Drug repositioning: identifying and developing new uses for existing drugs

By Ted T. Ashburn, K. Thor. Nature reviews. Drug discovery, 2004

2,972 citations recorded by the source corpus.

Subfields: Oncology, Pharmacology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/75d4215306e82bb2e286dbd472bc78ffd2c8251b

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Citations in the corpus

Mechanisms of drug combinations: interaction and network perspectives (2009, background): “Although new drugs have continuously been discovered, there is a growing productivity gap, despite major spending on research and development and advances in technology developmen”
Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties (2012, background): “Furthermore, predictions on clinically approved drugs is expected to reveal candidates for drug repurposing and potentially identify specific disease sub-types that would be most responsive [8].”
Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases (2018, methodology): “In addition, the computational approaches mainly employed in VS can also be used for drug repurposing and off target effect identification, where the aim is to find new uses for the already approved drugs [14].”
Prediction of Drug-Target Interactions and Drug Repositioning via Network-Based Inference (2012, background): “Some good examples are thalidomide, sildenafil, bupropion and fluoxetine [4,5].”
Exploiting drug-disease relationships for computational drug repositioning (2011, background): “Some of the most profitable and successful pharmaceuticals did not begin development for their current indications, but instead were re-purposed or repositioned for new uses [4].”
Integrating virtual screening and combinatorial chemistry for accelerated drug discovery. (2011, background): “Collections of approved drugs, such as DrugBank [35], are attractive sources for drug repurposing and drug repositioning which are aimed to speed up the drug development process [36, 37].”
Combination therapy in combating cancer (2017, background): “This approach is efficient because the FDA-approved drug would have already passed drug safety protocols and has a known pharmacokinetic profile [27].”
The genome of the blood fluke Schistosoma mansoni (2009, positive): “In the context of neglected tropical diseases and with constrained investment in drug discovery, piggy-backing 37 or ‘drug-repositioning’ strategies 42 that re-use existing drugs offer potential time-saving and costbenefits.”
Shaping the interaction landscape of bioactive molecules (2013, background): “, 2012), or (ii) to predict a new target for an approved drug and reposition it for another disease (Ashburn and Thor, 2004; Keiser et al., 2009; Novac, 2013).”
Systematic integration of biomedical knowledge prioritizes drugs for repurposing (2017, background): “Drug repur-posing — identifying novel uses for existing therapeutics — can drastically reduce the duration, failure rates, and costs of approval ( Ashburn and Thor, 2004 ).”