Quantitative risk assessment limitations

Hazard analysis (HAZAN) is a quantitative way of assessing the likelihood of failure. Other names associated with this technique are risk analysis, quantitative risk assessment (QRA), and probability risk assessment (PRA). Keltz [44] expressed the view that HAZAN is a selective technique while HAZOP can be readily applied to new design and major modification. Some limitations of HAZOP are its inability to detect every weakness in design such as in plant layout, or miss hazards due to leaks on lines that pass through or close to a unit but cany material that is not used on that unit. In any case, hazards should... 

The utilisation of RCP as secondary raw material has to find a quantitative risk assessment in the future to establish meaningful limit values as basis for the development of e.g. elimination processes or barrier coatings. 

The 95% confidence limits of the estimate of the linear component of the LMS model, /, can also be calculated. The 95% upper confidence limit is termed qi and is central to the US-EPA s use of the LMS model in quantitative risk assessment, as qi represents an upper bound or worst-case estimate of the dose-response relationship at low doses. It is considered a plausible upper bound, because it is unlikely that the tme dose-response relationship will have a slope higher than qi, and it is probably considerably lower and may even be zero (as would be the case if there was a threshold). Lfse of the qj as the default, therefore, may have considerable conservatism incorporated into it. The values of qi have been considered as estimates of carcinogenic potency and have been called the unit carcinogenic risk or the Carcinogen Potency Factor (CPF). 

The major change from the previous guidelines in terms of the quantitative risk assessment is that the LMS model no longer is the recommended default approach for low-dose extrapolation. Instead, an MOE approach is recommended based on curve fitting within the range of observation with extrapolation from a UED (the 95% lower confidence limit on a dose associated with an extra tumor risk) chosen to be representative of the lower end of the observed range. 

Human health risk assessment has often been dominated by the use of default assumptions and worst case analyses, based on the use of upper bounds on the dose from exposure instead of distributional characterizations of that dose. There are severe limitations associated with the use of default assumptions and upper bounds instead of distributions when detailed exposure and/or dose-response data are available. The US National Academy of Sciences, the USEPA, and many others have recognized the need for new risk assessment methodology (NRC, 1983, 1993, 1994 USEPA, 1992 CRARM, 1997). This need has promoted the development of new quantitative risk assessment methods that use probabilistic techniques, especially Monte Carlo simulation and distributional characterizations of dose-response, exposure, and risk. For these reasons, this paper uses a probabilistic approach. An indication of some of these new methods and the type of results they produce are given below. 

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. 

As a result, to date epidemiological studies of pesticide exposures have only been indicative of the presence of elevated health risks. Quantitative studies contributing to evidence on exposure-response relationships which could be used for quantitative risk assessment purposes are not widely available. This implies that the epidemiological potential has not been explored to its limits, as has been done for certain other agents such as asbestos and lead, for which present legislation has been based, to a large extent, on quantitative evidence of health risks in humans obtained from epidemiological studies. 

In the United States, some state and federal regulatory agencies conduct quantitative risk assessments on known or suspect carcinogens for continuous or long-term human exposure by extrapolating downward in linear fashion from an npper confidence limit on theoretical excess risk (FDA 1985 EPA 1986). The values derived for a specified acceptable theoretical excess risk to the U.S. human population, based on a lifetime of exposure to a carcinogenic substance, have been used extensively for regulatory purposes. 

In certain cases, the FDA has applied a negligible risk concept for food additives. This is demonstrated in the case of dimethyl dicarbamate, a yeast inhibitor for use in beverages (FDA 2000). The additive evenmaUy decomposes to methanol and carbon dioxide, but in the presence of ammonium ions (not uncommon in certain beverages) a carcinogenic chemical may also be formed in small amounts. The FDA used formal quantitative risk assessment procedures to estimate the upper-bound limit of carcinogenic risk to humans posed by urethane generated by decomposition of the additive. It was concluded that the potential risk was sufficiently low that the additive would be safe for the requested use, and the FDA s final rule approved its use (56 FR 40502 1988). 

Quantitative risk assessment requires extrapolation from results of experimental assays conducted at high dose levels to predicted effects at lower dose levels which correspond to human exposures. The meaning of this high to low dose extrapolation within an animal species will be discussed, along with its inherent limitations. A number of commonly used mathematical models of dose-response necessary for this extrapolation, will be discussed. Other limitations in their ability to provide precise quantitative low dose risk estimates will also be discussed. These include the existence of thresholds incorporation of background, or spontaneous responses modification of the dose-response by pharmacokinetic processes. 

The limitations of event-chain models are reflected in the current approaches to quantitative risk assessment, most of which use trees or other forms of event chains. Probabilities (or probability density functions) are assigned to the events in the chain and an overall likelihood of a loss is calculated. 

These constraints, however, apply independently of the source of the input data, either QSARs or experiments. Therefore, within the framework available, the comparison of risk assessments for the different scenarios demonstrate positively that QSAR estimates and exposure modelling can be useful for environmental risk assessments. If the established validation criteria and limitations are considered, the reliability of the QSAR data and the accuracy of the modelling mostly correspond to the variability in the underlying experimental data. Special care has to be taken to obtain representative data sets, such as accounting for the toxicity to all relevant species in an aquatic community. As long as the wide variety of data required for quantitative risk assessments are not available from experimental sources, QSARs remain a tool for providing estimates of the exposure-relevant properties of chemicals and the toxicity of the compounds towards various species, thus allowing a more reliable quantification of the potential hazards and risks from environmental contaminants. 

Methods for toxicological safety assessments are multiple and varied - some are more reliable than others, some more radical than others, but all are important. Their nature greatly depends on their endpoints, namely, the degree of practical safety they attempt to attain. Unfortunately, the true validity of these methods can only be assessed retrospectively, that is to say, by the record of cases of health impairment they were able to prevent over a reasonable period of time. Because of this and the uncertainty inherent in any extrapolation technique, the final products expressed in numerical form can only be considered as opinions. Some important toxicological opinions presented in numerical form are the LD50 the quantitative risk assessments, the threshold limit values (TLV), and the acceptable daily intakes (ADIs). 

Envlroiunental testing Is a critical element In this process since It enables the qualitative and quantitative determination of toxic chemicals In the environment and the definition of environmental pathways which may lead to human exposure This paper briefly reviews the overall process of health risk assessments and the particular role which environmental testing plays Recent efforts to assess environmental health risks In relation to Love Canal Illustrate both the usefulness and the limitations of environmental testing In risk assessment ... 

In animal experiments exposures can be carefully controlled, and dose-response curves can be formally estimated. Extrapolating such information to the human situation is often done for regulatory purposes. There are several models for estimating a lifetime cancer risk in humans based on extrapolation from animal data. These models, however, are premised on empirically unverified assumptions that limit their usefulness for quantitative purposes. While quantitative cancer risk assessment is widely used, it is by no means universally accepted. Using different models, one can arrive at estimates of potential cancer incidence in humans that vary by several orders of magnitude for a given level of exposure. Such variations make it rather difficult to place confidence intervals around benefits estimations for regulatory purposes. Furthermore, low dose risk estimation methods have not been developed for chronic health effects other than cancer. The... 

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