Chemical Drug Design
Year: 2024
Type: article
Abstract: Drug discovery and development are intricate processes that traditionally involve numerous costly and time-consuming experimental steps. AI has emerged as a game-changer in this domain, offering a suite of tools and techniques that can significantly expedite the drug design process while reducing costs and enhancing success rates. AI-aided drug design leverages machine learning algorithms, deep learning models, molecular simulations, and big data analytics to streamline various stages of drug discovery, from target identification to lead optimization and pharmacokinetics evaluation.
Author: Janet Smith
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6892952778
FWCI:
Cites:
Cited by:
Related to: