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Letters in Drug Design & Discovery

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ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

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Review Article

A Brief Study on Drug Repurposing: New Way of Boosting Drug Discovery

Author(s): Kamal Kant Kaushik, Rupa Mazumder*, Abhijit Debnath and Manisha Patel

Volume 20, Issue 3, 2023

Published on: 06 October, 2022

Page: [264 - 278] Pages: 15

DOI: 10.2174/1570180819666220901170016

Price: $65

Abstract

Background: Even with the massive increase in financial investments in pharmaceutical research over the last decade, the number of new drugs approved has plummeted. As a result, finding new uses for approved pharmaceuticals has become a prominent alternative approach for the pharmaceutical industry.

Objective: Drug repurposing or repositioning is a game-changing development in the field of drug research that entails discovering additional uses for previously approved drugs.

Methods: In comparison to traditional drug discovery methods, drug repositioning enhances the preclinical steps of creating innovative medications by reducing the cost and time of the process. Drug repositioning depends heavily on available drug-disease data, so the fast development of available data as well as developed computing skills has resulted in the boosting of various new drug repositioning methods. The main goal of this article is to describe these different methods and approaches for drug repurposing.

Results: The article describes the basic concept of drug repurposing, its significance in discovering new medications for various disorders, drug repurposing approaches such as computational and experimental approaches, and previous as well as recent applications of drug repurposing in diseases such as cancer, COVID-19, and orphan diseases.

Conclusion: The review also addresses obstacles in drug development using drug repurposing strategies, such as a lack of financing and regulatory concerns and concludes with outlining recommendations for overcoming these challenges.

Keywords: Drug repurposing, Drug repositioning, Computational methods, Machine learning, Docking, Pharmacogenomics, Orphan diseases, COVID-19, Cancer.

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