In recent years, the need to generate toxicological data using methods other than animal experimentation has become apparent, leading to the extensive development of computational toxicology. Specifically, methods based on Quantitative Structure-Activity Relationships (QSAR) are computational models that predict the properties of a substance based on its molecular structure and are now widely recognized for the study of certain toxicological parameters.

The " expert " (or " rule-based ") QSAR systems are developed on the basis of bibliographic data that allow the toxicity associated with specific structural groups, called toxicophores, to be identified empirically.

Statistical QSAR systems are based on empirical data that allow assigning a toxicological probability value based on the presence of functional groups, physicochemical properties, adjacent groups and the chemical environment in the molecule under study. The combination of both "expert" and "statistical" QSAR studies will allow the accurate prediction of some toxicological parameters such as mutagenicity, avoiding in many cases in vitro and in vivo experimental tests.

At Dalia we have a team of toxicologists with extensive experience in the use of statistical and expert QSAR models in the development of toxicological evaluations of impurities or molecules under development.

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