Quantum-machine-assisted Drug Discovery

TL;DR

This paper explores how quantum computing can revolutionize drug discovery by accelerating molecular simulations, improving interaction predictions, and optimizing clinical trials, thereby reducing costs and timelines.

Contribution

It introduces quantum computing applications across the entire drug development process, highlighting potential improvements over classical methods.

Findings

Quantum approaches can significantly speed up molecular simulations.

Quantum algorithms may improve accuracy in drug-target interaction predictions.

Quantum optimization can streamline clinical trial design.

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.