In silico drug repositioning: from large-scale transcriptome data to therapeutics

Ok Seon Kwon, Wankyu Kim, Hyuk Jin Cha, Haeseung Lee

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations

Abstract

Drug repositioning is an attractive alternative to conventional drug development when new beneficial effects of old drugs are clinically validated because pharmacokinetic and safety profiles are generally already available. Since ~ 30% of drugs newly approved by the US food and drug administration (FDA) are developed through drug repositioning, identifying novel usage for existing drugs is an emerging strategy for developing disease treatments. With advances in next-generation sequencing technologies, available transcriptome data related to diseases have expanded rapidly. Harnessing these resources enables a better understanding of disease mechanisms and drug mode of action (MOA), and moves toward personalized pharmacotherapy. In this review, we briefly outline publicly available large-scale transcriptome databases and tools for drug repositioning. We also highlight recent approaches leading to the discovery of novel drug targets, drug response biomarkers, drug indications, and drug MOA.

Original languageEnglish
Pages (from-to)879-889
Number of pages11
JournalArchives of Pharmacal Research
Volume42
Issue number10
DOIs
StatePublished - 1 Oct 2019

Keywords

  • Big data
  • Drug repositioning
  • In silico drug repositioning
  • Pharmacogenomics
  • Transcriptome

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