Quantum computing in drug discovery

Keywords: quantum computing, qubits, drugs, algorithms, machine learning

Abstract

Quantum computers are recently being developed in wide varieties, but the computational results from quantum computing have been largely confined to constructing artificial assignments. The applications of quantum computers to real-world problems are still an active area of research. However, challenges arise when the limits of scale and complexity in biological problems are pushed, which has affected drug discovery. The fast-evolving quantum computing technology has transformed the computational capabilities in drug research by searching for solutions for complicated and tedious calculations. Quantum computing (QC) is exponentially more efficient in drug discovery, treatment, and therapeutics, generating profitable business for the pharmaceutical industry. In principle, it can be stated that quantum computing can solve complex problems exponentially faster than classical computing. Here it is needed to mention that QC will not be able to take on every task that classical computers perform—at least not now. It may be classical and quantum-coupled computational technologies combined with machine learning (ML) and artificial intelligence (AI) will solve each task in the future. This review is an overview of quantum computing, which may soon revolutionize the pharmaceutical industry in drug discovery.

Author Biography

Ruby Srivastava, CSIR-Centre for Cellular and Molecular Biology
Principal Investigator, Bioinformatics

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Published
2023-12-11
How to Cite
Srivastava, R. (2023). Quantum computing in drug discovery. Information System and Smart City, 3(1). https://doi.org/10.59400/issc.v3i1.294
Section
Review Articles