ABSTRACT
The effect a chemical exerts on a system is dependent on its structure and
properties. If one can determine the nature of this dependence, then models may
be constructed to allow for extrapolation of this knowledge to other chemicals.
Broadly speaking, this is the basis of (quantitative) structure-activity relationships
[(Q)SARs] whereby knowledge of a chemical’s structure and its properties is related
to its effects. When this knowledge is applied to toxicological endpoints, this helps
to reduce testing requirements. The science of (Q)SAR in toxicology is now a broad
area including SARs, QSARs, expert systems, read across, analogs, and categories.
It is variously known as computational toxicology, predictive toxicology, and in
silico toxicology, amongst other descriptions. For a more detailed review of the area,
the reader is referred to recent volumes edited by Cronin and Livingstone (1) and
Helma (2).
