English

Quantum-machine-assisted Drug Discovery

Quantum Physics 2026-01-08 v5 Machine Learning Biomolecules

Abstract

Drug discovery is lengthy and expensive, with traditional computer-aided design facing limits. This paper examines integrating quantum computing across the drug development cycle to accelerate and enhance workflows and rigorous decision-making. It highlights quantum approaches for molecular simulation, drug-target interaction prediction, and optimizing clinical trials. Leveraging quantum capabilities could accelerate timelines and costs for bringing therapies to market, improving efficiency and ultimately benefiting public health.

Keywords

Cite

@article{arxiv.2408.13479,
  title  = {Quantum-machine-assisted Drug Discovery},
  author = {Yidong Zhou and Jintai Chen and Jinglei Cheng and Xu Cao and Yuanyuan Zhang and Gopal Karemore and Marinka Zitnik and Frederic T. Chong and Junyu Liu and Tianfan Fu and Zhiding Liang},
  journal= {arXiv preprint arXiv:2408.13479},
  year   = {2026}
}

Comments

23 pages, 4 figures

R2 v1 2026-06-28T18:22:47.425Z