Quantum-machine-assisted Drug Discovery
This addresses the problem of inefficient drug discovery for pharmaceutical companies and public health, but it is incremental as it builds on existing quantum computing ideas without new results.
The paper tackles the slow and costly process of drug discovery by integrating quantum computing across the drug development cycle, potentially accelerating timelines and reducing costs for bringing therapies to market.
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.