Weight-of-evidence WOE approach in assessing mixture effects

2007) to observations on pollution-induced community tolerance (Blanck 2002). Since most ecoepidemiological studies have a wider scope than the exclusive analysis and assessment of mixture risks, they are not treated in depth here. 

1) Concentration additivity (CA) for similarly acting chemicals as a mathematical null model for testing observed responses (associated with the pharmacological concept of simple similar action) often fits well or quite well to the data, but misfits do occur, and when they occur, they are often in the tails of the response curves. 

3) Well-designed tests, with powerful test designs and clear working hypotheses on the (differences in) MOA of the compounds in the mixture, allow for differentiation between the different null models assumed similar MOA mixtures fit best to CA predictions, and assumed dissimilar MOA mixtures fit best to RA predictions. 

4) No pattern can be derived from a scientific review of the (few) available data for the community level, but there (again) the pharmacological null models may be of help in the analysis and characterization of the observed responses in relation to the expectations from the classical toxicological null models (e.g., Backhaus et al. 2004). 

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Figure 5.7 Weight-of-evidence (WOE) approach in assessing mixture effects. Three Lines of Evidence (LOE) are considered, in a tiered fashion (simple and quick methods in the tier-1, more complex methods in higher tiers). For each LOE, the response is scaled between 0 and 1. The LOEs can indicate a similar type of response, which results in a low Coefficient of Variation (CV), or differences (high CV). When the CV is lower than a predefined value, the assessment is stopped, and a decision (e.g., on remediation) is taken. TU = Toxic Unit, PAF = Probably Affected Fraction of species.

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