Artificial Intelligence and Cancer Drug Development

Fan Yang; Jerry A. Darsey; Anindya Ghosh; Hong Yu Li; Mary Q. Yang; Shanzhi Wang

doi:10.2174/1574892816666210728123758

Artificial Intelligence and Cancer Drug Development

Fan Yang, Jerry A. Darsey, Anindya Ghosh, Hong Yu Li, Mary Q. Yang, Shanzhi Wang

Pharmacology and Toxicology

Research output: Contribution to journal › Short survey › peer-review

11 Scopus citations

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. Objectives: This review focused on the recent advancements 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.

Original language	English (US)
Pages (from-to)	2-8
Number of pages	7
Journal	Recent Patents on Anti-Cancer Drug Discovery
Volume	17
Issue number	1
DOIs	https://doi.org/10.2174/1574892816666210728123758
State	Published - Feb 1 2022

Keywords

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

ASJC Scopus subject areas

Oncology
Drug Discovery
Cancer Research
Pharmacology (medical)

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10.2174/1574892816666210728123758

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@article{2e766e6e04db49dbb445b3a3bf0b65c2,

title = "Artificial Intelligence and Cancer Drug Development",

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. Objectives: This review focused on the recent advancements 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, deep learning, drug design, drug discovery, machine learning, target validation",

author = "Fan Yang and Darsey, {Jerry A.} and Anindya Ghosh and Li, {Hong Yu} and Yang, {Mary Q.} and Shanzhi Wang",

note = "Funding Information: This study was funded by National Institute of General Medical Sciences, (NIGMS), P20 GM103429 from the National Institutes of Health. Funding Information: This publication was made possible by the Arkansas IN-BRE program, supported by a grant from the National Institute of General Medical Sciences, (NIGMS). Publisher Copyright: {\textcopyright} 2022 Bentham Science Publishers.",

year = "2022",

month = feb,

day = "1",

doi = "10.2174/1574892816666210728123758",

language = "English (US)",

volume = "17",

pages = "2--8",

journal = "Recent Patents on Anti-Cancer Drug Discovery",

issn = "1574-8928",

publisher = "Bentham Science Publishers B.V.",

number = "1",

}

TY - JOUR

T1 - Artificial Intelligence and Cancer Drug Development

AU - Yang, Fan

AU - Darsey, Jerry A.

AU - Ghosh, Anindya

AU - Li, Hong Yu

AU - Yang, Mary Q.

AU - Wang, Shanzhi

N1 - Funding Information: This study was funded by National Institute of General Medical Sciences, (NIGMS), P20 GM103429 from the National Institutes of Health. Funding Information: This publication was made possible by the Arkansas IN-BRE program, supported by a grant from the National Institute of General Medical Sciences, (NIGMS). Publisher Copyright: © 2022 Bentham Science Publishers.

PY - 2022/2/1

Y1 - 2022/2/1

N2 - 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. Objectives: This review focused on the recent advancements 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.

AB - 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. Objectives: This review focused on the recent advancements 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.

KW - Artificial intelligence

KW - deep learning

KW - drug design

KW - drug discovery

KW - machine learning

KW - target validation

UR - http://www.scopus.com/inward/record.url?scp=85125552956&partnerID=8YFLogxK

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U2 - 10.2174/1574892816666210728123758

DO - 10.2174/1574892816666210728123758

M3 - Short survey

C2 - 34323201

SN - 1574-8928

VL - 17

SP - 2

EP - 8

JO - Recent Patents on Anti-Cancer Drug Discovery

JF - Recent Patents on Anti-Cancer Drug Discovery

IS - 1

ER -

Artificial Intelligence and Cancer Drug Development

Abstract

Keywords

ASJC Scopus subject areas

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