Quantum-machine-assisted drug discovery

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.

• NS
  National Science Foundation

  Awards: 1818914, CCF-1730449, 2519029, 2016136, DE-AC05-00OR22725, NSF Phy-1818914, 1730449
• UD
  U.S. Department of Energy

  Awards: AC05-00OR22725, DE-AC05, 00OR22725
• UO
  University of Pittsburgh
• OO
  Office of Science

  Awards: DE-AC05-00OR22725, AC05-00OR22725
• AS
  Advanced Scientific Computing Research

  Award: DE-AC05-00OR22725
• AR
  Army Research Office

  Awards: W911NF-23-1-0077, W911NF