Predicting the potential hazard of contaminants

Around the world, the number of contaminants that may be found in water is increasing. In the case of new, emerging substances and for substances that may be produced in the environment or during water treatment (i.e. transformation products), often no or hardly any information is available about the toxicological properties and potentially adverse effects on human health and the environment. In silico models are designed to predict the toxicity of contaminants and they therefore represent a possible solution for filling data gaps.

QSAR and ‘read-across’

(Quantitative) structure-activity relationships – (Q)SARs – are used to determine, on the basis of the chemical structure, whether a substance can be expected to have an adverse effect on health or the environment. A ‘read-across’ compares the chemical structure of a contaminant with other substances to predict its potential adverse effects on humans and the environment. In the case of contaminants for which the toxicological information is very limited, an in silico approach is faster and more cost-effective than toxicological experiments.

Mitigating risks

The added value of in silico tools for water-quality issues consists of the prioritisation of follow-up research and an integrated approach to the assessment of safety and risks. This means that in silico tools are useful for the targeted selection and deployment of measures and decision-making processes to mitigate any risks associated with contaminants.

Schematic representation of applications of in silico models of toxicity for the prioritisation of contaminants for follow-up testing and interpretation of chemical analyses as part of water-quality monitoring.

Schematic representation of the application of in silico models for the assessment of hazards and risks associated with individual water-relevant contaminants.