Drug Discovery Acceleration Using Quantum Simulations

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, Issue 4, pp. 47-56, April 2026.

https://doi.org/10.58482/ijersem.v2i4.7

This work is licensed under a Creative Commons Attribution 4.0 International License.

Drug Discovery Acceleration Using Quantum Simulations

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R. G. Kumar

V. Sambasiva Reddy

G. Neha Chowdary

Amuru Vishnu Sai

V. Trisha

Gundluru Sahil

1Professor, Department of CSE, Siddarth Institute of Engineering & Technology, Puttur, India.

2Assistant Professor, Department of CSE, Siddarth Institute of Engineering & Technology, Puttur, India.

3-6UG Scholar, Department of CSE, Siddarth Institute of Engineering & Technology, Puttur, India.

Abstract: This paper presents a software quantum computing techniques with advanced computational models to accelerate the drug discovery process. Quantum simulations are utilized to model molecular structures, interactions, and chemical properties with high precision, enabling accurate prediction of drug behavior and binding affinities. The generated data is processed and analyzed using intelligent algorithms to identify promising drug candidates efficiently. By combining quantum-based computation with data-driven optimization, the framework enhances accuracy, reduces computational complexity, and speeds up the overall discovery pipeline. This approach ensures reliable results, minimizes experimental costs, and improves decision-making in pharmaceutical research. Overall, the proposed system provides a powerful and efficient solution for accelerating drug development, particularly benefiting modern healthcare and biomedical research.

Keywords: Drug Discovery, Quantum Simulation, Computational Model, Health Care, Data-driven Optimization.

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This article is part of Volume 2, Issue 4 (April 2026)