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Computational approaches have been proven to be complementary tools of interest in identifying
potential candidates for drug repurposing. However, although the methods developed so far
offer interesting opportunities and could contribute to solving issues faced by the pharmaceutical
sector, they also come with their constraints. Indeed, specific challenges ranging from data access,
standardization and integration to the implementation of reliable and coherent validation methods
must be addressed to allow systematic use at a larger scale. In this mini-review, we cover computational
tools recently developed for addressing some of these challenges. This includes specific databases
providing accessibility to a large set of curated data with standardized annotations, web-based
tools integrating flexible user interfaces to perform fast computational repurposing experiments and
standardized datasets specifically annotated and balanced for validating new computational drug repurposing
methods. Interestingly, these new databases combined with the increasing number of information
about the outcomes of drug repurposing studies can be used to perform a meta-analysis to
identify key properties associated with successful drug repurposing cases. This information could
further be used to design estimation methods to compute a priori assessment of the repurposing possibilities.
