Computational Drug Repurposing

Dear Colleagues,

With daunting costs in the billions of dollars and time-to-market over a decade, the current drug-discovery pipeline is inefficient and unsustainable. To continue finding novel and potentially more effective drugs for diseases, there must be a paradigm shift towards expeditious and relatively inexpensive pipelines. Computational drug repurposing, i.e., finding new treatments for diseases using FDA approved drugs via computational methods, is one alternative method for increasing the efficacy of pharmaceutical research that has been gaining traction in recent years. Using modern computational tools to narrow the search for efficacious drugs from a pool of drugs greatly decreases cost due to fewer drugs being needed to be experimentally tested to validate effectiveness. Furthermore, since all of the drugs being considered are FDA-approved, their toxicity and side effects profile are known, and the time from bench-to-bedside for a new indication is reduced due to the fact that they have already been subjected to clinical trials.  

Drug repurposing has become a burgeoning topic of research in pharmaceutical research, in both academia and industry, for its potential to discover new therapeutic uses for old drugs. Many different approaches are being taken for drug repurposing, and even with the large number of journal articles describing the myriad of methods being developed, there has been no effort to assemble a comprehensive collection of knowledge of this field, specifically focused on computational methods, to have as a reference for novices and experts alike. In this Special Issue of Pharmaceutics, an understanding of how state-of-the-art computational drug repurposing methods make the drug-discovery process more efficient, as well as the juxtaposition of drug repurposing and drug-design methods, will be comprehensively explored. 

Prof. Dr. Ram Samudrala
Dr. Zackary Falls
Guest Editors

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