Application of Artificial Intelligence and Machine Learning in Drug Discovery and Development

Authors

  • Madhukiran Parvathaneni Professor, Biotechnology, Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101 https://orcid.org/0000-0003-2747-4882
  • Abduselam K. Awol Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101
  • Monika Kumari Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101
  • Ke Lan Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101
  • Manisha Lingam Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Abstract

Drug discovery has traditionally been a time consuming and expensive endeavor. Additionally, drugs weren’t as effectively designed as those that are being predicted and developed through AI and ML today. Machine learning is a form of artificial intelligence that develops and evolves based on experience (similarly to the human mind), and is more recently being utilized in drug discovery and design. The integration of AI and ML into the drug discovery and development process has allowed for higher target precision, lower toxicity, and better dosage formulations. AI more generally has been introduced to and has been leveraged at, each step of drug development, including target identification and validation, hit identification, as well as hit to lead optimization, and has been key in shortening the previously lengthy drug screening process. AI and ML has also been applied downstream in drug formulation where it has maximized resource utilization and is allowing for web-based 3D printing of drugs. Application of AI in the drug development process has also been extended to the modeling of novel drug-like compounds to predict their ADMET properties. This review will address the stages of drug discovery and development in which the application of AI and ML modeling has altered the traditional development of drugs.

Keywords: Drug discovery, machine learning, artificial intelligence, computational drug development.

Keywords:

Drug discovery, machine learning, artificial intelligence, computational drug development

DOI

https://doi.org/10.22270/jddt.v13i1.5867

Author Biographies

Madhukiran Parvathaneni, Professor, Biotechnology, Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Abduselam K. Awol, Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Monika Kumari, Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Ke Lan, Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Manisha Lingam, Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

Harrisburg University of Science and Technology, Harrisburg, Pennsylvania, USA 17101

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Published

2023-01-15
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1.
Parvathaneni M, Awol AK, Kumari M, Lan K, Lingam M. Application of Artificial Intelligence and Machine Learning in Drug Discovery and Development. J. Drug Delivery Ther. [Internet]. 2023 Jan. 15 [cited 2025 Oct. 29];13(1):151-8. Available from: https://www.jddtonline.info/index.php/jddt/article/view/5867

Issue

Vol. 13 No. 1 (2023): Volume 13, Issue 1, January 2023

Section

Review

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How to Cite

1.
Parvathaneni M, Awol AK, Kumari M, Lan K, Lingam M. Application of Artificial Intelligence and Machine Learning in Drug Discovery and Development. J. Drug Delivery Ther. [Internet]. 2023 Jan. 15 [cited 2025 Oct. 29];13(1):151-8. Available from: https://www.jddtonline.info/index.php/jddt/article/view/5867
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