Chemical Drug Design

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-12
DOI
https://doi.org/10.5281/zenodo.13752976
Primary Topic
GABA and Rice Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Chemical Drug Design

Zenodo (CERN European Organization for Nuclear Research)
GABA and Rice Research
article

Chemical Drug Design

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 77%
GABA and Rice Research
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Chemical Drug Design · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS