Science and Decisions Advancing Risk Assessment (2009) / Chapter Skim
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5 Toward a Unified Approach to Dose-Response Assessment
5 Toward a Unified Approach to Dose-Response Assessment
Pages 127-187
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From page 127... ...
Current Framework Dose-response assessments for carcinogenic end points have been conducted very differently from noncancer assessments. For carcinogens, it has been assumed that there is no threshold of effect, and dose-response assessments have focused on quantifying the risk at low doses.
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From page 128... ...
For carcinogens with sufficient MOA data to conclude nonlinearity at low doses, such as those acting through a cytotoxic MOA, the RfD approach outlined above for noncancer end points is applied (EPA 2005b) , More recent noncancer guidelines have abandoned the term threshold, noting the difficulty of empirically distinguishing dose-response relationships with true biologic thresholds from ones that are nonlinear at low doses (EPA 2005b, p.
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From page 129... ...
However, as illustrated in Figure 5-2, threshold determinations should not be made in isolation, inasmuch as other chemical exposures and biologic factors that influence the same adverse effect can modify the doseresponse relationship at low doses and should therefore be considered. Nonlinear Cancer End Points The current determination of "nonlinearity" based on MOA assessment is a reasonable approach to introduce scientific evidence on MOA into cancer dose-response assessment.
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From page 130... ...
Animal to human dose conversion: - Human interindividual variability (U2) mg/kg3/4-d scaling or pharmacokinetic modeling - Other (U3)
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From page 131... ...
And EPA practices do not call for systematic evaluation of endogenous and exogenous exposures or mechanisms that can lead to linearity. By segregating cancer and noncancer risk assessment, the current framework tends to place undue focus on "complete" carcinogens, ignoring contributions to ongoing carcinogen esis processes and the multifactorial nature of cancer.
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From page 132... ...
and does not provide methods and practices for readily assessing the dose-response relationship for cases in which thresholds are not apparent or not expected, for example, because of background additivity. As discussed in this chapter, for critical end points driving the risk characterization at low doses, such cases may be common, and a new framework and practice are needed.
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From page 133... ...
Therefore, the committee finds the 2005 Guidelines for Carcinogen Risk Assessment movement toward RfDs and away from an expression of risk posed by nonlinear carcinogens problematic. Similarly, although noncancer risk assessment has moved to a BMD framework that makes better use of evidence than an approach based on NOAELs and lowest observed-adverse-effect levels (LOAELs)
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From page 134... ...
. There are three main steps in deriving human cancer risk from animal bioassay data: adjusting animal doses to equivalent human doses, deriving the POD by fitting a mathematical model to the data, and linearly extrapolating from the POD to lower doses.
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From page 135... ...
The shape of the population dose-response relationship at low doses is inferred from an understanding of individual dose-response relationships, which in turn are based on consideration of background exposure and biologic susceptibility on human heterogeneity. An upper bound on the population dose-response relationship would be derived to express uncertainty in the population dose-response relationship.
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From page 136... ...
136 SCIENCE AND DECISIONS: ADVANCING RISK ASSESSMENT Risk Determinants Environmental Chemical Stressor Biological Background Susceptibility: Exposure Health and Disease Endogenous & Status, Genetics, Xenobiotic Age, Gender An individual's dose response Probability of Effect from Environmental Exposure Environmental Chemical Dose Heterogeneity in Background Exposure and Susceptibility Population dose response Fraction of Population Responding to Environmental FIGURE 5-3a New conceptual framework for dose- Chemical response assessment. Risk posed by environmental chemical is determined from individual's biologic makeup, health status, and other endogenous and exogenous exposures that affect toxic process; differences among Environmental humans in these factors affect shape of population Chemical Dose dose-response curve.
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From page 137... ...
and dose-response relationships for Mean sensitive members of population are described. (As Estimate explained in text, upper 95% confidence bound on risk is not same as upper-bound estimate generated Environmental in current cancer risk assessments.)
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From page 138... ...
Characteristics of the Dose-Response Framework The dose-response framework envisioned includes the following features: • Dose-response characterizations that use the spectrum of evidence from human, animal, mechanistic, and other relevant studies. Whole-animal dose-response studies will continue to play a central role in establishing PODs for most chemicals, but information on human heterogeneity, background exposures, and disease processes and data from mechanistic in vitro and in vivo studies will be critical in selecting the approach to the dose-response analysis.
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From page 139... ...
The term uncertainty factors can be problematic because it connotes only one aspect of the function of the factors. As the default distributions are developed, a better, more specific label for them would be preferable (for example, human variability distribution)
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From page 140... ...
It can be derived by applying human variability and other adjustment factors (for example, for interspecies differences) represented by distributions rather than default uncertainty factors.
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From page 141... ...
This is the dose-response conceptual model currently in use for noncancer end points. For these dose-response relationships, the fraction of the human population responding drops to inconsequential levels at low doses.
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From page 142... ...
Low-dose linear individual and population dose-response. For this conceptual model, both individual risk and population risk have no threshold and are linear at low doses, as illustrated in Figure 5-6.
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From page 143... ...
. General Approach to Dose-Response Assessment The general approach, illustrated in Figure 5-8, involves consideration of MOA, background exposures, and possible vulnerable populations in selecting a conceptual model and methods for dose-response analysis.
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From page 144... ...
Because epidemiologic studies are often limited in their ability to explore outcomes related to workplace or environmental exposures, it is typically impossible to rule out the relevance of an effect seen in a particular rodent tissue unless there is detailed mechanistic information on why humans would not be affected (IARC 2006)
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From page 145... ...
Any MOA information that might be helpful in understanding dose-response relationships at both high and low doses would be considered, including dose-dependent nonlinearities in metabolic processes, depletion of cellular defenses, potential to outpace repair processes, induction of enzymes by repeat dosing, additivity and interaction with background disease processes, and additivity of the chemical and its metabolites with other chemical exposures. The MOA assessment brings mechanistic information to bear on the dose-response assessment.
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From page 146... ...
Questions, like those above, are essential to ask when conducting chemical risk assessment, whether using the unified framework or current approaches. These questions help identify potential data sources for understanding inter-human variability in response and the extent to which a chemical may pose risks at low doses, and the limits in that understanding.
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From page 147... ...
. The unified framework formalizes the incorporation of this type of information into human-health risk assessments, through background and vulnerability assessments and the subsequent selection of a conceptual model for dose-response assessment.
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From page 148... ...
To guide this decision, the committee has developed examples of prototypical conceptual models, described earlier and summarized in Figure 5-10. Consideration of background exposures and processes is critical for the determination of likelihood of low-dose linearity in the population dose-response relationship.
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From page 149... ...
An individual's: Probability of Effect Population Nonlinear Affected The population: Nonlinear Background dose Dose Background dose Dose 3. An individual's: Probability Fraction of Population of Effect Linear Affected The population: Linear Dose Dose FIGURE 5-10 Examples of conceptual models to describe individual and population dose-response relationships.
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From page 150... ...
Approaches and guidelines for conducting vulnerability and background assessments will be needed, as will guidelines for conducting the assessments and selecting conceptual models. Selection of Method for Dose-Response Analysis The approach to the analysis depends on the conceptual model, the data available for the analysis, and risk-management needs.
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From page 151... ...
Other methods are "top down" in that the dose-response relationship at low doses is derived by fitting exposureresponse models to observations from epidemiologic or animal studies. Conceptual Model 1: Low-Dose Linear Dose-Response Relationship Due to Heterogeneous Individual Thresholds and High Background Particulate-Matter Case Study Fine PM (PM2.5)
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From page 152... ...
interindividual variability • Linear extrapolation • Extrapolation based on human • Linear extrapolation variability distribution Special case if sensitive subgroups identified FIGURE 5-12 Three example conceptual models lead to different descriptions of dose-response relationships at individual or population levels. These are illustrated in the case studies.
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From page 153... ...
An extension of this analysis found results for subpopulations that were consistent with lognormal distributions for a very small number of cut points (Hattis 2008) , suggesting the general population responses may be consistent with a mixture of lognormal distributions.
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From page 154... ...
These approaches entail characterization of background processes of function loss, damage, disease, and concomitant exposures that will enable a description of the population distribution of vulnerability. That, in turn, can be used in assessing interindividual variability in toxicodynamic response at low doses and can inform the shape of the dose-response relationship at low doses.
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From page 155... ...
. The background rate of airway hyperresponsiveness may be used to assess the number of people at risk for developing asthma symptoms in response to even low doses of a new insulting agent.
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From page 156... ...
1,4-Dioxane in Animals Case Study When epidemiologic data are lacking, diagnostic questions regarding vulnerability and background exposures may be difficult to answer. The background rate of toxicity in
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From page 157... ...
However, evidence of its involvement as a precursor lesion in hepatocarcinogenesis could lead to its evaluation with a different analytic framework (for example, conceptual model 3)
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From page 158... ...
Default Modeling Approach for Conceptual Model 1: Linear Extrapolation for Phosgene As described above, small chemical exposures in the presence of existing disease processes and other endogenous and exogenous exposures can have linear dose-response relationships at low doses. Thus, a simple methodologic default to address conceptual model 1 compounds is linear extrapolation from the POD, such as a benchmark dose, down to low doses.
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From page 159... ...
Here, as for conceptual model 3, an important issue is whether dose effectiveness is the same at high doses and low doses. Extrapolation methods for addressing that are discussed in the section below on the mathematical framework for conceptual model 3.
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From page 160... ...
The extrapolation from the POD down the dose-response curve is driven by interhuman variability, broken out in Figure 5-16 into PK and PD elements. The application of adjustment and uncertainty distributions representing each of these elements effectively converts the animal POD (for example, the BMDL or the ED50, the effective dose estimated to affect 50% of subjects)
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From page 161... ...
Step 2 adjusts animal POD by this cross-species distribution. Step 3 uses human variability distribution to extrapolate from POD to lower risk.
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From page 162... ...
The overall adjustment is made up of three adjustments: for animal-to-human extrapolation, "FA→H"; for experiment duration from subchronic to chronic, "FSC→C"; and for data gaps, "FGap." Thus, Human POD = (Animal POD) /(FA→H POD adjust)
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From page 163... ...
A sample set of calculations is provided in Box 5-3 to illustrate how the above calculations can be made to derive a human POD. Human Variability Distributions for Extrapolating from Human POD to Low Doses • Interindividual variability -- PK Dimension.
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From page 164... ...
For the example here, overall human interindividual variability is described by a lognormal distribution with me
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From page 165... ...
Because these characterizations of variability are limited by the relatively small numbers upon which the estimates are based, this uncertainty estimate may have a downward bias. Calculation of Risk-Specific Dose and Confidence Bound A distribution of human variability can be applied to move from the human POD down the dose-response curve, as illustrated in the set of calculations in Box 5-3.
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From page 166... ...
This is unlike the previous two conceptual models, which described population dose-response distributions that arise when the dose-response relationship in an individual has a threshold. A possible approach to default analysis following this conceptual model is presented below.
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From page 167... ...
÷ = POD Dose (mg-kg-d) 3: Extrapolate from human POD to linearly to low dose Extra Risk Risk for Median Individual POD05 50 95th percentile risk + +POD 50th percentile risk median person median person POD05 and POD50 represent the 5th and 50th percentiles of the human POD for the median individual Dose 4: Estimate population and individual risk and uncertainty Extra Risk Uncertainty in individual's Extra Risk risk-specific dose Inter-Human Variability Average population risk 95th percentile individual's risk × 95th percentile risk median individual's risk median person 50th percentile risk median person Dose Dose FIGURE 5-17 Steps to derive population and individual risk estimates,5-17.eps Figure with uncertainty in estimates from animal data.
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From page 168... ...
In the 4-aminobiphenyl case discussed below, additional physiologic factors such as storage in the bladder contributed to human variability in PK elements. The suggested default of 25 will have the effect of increasing the population risk (average risk)
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From page 169... ...
It would be important for the cancer risk assessment to express interindividual variability by showing the median and average population risks, as well as the range of individual risks for risk-management consideration. Case Study: 4-Aminobiphenyl 4-Aminobiphenyl is a known cause of human bladder cancer.
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From page 170... ...
, and in base 10 log space of 1.03. Derivation of Median Human POD and Slope for 4-Aminobiphenyl Despite the known causal association between human bladder-cancer risk and 4-aminobiphenyl, human exposure estimates in occupational studies may be insufficient for establishing reliable dose-response relationships, and the assessment may have to be based on animal data, as is done here.
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From page 171... ...
. At low doses, population risk is calculated by multiplying the population potency by the dose.
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From page 172... ...
The goal here is to enable such expressions as "The risk of effect does not exceed x for the yth percentile individual, stated with a confidence interval of z1- z2." The 4-aminobiphenyl case provided an example of how that might be done. In some cases, as a default, it may be convenient and appropriate to describe uncertainty in RiskH mathematically with a lognormal distribution, for example, if the uncertainty in each factor in Equation 1 can be represented by a lognormal distribution.
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From page 173... ...
12) noted there is "some possibility that genotoxicity could contribute to the dose-response at low doses" for the observed kidney tumors and called for the agency to address the general issue of mixed modes of action by "beginning to develop a reasonable means of estimating the most likely and upper bound estimate of potential contribution of a ‘genotoxic' component to the carcinogenic activity." Dose-response analysis of chemicals whose end points are associated with multiple MOAs is challenging.
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From page 174... ...
For noncancer end points, the defaults will enable a probabilistic basis of establishing the RfD and characterizing noncancer risks; for cancer-risk characterization, they will enable incorporation of interhuman variability. Use of default distributions for adjustments in extrapolations, rather than default point-estimate uncertainty factors, provides an improved representation of variability and uncertainty and offers an opportunity for further refinements and incentives to gather and analyze existing information and to generate new data targeted to specific extrapolation needs.
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From page 175... ...
with humans; consider human population using bodyweight scaling for PK portion of extrapolation if overall distribution covering PK and PD cannot be derived; develop default distribution to describe uncertainty in bodyweight scaling Interindividual PK differences PK datasets on Derive default distribution of PK variability in among life stages, susceptible groups PK variability based on analogy humans disease states, genetic (such as children) are with drug literature and, to polymorphisms, drug difficult to obtain; extent possible, made spceific interactions default may have to to particular enzyme pathways, be based primarily on types of receptors, and classes drug literature, which of chemicals; use PBPK Bayesian is also limited and Monte Carlo approaches to evaluate implications of variability in enzyme pathways for overall PK variability; consider adjustments to address small samples and other biases in derivation Interindividual PD differences in Human PD response is Base default distribution on PD variability in population with likely to vary widely, broad array of human responses, humans respect to various especially in groups chemicals, and end points from types of end points, that are difficult drug testing and high-quality including cancer to study (such as epidemiologic studies; use children, elderly)
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From page 176... ...
; formally adopt assumption that genotoxic chemicals (clastogens, mutagens) cause cancer via a mutagenic MOA Low-dose linear Dose-response data Data from epidemiologic Develop series of default M factors slope factor -- M over wide dose ranges and toxicologic studies based on mechanistic consideradjustment in human and animal are limited; there is ations and human and animal studies and related need to know how to observations to apply in differ mechanistic data use biologic models in ent situations (such as saturation considering mechanistic phenomena or high-dose cytotoxic data ity that influences carcinogenicity of chemicals with some genotoxic activity)
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From page 177... ...
Default distributions that characterize PK and PD variability, crossspecies dose adjustments, and adjustments for the lack of sensitive studies will be needed as starting points that can be improved as the research advances. • The committee considers that the term safety factor, to characterize uncertainty factors in noncancer risk assessments, is inappropriate and misleading.
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From page 178... ...
that interact with a chemical's MOAs and thus contribute to variability in and vulnerability to the toxicant response and that can result in a population dose-response relationship that is linear at low doses. − Selection of a conceptual model for individual and population dose-response relationships.
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From page 179... ...
Depending on the level of analysis, that would provide incentives for chemical-specific information on background exposures, interaction with baseline aging and disease processes, and interindividual variability. It comes at a time when toxicology and risk-assessment resources are already challenged by the expanding role of risk assessment in decision-making and the lack of basic toxicology information on many chemicals.
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From page 180... ...
− Evaluation of each chemical in terms of MOA, background exposure and disease processes, and vulnerable populations. This would add a step to the dose-response analysis in which background exposures and vulnerabilities of the target population are analyzed and used to decide between analytic options based on conceptual models, according to the unified framework outlined in Figure 5-8.
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From page 181... ...
When analyzed with exposure biomarkers, they could be used to assess human exposure-response relationships and interindividual variability. Regional and national datasets, such as those from National Health and Nutrition Examination Surveys and environmental and public-health tracking, could be used to evaluate whether people with background vulnerability or background exposure are at increased risk of the effects of exposure to toxicants.
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From page 182... ...
1995. Modeling human interindividual variability in metabolism and risk: The example of 4-aminobiphenyl.
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From page 183... ...
�������� In Sup port of Summary Information on the Integrated Risk Information System (IRIS)
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From page 184... ...
1996. Human interindividual variability in cancer risks -technical and management challenges.
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From page 185... ...
Pp. 25-48 in Chemical-Spe cific Adjustment Factors for Interspecies Differences and Human Variability: Guidance Document for Use of Data in Dose/Concentration-Response Assessment.
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From page 186... ...
1993. Polycyclic aromatic hydrocarbon-DNA adducts in white blood cells and urinary 1-hydroxypyrene in foundry workers.
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From page 187... ...
TOWARD A UNIFIED APPROACH TO DOSE-RESPONSE ASSESSMENT 187 West, J., H
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