The main goal of risk assessment is the overall protection of not only the ecological communities in the aquatic
environment but also the human health of people living in contact , either directly or indirectly , with water (e.g.,
drinking water consumption, dietary intake of foods irrigated with water). In the past , the procedure for assessing the
ecological risk of a substance consisted basically of comparing its concentrations in environmental compartments
(predicted environmental concentration, PEC) with concentrations below which unacceptable/adverse effects on
organisms will most likely not occur (predicted no effect concentration, PNEC)(Lepper, 2002). However,this
procedure has significant difficulties, e.g.how to deal with the different PNEC values reported for a single species.
The approach for human health risk assessment is slightly different , as human exposure through different pathways is
estimated,prior to the comparison with threshold levels of non-carcinogenic and carcinogenic risk (reference doses
and slope factors,respectively). In this framework, risk assessment usually depends on the robustness and quality of
databases,as toxicity and ecotoxicity endpoints may differ depending on the sources of literature.Therefore, for an
accurate evaluation of ecological and health risks, including human exposure, uncertainty and variability aspects
must be considered as essential. In recent years, Intelligent Testing Strategies (ITS) have become increasingly
employed by the scientific community and considered as viable tools for studying chemical substances , with a clear
cost reduction and animal testing minimization. Components of ITS include the integration of a series of
complementary methodologies , such as Quantitative Structure - Activity Relationships (QSARs),read-across models
(or chemical categorization),thresholds of toxicological concern,exposure information, in vitro testing methodol -
ogies ,as well as other in silico (or computational) models. This integration favours the minimization of weaknesses
and of strengths of each one of the methodologies.