Risk assessment prospective

In this paper I have tried to show that measurement of health benefits attributable to TSCA is not feasible. I hope that in doing so I have not belabored the obvious. For new chemicals and for most existing chemicals, prospective evaluation of health benefits to be achieved by various exposure controls will have to be based on extrapolation from microbial and animal data. However, while such extrapolation may be useful in a qualitative sense, quantitative risk assessment techniques involve considerable uncertainty, and in any case have not been developed for chronic effects other than cancer. 

Experimental data or field observations on mixture toxicity and the responses in species assemblages are rarely available, with some exceptions (Korthals et al. 2000 Backhaus et al. 2004 Arrhenius et al. 2004). Nonetheless, risk assessment and legislation often focus on the protection of community-level endpoints in both prospective and retrospective risk assessments. 

Species sensitivity distributions (SSDs) are used for both prospective and retrospective risk assessments (Posthuma et al. 2002b). In prospective risk assessments, the concept is used to derive hazardous concentrations (e.g., HC5), which are used to derive environmental quality criteria. In retrospective risk assessments, the SSD approach is used to determine the local toxic pressure in terms of the potentially affected fraction (PAF) of species for each compound separately. Subsequently the multisubstance (ms)PAF, or optionally the combi-PAF, for the local mixture can be calculated. Originally, the combi-PAF concept was developed by Hamers et al. (1996) and assumes that only compounds exerting narcotic effects... 

Prospective and Retrospective Risk Assessment at the Landscape Level... 

It is clear that an accurate exposure prediction at the landscape level requires models calibrated and validated for the landscape unit of interest and that the input parameters used have a high precision and accuracy for the area of interest (see Section 1.7 in Chapter 1). However, in a prospective risk assessment for new chemicals not yet placed on the market, chemical monitoring data are not yet available, and exposure predictions at the landscape level may be characterized by a relatively high uncertainty because the scale and intensity of the use of these chemicals are not... 

There are many extrapolation methods, of different complexities, and with different purposes and suitabilities for prospective and retrospective risk assessments. A compilation of the methods is insufficient to guide the choice of procedures to use when assessors need to conduct risk assessments. Therefore, a practical and pragmatic guide to extrapolations and their everyday use is provided in the last chapter. It defines a general stepwise approach to identifying the types of extrapolation (matrix and media, (Q)SARs, mixtures, etc.) that are most relevant for an assessment problem, and it defines an overall approach to the assignment of tiers. 

Extrapolation methods are used for various types of risk assessment. Methods may be used in the process of deriving environmental quality objectives, in the registration of new substances, and in the process of site-specific risk assessment. Suter (1993) called these approaches prospective (the former 2) and retrospective (the latter) risk assessments. The specific process in which extrapolation methods are used has implications for the concepts to be applied and the data to be used as input in extrapolation. Strictly described approaches are in place for the derivation of environmental quality criteria (EQCs) and the registration of pesticides and newly developed substances. The prescribed approaches for deriving EQCs can differ between jurisdictions. The approaches for retrospective investigations have more degrees of freedom. A characteristic of the latter approach is that the methods can make use of measured local exposure levels and can estimate local risk with known precision (or known uncertainty ). The latter is uncommon for EQCs. 

When the scope is known and the extrapolation methods are defined, the data for the risk assessment steps (and extrapolations) can be collected. For tiered systems, this implies that choices need to be made on the manner in which uncertainties are addressed and what to do when these are only addressed by simple methods. A distinction was already made between prospective use and retrospective use of extrapolation methods. In both cases, extrapolations are being applied, but the way in which existing methods are selected for an assessment problem can differ. 

In the prospective context, a common and simple way to handle uncertainty is the use of uncertainty factors (UFs). These may suffice to derive a safe concentration of a substance associated to a predefined protection level to be used generically — that is, it is safe even in worst-case conditions. The greater the uncertainty in models or data for the extrapolations, the larger the overall UF in the lower tiers. The UF is applied to the risk assessment to account for unquantified uncertainties. In some cases, the factor depends on the amount of available data, or UFs per extrapolation are multiplied to provide the final factor (e.g., 10 x 10 x 10 as the UF for 3 assessment steps yields an overall factor of 1000). 

Assessors should base their selection of methods on clearly defined decision criteria, and they need to communicate the results using clear and transparent language. This includes statements on the extrapolation issues that were considered but not addressed, and the magnitude and direction of the bias that may have been introduced by the extrapolation or lack thereof. In lower tiers and prospective risk assessment, this should lead to setting more appropriate UFs and ensure that lower tier approaches are more conservative than higher tier approaches. All this helps assessors to make informed decisions, on one hand, but it also allows the identification of future research needs, on the other hand, especially when methods are not available. 

For the derivation of EQCs and the registration of substances (prospective risk assessment), worst-case assumptions are usually applied in the lower tiers, and UFs may be applied, whereas more specific data are used in higher tiers... 

Problems that have been solved in the risk assessment of single substances have not been solved equally well in mixture assessments. Even the most generic question in prospective risk analyses— What is a safe level —poses problems. Often the mixture composition is unknown, and the mixture problem is then that the safe level would only be applicable to that particular mixture. Even if the mixture composition is well characterized, the safe exposure or concentration level would apply only to mixtures with the same or similar concentration ratios between the mixture compounds, as in cigarette smoke, diesel exhaust, or some polychlorinated biphenyl (PCB) mixtures. One option in such cases is to set a safe level for the mixture by using one of the mixture components as an indicator compound for the whole mixture. If the concentration ratios between the mixture compounds vary, there is no unique safe mixture concentration, but an infinite number of possible safe concentration combinations. 

R.D. Combes, Prospects for using Data from (Q)SARs and Expert Systems in Integrated Testing Strategies for the Risk Assessment of Chemicals, Silico AMET Design of Bioactive Compounds, SCI Conference, London, UK, 2005. 

Worth AP and Balls M (eds.) (2002) Alternative (non-animal) methods for chemicals testing Current status and future prospects. Chapter 3 The scientific basis of chemical risk assessment. Alternatives to Laboratory Animals ATLA 30(Suppl. 1) 21-25. 

Dourson ML and Patterson J (2003) A 20-year prospective on the development of non-cancer risk assessment methods. Human and Ecological Risk Assessment 9 1239-1252. 

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