Risk assessment methods relationship

Among the possible alternative methods, in vitro assay (for ATMs) and quantitative structure-activity relationships (QSARs) models (for ANTMs) are the most applied approaches in the toxicological and ecotoxicological evaluation of chemicals profiles, even in the field of environmental research and risk assessment. 

Decision Analysis. An alternative to making assumptions that select single estimates and suppress uncertainties is to use decision analysis methods, which make the uncertainties explicit in risk assessment and risk evaluation. Judgmental probabilities can be used to characterize uncertainties in the dose response relationship, the extent of human exposure, and the economic costs associated with control policies. Decision analysis provides a conceptual framework to separate the questions of information, what will happen as a consequence of control policy choice, from value judgments on how much conservatism is appropriate in decisions involving human health. 

Probabilistic methods can be applied in dose-response assessment when there is an understanding of the important parameters and their relationships, such as identification of the key determinants of human variation (e.g., metabolic polymorphisms, hormone levels, and cell replication rates), observation of the distributions of these variables, and valid models for combining these variables. With appropriate data and expert judgment, formal approaches to probabilistic risk assessment can be applied to provide insight into the overall extent and dominant sources of human variation and uncertainty. 

Central to any risk assessment is a model of causality. At the onset, a conceptual model is needed that identifies a plausible cause-effect relationship linking stressor exposure to some effect. Most ecological risk assessments rely heavily on weight-of-evidence or expert opinion methods to foster plausibility of the causal model. Unfortunately, such methods are prone to considerable error (Lane et al. 1987 Hutchinson and Lane 1989 Lane 1989), and attempts to quantify that error are rare. Although seldom used in risk assessment, Bayesian methods can explicitly quantify the plausibility of a causal model. 

In the absence of definitive human data, risk assessment may have to depend on the results of cancer bioassays in laboratory animals, short-term tests, or other experimental methods. Hence the following issues must be addressed under such circumstances the ability of the test system to predict risks for man (quantitatively as well as qualitatively) the reproducibility of test results the influence of species differences in pharmacokinetics, metabolism, homeostasis, repair rates, life span, organ sensitivity, and baseline cancer rates extrapolation across dose and dose rates, and routes of exposure the significance of benign tumors fitting models to the data in order to characterize dose-incidence relationships and the significance of negative results. 

The approaches described previously can be used to relate biomonitoring results to a reference population or to workplace exposures, but they do not evaluate the risk associated with the amount of a chemical found in the body. To do that, one needs to develop a relationship between biomarker concentration and toxic response, a relationship that is not commonly derived in standard toxicologic practice. The following sections outline methods for deriving such a relationship. The approaches include the ideal case of existing risk assessments based on biomarker-response relationships established in epidemiologic research. Lead and mercury are used as examples of cases in which exposure was quantified according to hair or blood biomarkers and dose-response associations were developed on this basis. 

The outputs from risk assessment will normally include information about the relationship between dose and risk and estimates of levels of doses and thus risks in the population. For contaminants that have a toxicological threshold the Provisional Tolerable Weekly Intake (PTWI) might be defined and the number of consumers who have the potential to exceed this level of intake quantified. If a PTWI cannot be established (such as for genotoxic carcinogens) then it may be possible to quantify the proportion of a population exposed to a given level of risk by using QRA methods. If QRA methods cannot be applied then a qualitative assessment can be made such as to reduce intake levels to as low as is reasonably practicable. In either case it is the function of risk management to identify an optimal course of action to minimise the risk to consumers. 

Borgmann, A., Moody, M. and Scroggins, R. (2004) The Lab-to-Field (LTF) Rating Scheme A New Method of Investigating the Relationships between Laboratory Sublethal Toxicity Tests and Field Measurements in Environmental Effects Monitoring Studies, Journal of Human and Environmental Risk Assessment, August 2004. 

These methods can be adopted to define dose relationships - as was the intent of the open epicutaneous test (OET). The availability of the threshold for induction (TIC) and elicitation (TEC) provides a valuable tool in clinical risk assessment. 

Because the literature describes several limitations in the use of NOAELs (Gaylor 1983 Crump 1984 Kimmel and Gaylor 1988), the evaluative process considers other methods for expressing quantitative dose-response evaluations. In particular, the BMD approach originally proposed by Crump (1984) is used to model data in the observed range. That approach was recently endorsed for use in quantitative risk assessment for developmental toxicity and other noncancer health effects (Barnes et al. 1995). The BMD can be useful for interpreting dose-response relationships because it accounts for all the data and, unlike the determination of the NOAEL or LOAEL, is not limited to the doses used in the experiment. The BMD approach is especially helpful when a NOAEL is not available because it makes the use of a default uncertainty factor for LOAEL to NOAEL extrapolation unnecessary. 

In addition to in vivo and in vitro experimentation, mathematical models and quantitative structure-permeability relationship (QSAR) methods have been used to predict skin absorption in humans. These models use the physico-chemical properties of the test compound (e.g. volatility, ionization, molecular weight, water/lipid partition, etc.) to predict skin absorption in humans (Moss et al 2002). The models are particularly attractive because of the low cost and rapidity. However, because of the above-mentioned factors influencing dermal absorption, mathematical models are of limited use for risk assessment purposes. Since these models are currently not accepted by regulatory agencies involved in pesticide evaluations, they will not be further discussed in this chapter. 

The relationship being found between endocrine system, the nervous system, and immune system will make these endpoints prime areas for further development of chronic toxicity test methods for aquatic organisms and should be considered for ecological and hazard risk assessments of chemicals [7,386]. 

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