Abstract

The identification of safe and effective compounds is at the core of the compound development process. The richness of publicly available datasets opened unprecedent horizons for the development of data-driven methodologies. However, traditional methods often neglect the interactions between the compounds and the exposed biological systems, resulting in uncomprehensive safety and efficacy assessment. Toxicogenomics aims at explaining the underlying biological mechanisms associated with compound exposures and at linking them with their efficacy and safety assessment. Moreover, by following the 3R principles (replacement, reduction, refinement of animal experiments), toxicogenomic-based approaches can facilitate the reduction of in vivo assays with in vitro testing. Methodologies that combine cheminformatics and bioinformatics data and techniques have the potential to advance the development of new effective and safe compounds. In this chapter, we identified relevant datasets for the development of integrative models, we review existing computational models, and we discuss their methodologies to promote their growth in the compound development field.

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