Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs

The integration of AI has revolutionized cancer drug development, transforming the landscape of drug discovery through sophisticated computational techniques. AI-powered models and algorithms have enhanced computer-aided drug design (CADD), offering unprecedented precision in identifying potential anticancer compounds. Traditionally, cancer drug design has been a complex, resource-intensive process, but AI introduces new opportunities to accelerate discovery, reduce costs, and optimize efficiency. This manuscript delves into the transformative applications of AI-driven methodologies in predicting and developing anticancer drugs, critically evaluating their potential to reshape the future of cancer therapeutics while addressing their challenges and limitations.

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Publication Details

Journal
Cancers
Published
2024-11-20
DOI
https://doi.org/10.3390/cancers16223884
Citations
34
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
12.29
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article

Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs

Ravi Salgia, G. D. Singhal, Pankaj Garg, David Horne et al.
34 citations
Cancers
Computational Drug Discovery Methods
12.29
article

Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs

Ravi Salgia, G. D. Singhal, Pankaj Garg, David Horne, Sharad S. Singhal, Prakash Kulkarni
article en
34 citations

Abstract

The integration of AI has revolutionized cancer drug development, transforming the landscape of drug discovery through sophisticated computational techniques. AI-powered models and algorithms have enhanced computer-aided drug design (CADD), offering unprecedented precision in identifying potential anticancer compounds. Traditionally, cancer drug design has been a complex, resource-intensive process, but AI introduces new opportunities to accelerate discovery, reduce costs, and optimize efficiency. This manuscript delves into the transformative applications of AI-driven methodologies in predicting and developing anticancer drugs, critically evaluating their potential to reshape the future of cancer therapeutics while addressing their challenges and limitations.

CancersVol. 16(22)
City Of Hope National Medical Center (US), Sarojini Naidu Medical College (IN), City of Hope (US), GLA University (IN)
Openalex Percentile: Top 1%
Computational Drug Discovery Methods
12.29
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Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs — Ravi Salgia, G. D. Singhal, et al. · Cancers (2024) | TGRS Research Map | TGRS