Artificial Intelligence–Driven Computational Approaches in the Development of Anticancer Drugs
Year: 2024
Type: article
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.
Source: Cancers
Authors: Pankaj Garg, Gargi Singhal, Prakash Kulkarni, David Horne, Ravi Salgia, Sharad S. Singhal
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,296
Funder: U.S. Department of Defense
OpenAlex ID: W4404539855