BMC Medical Informatics and Decision Making is calling for submissions to our Collection on "Computational techniques for drug repositioning".
Developing a drug for a specific condition is a remarkably costly task in terms of money, time, and risks. An alternative approach to this lengthy process is drug repurposing, which tries to identify other uses for drugs that already exist. The problem is addressed by using known drugs to treat other diseases different from the ones they were developed for. This way, some of the phases of developing a drug can be skipped, being more efficient and reducing the investment. Although this process used to occur by chance in the beginning, nowadays drug repurposing can be targeted. Some of the most promising strategies derive from computational methodologies. In contrast with experimental or activity-based methods, computational drug repurposing employs online public databases and bioinformatic tools to detect interactions between drugs, targets, and diseases.
This collection welcomes studies on the latest advances in the field of data-driven drug repurposing/repositioning through the use of computational techniques and strategies, presenting theoretical approaches as well as practical (validated) methods. This includes but is not limited to retrospective clinical analyses, exploitation of real-world data, studies involving machine learning and artificial intelligence techniques and applying generative AI paradigms, data integration, signature matching, molecular docking, GWAS, pathway mapping or network analysis.
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