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Artificial Intelligence and Cancer Drug Development

Author(s):

Fan Yang, Jerry A. Darsey, Anindya Ghosh, Hong-Yu Li, Mary Q. Yang and Shanzhi Wang*   Pages 1 - 7 ( 7 )

Abstract:


Background: The development of cancer drugs is among the most focused “bench to bedside activities” to improve human health. Because of the amount of data publicly available to cancer research, drug development for cancers has significantly benefited from big data and Artificial Intelligence (AI). In the meantime, challenges, like curating the data of low quality, remain to be resolved.

Objective: This review focused on the recent advancements in and challenges of AI in developing cancer drugs.

Methods: We discussed target validation, drug repositioning, de novo design, and compounds' synthetic strategies.

Results and Conclusion: AI can be applied to all stages during drug development, and some excellent reviews detailing the applications of AI in specific stages are available.

Keywords:

Artificial intelligence, drug design, target validation, drug discovery, deep learning, machine learning.

Affiliation:

Healthville Primary Care, Little Rock, AR 72211, Department of Chemistry, University of Arkansas at Little Rock, AR 72204, Department of Chemistry, University of Arkansas at Little Rock, AR 72204, University of Arkansas for Medical Sciences, Little Rock, AR 72204, Department of Information Science, University of Arkansas at Little Rock, AR 72204, Department of Chemistry, University of Arkansas at Little Rock, AR 72204



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