Current Trends in Biotechnology and Pharmacy

Open Access
SCOPUS
  • Year: 2023
  • Volume: 17
  • Issue: 2

A Comprehensive Review on Technological Advances in Alternate Drug Discovery Process: Drug Repurposing

  • Author:
  • Madhuri Pola1,*, Alok Tiwari1, Potla Durthi Chandrasai2
  • Total Page Count: 10
  • Page Number: 907 to 916

1uGDX School of Technology, ATLAS SkillTech University, Tower 1-Equinox Business Park, Off Bandra-Kurla Complex, LBS Marg, Kurla West, Mumbai-400070

2Department of Biotechnology, National Institute of Technology Warangal, Warangal, Telangana, India-506004

Abstract

The traditional de novo drug discovery is time consuming, costly and in some instances the drugs will fail to treat the disease which result in a huge loss to the organization. Drug repurposing is an alternative drug discovery process to overcome the limitations of the De novo drug discovery process. Ithelps for the identification of drugs to the rare diseases as well as in the pandemic situationwithin short span of time in a cost-effective way. The underlying principle of drug repurposing is that most of the drugs identified on a primary purpose have shown to treat other diseases also. One such example is Tocilizumab is primarily used for rheumatoid arthritis and it is repurposed to treat cancer and COVID-19. At present, nearly 30% of the FDA approved drugs to treat various diseases are repurposed drugs. The drug repurposing is either drug-centric or disease centric and can be studied by using both experimental and in silico studies. The in silico repurpose drug discovery process is more efficient as it screens thousands of compounds from the diverse libraries within few days by various computational methods like Virtual screening, Docking, MD simulations, Machine Learning, Artificial Intelligence, Genome Wide Association Studies (GWAS), etc. with certain limitations. These limitationscan be addressed by effective integration of advanced technologies to identify a novel multi-purpose drug.

Keywords

Drug repurposing, Screening, Drug-centric, Disease-centric, FDA, Pandemic, GWAS, Machine Learning, Artificial Intelligence