, 0.022 and 0.04 ppm). These estimations are well below Health Canada's maximum recommended chronic air guidelines for toluene. In conclusion, PBPK modeling and reverse dosimetry may be combined to help interpret biomonitoring data for chemical exposure in large population surveys and estimate the associated toxicological health risk.

Biological fate of low-calorie sweeteners

With continued efforts to find solutions to rising rates of obesity and diabetes, there is increased interest in the potential health benefits of the use of low- and no-calorie sweeteners (LNCSs). Concerns about safety often deter the use of LNCSs as a tool in helping control caloric intake, even though the safety of LNCS use has been affirmed by regulatory agencies worldwide. In many cases, an understanding of the biological fate of the different LNSCs can help health professionals to address safety concerns. The objectives of this review are to compare the similarities and differences in the chemistry, regulatory status, and biological fate (including absorption, distribution, metabolism, and excretion) of the commonly used LNCSs: acesulfame potassium, aspartame, saccharin, stevia leaf extract (steviol glycoside), and sucralose. Understanding the biological fate of the different LNCSs is helpful in evaluating whether reports of biological effects in animal studies or in humans are indicative of possible safety concerns. Illustrations of the usefulness of this information to address questions about LNCSs include discussion of systemic exposure to LNCSs, the use of sweetener combinations, and the potential for effects of LNCSs on the gut microflora.

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.

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.

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.

Metabolism, variability and risk assessment

For non-genotoxic carcinogens, "thresholded toxicants", Acceptable/Tolerable Daily Intakes (ADI/TDI) represent a level of exposure "without appreciable health risk" when consumed everyday or weekly for a lifetime and are derived by applying an uncertainty factor of a 100-fold to a no-observed-adverse-effect-levels (NOAEL) or to a benchmark dose. This UF allows for interspecies differences and human variability and has been subdivided to take into account toxicokinetics and toxicodynamics with even values of 10(0.5) (3.16) for the human aspect. Ultimately, such refinements allow for chemical-specific adjustment factors and physiologically based models to replace such uncertainty factors. Intermediate to chemical-specific adjustment factors are pathway-related uncertainty factors which have been derived for phase I, phase II metabolism and renal excretion. Pathway-related uncertainty factors are presented here as derived from the result of meta-analyses of toxicokinetic variability data in humans using therapeutic drugs metabolised by a single pathway in subgroups of the population. Pathway-related lognormal variability was derived for each metabolic route. The resulting pathway-related uncertainty factors showed that the current uncertainty factor for toxicokinetics (3.16) would not cover human variability for genetic polymorphism and age differences (neonates, children, the elderly). Latin hypercube (Monte Carlo) models have also been developed using quantitative metabolism data and pathway-related lognormal variability to predict toxicokinetics variability and uncertainty factors for compounds handled by several metabolic routes. For each compound, model results gave accurate predictions compared to published data and observed differences arose from data limitations, inconsistencies between published studies and assumptions during model design and sampling. Finally, under the 6(th) framework EU project NOMIRACLE (http://viso.jrc.it/nomiracle/), novel methods to improve the risk assessment of chemical mixtures were explored (1) harmonization of the use of uncertainty factors for human and ecological risk assessment using mechanistic descriptors (2) use of toxicokinetics interaction data to derive UFs for chemical mixtures. The use of toxicokinetics data in risk assessment are discussed together with future approaches including sound statistical approaches to optimise predictability of models and recombinant technology/toxicokinetics assays to identify metabolic routes for chemicals and screen mixtures of environmental health importance.

A Tiered Approach to Life Stages Testing for Agricultural Chemical Safety Assessment

A proposal has been developed by the Agricultural Chemical Safety Assessment (ACSA) Technical Committee of the ILSI Health and Environmental Sciences Institute (HESI) for an improved approach to assessing the safety of crop protection chemicals. The goal is to ensure that studies are scientifically appropriate and necessary without being redundant, and that tests emphasize toxicological endpoints and exposure durations that are relevant for risk assessment. The ACSA Life Stages Task Force proposes a tiered approach to toxicity testing that assesses a compound's potential to cause adverse effects on reproduction, and that assesses the nature and severity of effects during development and adolescence, with consideration of the sensitivity of the elderly. While incorporating many features from current guideline studies, the proposed approach includes a novel rat reproduction and developmental study with enhanced endpoints and a rabbit development study. All available data, including toxicokinetics, ADME data, and systemic toxicity information, are considered in the design and interpretation of studies. Compared to existing testing strategies, the proposed approach uses fewer animals, provides information on the young animal, and includes an estimation of human exposure potential for making decisions about the extent of testing required.

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.

Development of a Physiology-Based Whole-Body Population Model for Assessing the Influence of Individual Variability on the Pharmacokinetics of Drugs

In clinical development stages, an a priori assessment of the sensitivity of the pharmacokinetic behavior with respect to physiological and anthropometric properties of human (sub-) populations is desirable. A physiology-based pharmacokinetic (PBPK) population model was developed that makes use of known distributions of physiological and anthropometric properties obtained from the literature for realistic populations. As input parameters, the simulation model requires race, gender, age, and two parameters out of body weight, height and body mass index. From this data, the parameters relevant for PBPK modeling such as organ volumes and blood flows are determined for each virtual individual. The resulting parameters were compared to those derived using a previously published model (P(3)M). Mean organ weights and blood flows were highly correlated between the two models, despite the different methods used to generate these parameters. The inter-individual variability differed greatly especially for organs with a log-normal weight distribution (such as fat and spleen). Two exemplary population pharmacokinetic simulations using ciprofloxacin and paclitaxel as model drugs showed good correlation to observed variability. A sensitivity analysis demonstrated that the physiological differences in the virtual individuals and intrinsic clearance variability were equally influential to the pharmacokinetic variability but were not additive. In conclusion, the new population model is well suited to assess the influence of individual physiological variability on the pharmacokinetics of drugs. It is expected that this new tool can be beneficially applied in the planning of clinical studies.

Human variability in hepatic and renal elimination: implications for risk assessment

Hepatic metabolism and renal excretion constitute the main routes of xenobiotic elimination in humans. Improving human risk assessment for threshold contaminants requires the incorporation of quantitative data related to their elimination (toxicokinetics) and potential toxic effects (toxicodynamics). This type of data provides a scientific basis to replace the standard uncertainty factor (UF = 10) allowing for the consideration of human variability in toxicokinetics and toxicodynamics. This review focuses on recent research efforts aiming to incorporate human variability in hepatic and renal elimination (toxicokinetics) into the risk assessment process. A therapeutic drug database was developed to quantify pathway-related variability in human phase I and phase II hepatic metabolism as well as renal excretion in subgroups of the population (healthy adults, neonates and the elderly), using data on compounds cleared primarily through each route (> 60% dose). For each subgroup of the population and elimination route, pathway-related UFs were then derived to cover 95-99% of each subgroup. Overall, the default toxicokinetic UFs would not cover neonates, the elderly for most elimination routes and any subgroup of the population for compounds metabolized via polymorphic isozymes (such as CYP2C19 and CYP2D6). These pathway-related UFs allow the incorporation of in vivo metabolism and toxicokinetic data in the risk assessment process and provide a flexible intermediate option between the default UF and chemical-specific adjustment factors (CSAFs) derived from physiologically based pharmacokinetic models. Implications of human variability in hepatic metabolism and renal excretion for chemical risk assessment are discussed.

Human and environmental risk assessment of pharmaceuticals: differences, similarities, lessons from toxicology

The presence of human and veterinary pharmaceuticals in the environment has caused increasing concern due their effects on ecological receptors. Improving the risk assessment of these compounds necessitates a quantitative understanding of their metabolism and elimination in the target organism (toxicokinetics), particularly via the ubiquitous cytochrome P-450 (CYP) system and their mechanisms of toxicity (toxicodynamics). This review focuses on a number of pharmaceuticals and veterinary medicines of environmental concern, and the differences and similarities between ecological and human risk assessment. CYP metabolism is discussed with particular reference to its ubiquity in species of ecological relevance. The important issue of pharmaceutical mixtures is discussed to assess how emerging technologies such as ecotoxicogenomics may assist in moving towards a more mechanism-based environmental risk assessment of pharmaceuticals.

Toxicology of micronutrients: adverse effects and uncertainty

The establishment of safe upper intake levels for micronutrients must consider the intake-response relations for both deficiency and toxicity. Limited data are available on the toxicities of most micronutrients, and few studies that meet the criteria considered essential for the risk assessment of other chemicals in food, such as pesticides and food additives, have been performed. In some cases, the application of large uncertainty factors, which are used to establish the amount of a chemical that would be safe for daily intake throughout life, could result in nutritionally inadequate intakes of micronutrients. As a consequence, lower than normal uncertainty factors have been applied to determine safe or tolerable intakes of many micronutrients. There is no clear scientific rationale, on the basis of the metabolism and elimination of micronutrients or the nature of the adverse effects reported for high intakes, for the use of reduced uncertainty factors for micronutrient toxicity. A review of recent evaluations of selected vitamins and minerals shows little consistency in the application of uncertainty factors by different advisory groups, such as the Institute of Medicine in the United States and the Scientific Committee on Foods in the European Union. It is apparent that, in some cases, the uncertainty factor applied was selected largely to give a result that is compatible with nutritional requirements; therefore, the uncertainty factor represented part of risk management rather than hazard characterization. The usual risk assessment procedures for chemicals in food should be revised for micronutrients, so that the risks associated with intakes that are too low and too high are considered equally as part of a risk-benefit analysis.

Guidance on setting of acute reference dose (ARfD) for pesticides

This paper summarises and extends the work developed over the last decade by the Joint FAO/WHO Meeting on Pesticide Residues (JMPR) for acute health risk assessment of agricultural pesticides. The general considerations in setting of acute reference doses (ARfDs) in a step-wise process, as well as specific considerations and guidance regarding selected toxicological endpoints are described in detail. The endpoints selected are based on the practical experience with agricultural pesticides by the JMPR and are not a comprehensive listing of all possible relevant endpoints. Haematotoxicity, immunotoxicity, neurotoxicity, liver and kidney toxicity, endocrine effects as well as developmental effects are taken into account as acute toxic alerts, relevant for the consideration of ARfDs for pesticides. The general biological background and the data available through standard toxicological testing for regulatory purposes, interpretation of the data, conclusions and recommendations for future improvements are described for each relevant endpoint. The paper also considers a single dose study protocol. This type of study is not intended to be included in routine toxicological testing for regulatory purposes, but rather to guide further testing when the current database indicates the necessity for an ARfD but does not allow a reliable derivation of the value.

The refinement of uncertainty/safety factors in risk assessment by the incorporation of data on toxicokinetic variability in humans

The derivation of safe levels of exposure in humans for compounds that are assumed to cause threshold toxicity has relied on the application of a 100-fold uncertainty factor to a measure for the threshold, such as the no observed adverse effect level (NOAEL) or the benchmark dose (BMD). This 100-fold safety factor consists of the product of two 10-fold factors allowing for human variability and interspecies differences. The International Programme on Chemical Safety has suggested the subdivision of these 10-fold factors to allow for variability in toxicokinetics and toxicodynamics. This subdivision allows the replacement of the default uncertainty factors with a chemical-specific adjustment factor (CSAF) when suitable data are available. This short review describes potential options to refine safety factors used in risk assessment, with particular emphasis on pathway-related uncertainty factors associated with variability in kinetics. These pathway-related factors were derived from a database that quantified interspecies differences and human variability in phase I metabolism, phase II metabolism, and renal excretion. This approach allows metabolism and pharmacokinetic data in healthy adults and subgroups of the population to be incorporated in the risk-assessment process and constitutes an intermediate approach between simple default factors and chemical-specific adjustment factors.

Human variability in xenobiotic metabolism and pathway-related uncertainty factors for chemical risk assessment: a review

This review provides an account of recent developments arising from a database that defined human variability in phase I metabolism (CYP1A2, CYP2A6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, hydrolysis, alcohol dehydrogenase), phase II metabolism (N-acetyltransferases, glucuronidation, glycine conjugation, sulphation) and renal excretion. This database was used to derive pathway-related uncertainty factors for chemical risk assessment that allow for human variability in toxicokinetics. Probe substrates for each pathway of elimination were selected on the basis that oral absorption was >95% and that the metabolic route was the primary route of elimination of the compound (60-100% of a dose). Intravenous data were used for compounds for which absorption was variable. Human variability in kinetics was quantified for each compound from published pharmacokinetic studies (after oral and intravenous dosing) in healthy adults and other subgroups of the population using parameters relating to chronic exposure (metabolic and total clearances, area under the plasma concentration-time curve (AUC)) and acute exposure (Cmax) (data not presented here). The pathway-related uncertainty factors were calculated to cover 95%, 97.5% and 99% of the population of healthy adults and of each subgroup. Pathway-related uncertainty factors allow metabolism data to be incorporated into the derivation of health-based guidance values. They constitute an intermediate approach between the general kinetic default factors (3.16) and a chemical-specific adjustment factor. Applications of pathway-related uncertainty factors for chemical risk assessment and future refinements of the approach are discussed. A knowledge-based framework to predict human variability in kinetics for xenobiotics showing a threshold dose below which toxic effects are not observed, is proposed to move away from default assumptions.

Risk-benefit analysis of micronutrients

Traditionally, different approaches have been used to determine the recommended dietary allowances for micronutrients, above which there is a low risk of deficiency, and safe upper levels, below which there is a negligible risk of toxicity. The advice given to risk managers has been in the form of point estimates, such as the recommended dietary allowance (RDA) and the tolerable upper level (UL). In future, the gap between the two intake-response curves may become narrower, as more sensitive indicators of deficiency and toxicity are used, and as health benefits above the recommended daily allowance are taken into account. This paper reviews the traditional approaches and proposes a novel approach to compare beneficial and adverse effects across intake levels. This model can provide advice for risk managers in a form that will allow the risk of deficiency or the risk of not experiencing the benefit to be weighed against the risk of toxicity. The model extends the approach used to estimate recommended dietary allowances to make it applicable to both beneficial and adverse effects and to extend the intake-incidence data to provide a range of estimates that can be considered by the risk manager. The data-requirements of the model are the incidence of a response at one or more levels of intake, and a suitable coefficient of variation to represent the person-to-person variations within the human population. A coefficient of variation of 10% or 15% has been used for established recommended dietary allowances and a value of 15% is proposed as default for considerations of benefit. A coefficient of variation of 45% is proposed as default for considerations of toxicity, based on analyses of human variability in the fate and effects of therapeutic drugs. Using this approach risk managers, working closely with risk assessors, will be able to define ranges of intake based on a balance between the risks of deficiency (or lack of benefit) and toxicity.

Species-specific uncertainty factors for compounds eliminated principally by renal excretion in humans

An uncertainty factor of 100 is used to derive health-based guidance values for human intakes of chemicals based on data from studies in animals. The 100-fold factor comprises 10-fold factors for species differences and for interindividual differences in response. Each 10-fold factor can be subdivided into toxicokinetic and toxicodynamic aspects with a 4.0-fold factor to allow for kinetic differences between test species and humans. The current work determined the extent of interspecies differences in the internal dose (toxicokinetics) of compounds which are eliminated primarily by renal excretion in humans. An analysis of the published data showed that renal excretion was also the main route of elimination in the test species for most of the identified probe substrates. Interspecies differences were apparent for both the mechanism of renal excretion (glomerular filtration, tubular secretion and/or reabsorption) and the extent of plasma protein binding, both of which may affect renal clearance and therefore the magnitude of species differences in the internal dose. For compounds which are eliminated unchanged by both humans and the test species, the average differences in the internal doses between humans and animals were 1.6 for dogs, 3.3 for rabbits, 5.2 for rats and 13 for mice. This suggests that for renal excretion, the differences between humans and the rat and especially the mouse may exceed the 4.0-fold default factor for toxicokinetics.