Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

doi:10.1007/s12257-020-0049-y

Review

. 2020;25(6):895-930.

doi: 10.1007/s12257-020-0049-y. Epub 2021 Jan 7.

Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

Hyunho Kim¹, Eunyoung Kim¹, Ingoo Lee¹, Bongsung Bae¹, Minsu Park¹, Hojung Nam¹

Affiliations

PMID: 33437151
PMCID: PMC7790479
DOI: 10.1007/s12257-020-0049-y

Review

Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

Hyunho Kim et al. Biotechnol Bioprocess Eng. 2020.

. 2020;25(6):895-930.

doi: 10.1007/s12257-020-0049-y. Epub 2021 Jan 7.

Authors

Hyunho Kim¹, Eunyoung Kim¹, Ingoo Lee¹, Bongsung Bae¹, Minsu Park¹, Hojung Nam¹

Affiliation

¹ School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, 61005 Korea.

PMID: 33437151
PMCID: PMC7790479
DOI: 10.1007/s12257-020-0049-y

Abstract

As expenditure on drug development increases exponentially, the overall drug discovery process requires a sustainable revolution. Since artificial intelligence (AI) is leading the fourth industrial revolution, AI can be considered as a viable solution for unstable drug research and development. Generally, AI is applied to fields with sufficient data such as computer vision and natural language processing, but there are many efforts to revolutionize the existing drug discovery process by applying AI. This review provides a comprehensive, organized summary of the recent research trends in AI-guided drug discovery process including target identification, hit identification, ADMET prediction, lead optimization, and drug repositioning. The main data sources in each field are also summarized in this review. In addition, an in-depth analysis of the remaining challenges and limitations will be provided, and proposals for promising future directions in each of the aforementioned areas.

Keywords: artificial intelligence; data-driven; drug discovery; machine learning.

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References

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[1] J. A D, Grabowski H G, Hansen R W. Innovation in the pharmaceutical industry: New estimates of R&D costs. J. Health Econ. 2016;47:20–33. doi: 10.1016/j.jhealeco.2016.01.012. - DOI - PubMed

[2] J. A D, Grabowski H G, Hansen R W. Innovation in the pharmaceutical industry: New estimates of R&D costs. J. Health Econ. 2016;47:20–33. doi: 10.1016/j.jhealeco.2016.01.012. - DOI - PubMed

[3] S. M P, Mytelka D S, Dunwiddie C T, Persinger C C, Munos B H, Lindborg S R, Schacht A L. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat. Rev. Drug Discov. 2010;9:203–214. doi: 10.1038/nrd3078. - DOI - PubMed

[4] S. M P, Mytelka D S, Dunwiddie C T, Persinger C C, Munos B H, Lindborg S R, Schacht A L. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat. Rev. Drug Discov. 2010;9:203–214. doi: 10.1038/nrd3078. - DOI - PubMed

[5] H v d W, Gifford E. ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug Discov. 2003;2:192–204. doi: 10.1038/nrd1032. - DOI - PubMed

[6] H v d W, Gifford E. ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug Discov. 2003;2:192–204. doi: 10.1038/nrd1032. - DOI - PubMed

[7] K. K M, Pichika M R. Artificial intelligence in drug development: present status and future prospects. Drug Discov. Today. 2019;24:773–780. doi: 10.1016/j.drudis.2018.11.014. - DOI - PubMed

[8] K. K M, Pichika M R. Artificial intelligence in drug development: present status and future prospects. Drug Discov. Today. 2019;24:773–780. doi: 10.1016/j.drudis.2018.11.014. - DOI - PubMed

[9] X Y, Wang Y, Byrne R, Schneider G, Yang S. Concepts of artificial intelligence for computer-assisted drug discovery. Chem. Rev. 2019;119:10520–10594. doi: 10.1021/acs.chemrev.8b00728. - DOI - PubMed

[10] X Y, Wang Y, Byrne R, Schneider G, Yang S. Concepts of artificial intelligence for computer-assisted drug discovery. Chem. Rev. 2019;119:10520–10594. doi: 10.1021/acs.chemrev.8b00728. - DOI - PubMed

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Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

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Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

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