Mode of toxic action

Day by day, the number of scientific works and techniques based on in vitro tools has increased their relevancy, supporting the hypothesis of the use of in vitro models as refinement technique due to their ability to provide information on central events involved in toxicant mode of action. 

Available data from field and/or laboratory studies must be sufficient to reduce uncertainty. Most applicable to well-studied substances with a similar toxic mode of action. 

BOX 5.2 Example of a spreadsheet calculation of toxic risk (msPAF) for a species assemblage in an imaginary aquatic pond as the result of exposure to a mixture of toxicants with diverse and species-dependent toxic modes of action. Note Overall risk values (msPAF) per species group were calculated assuming concentration addition within common modes of action and response addition between modes of action. This example only serves to demonstrate the method of calculation. The SSD information on the mixture constituents as well as the total and bioeffective concentrations in pond water were randomly selected by realistic expert judgement. The gray cells contain examples of the formulas applied. 

Maltby et al. (2002) and Van den Brink et al. (2006a) compared SSDs based on acute and chronic laboratory toxicity data for aquatic test species exposed to pesticides. The SSDs were constructed with toxicity data for the most sensitive taxonomic group, because of the specific toxic mode of action of the pesticides selected. The SSDs were used to calculate the hazardous concentration to 5% of the species (HC5) by means of a log-normal distribution model, and comparisons were performed for 2 insecticides and 7 herbicides (Table 6.4). The log-normal model did not fit the diuron (herbicide) short-term L(E)C50 data or the atrazine (herbicide) long-term NOEC data. Consequently, the L(E)C50 HC5 value for diuron and the NOEC HC5 value for atrazine should be interpreted with caution, as well as their acute HC5-chronic... 

More chronic toxicity data on compounds with other toxic modes of action are required before a more robust generalization can be offered. 

For most pesticides evaluated, an uncertainty factor of 10 to 15 seems to suffice to extrapolate a median acute HC5 to a median chronic HC5, at least when based on toxicity data of sensitive taxonomic groups. In addition, it appears from model ecosystem experiments with pesticides that threshold concentrations for chronic exposures are approximately a factor of 10 lower than those for acute exposure. For a wider generalization, however, more data are required on compounds that differ in toxic mode of action (Section 6.2.4). 

A tiered system for mixture extrapolation is proposed. The lowest tier is based on extrapolation using toxicological point-estimate information such as EC50 values. This translates into the use of toxic units, toxic equivalencies, and similar techniques. The use of the entire concentration-response relationships of the separate compounds is recommended for Tier-2, in conjunction with the use of either concentration or response addition as a modeling approach. In Tier-3, a mixed-model approach can be considered, to more specifically address considerations on toxic modes of action. In the latter case, the approach may be extended to allow incorporation of the responses of different ecological receptors (Tier-4). Research needs have been clearly identified in community-level mixture assessments. 

Associated with the Aspect "Toxic Mode of Action (TMoA)"... 

Recent applications of CPSA descriptors include QSAR investigations of the genotoxicity of thiophene derivatives (Mosier et al., 2003) as well as of secondary and aromatic amines (Mattioni et al., 2003) and a study to classify phenols with respect to toxic modes of action (Aptula et al., 2003). A somewhat different route has been explored with the concept of dynamic molecular surface areas (Lipkowitz et al., 1989) that represent Boltzmann-weighted means of surface areas of different conformations within a preset energy window (e.g., within an excess of 10.5 kJ/mol above the lowest energy found for the particular molecule). Following this strategy, so-called dynamic polar... 

Boxall, A.B.A., Watts, C.D., Dearden, J.C., Bresnen, G.M., and Scoffin, R., Predicting the toxic mode of action for environmental pollutants based on physico-chemical properties, in Quantitative Structure-Activity Relationships in Environmental Sciences - VII, Chen, F. and Schiiurmann, G., Eds., SETAC Press, Pensacola, FL, 1997, pp. 263-275. 

Component-Based Methods. Component-based approaches (Figure 5.5) are generally used to evaluate human health risks from exposure to a limited number of chemicals as a mixture. Key issues for component-based assessments include similarity in dose-response curves and similar vs. independent toxic modes of action (MOAs) among mixture components. A distinction can be made between 1) assessments using relatively simple additivity methods without the consideration of potential interaction effects, and 2) assessments that include data on toxicological interactions. Both types of assessments are discussed in more detail below. 

The RPF method is based on dose addition and assumes that the chemicals in a mixture share a common toxic mode of action this means that when tested in the same bioassay, the dose response curves of each component should be similarly shaped. The components in this similarity group are assumed to be true toxicologic clones of each other and have... 

When mixture component chemicals are determined to act through independent toxic modes of action, response addition is recommended. When component chemicals act via a similar toxic mode of action, dose addition is recommended [1]. In response addition, the net response estimated for the mixture is equivalent to the sum of the individual component responses [1], The assumption is that for a toxicity following exposure to a mixture, the type or degree of adverse effect caused by one mixture component has no direct impact on the type or degree of adverse effect caused by a second component. Response addition requires dose-response data for all components of a mixture sufficient to define the slope of the dose-response carve with a degree of certainty sufficient to support predictions of risk at uncharacterized, environmentally relevant doses. 

Basak SC, Grunwald GD, Host GE, Niemi GJ, Bradbury SP. A comparative study of molecular similarity, statistical, and neural methods for predicting toxic modes of action. Environ Toxicol Chem 1998 17 1056-64. 

Pino, A., Giuliani, A. and Benigni, R. (2003) Toxicity mode-of-action discrimination via infrared spectra and eigenvalues of the modified adjacency matrix. Quant. Struct. -Act. Relat., 22, 1-5. 

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