Editorial | Volume 13, Supplement 1, September, 2023

Applications of Artificial Intelligence in Drug Design, Discovery and Development

Kalirajan Rajagopal   

Kalirajan Rajagopal

Department of Pharmaceutical Chemistry, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Ooty – 643001, The Nilgiris, Tamilnadu, India.

Open Access   

Published:  Sep 20, 2023

DOI: 10.7324/JAPS.2023.9.1ed
PDF [ 0.3 MB]
Request Permission
Share
Download Citation
Print
Download PDF
Abstract

There is no abstract in this article.


Keyword:     Artificial Intelligence Drug Design Computer-aided drug design drug discovery

Citation:

Rajagopal K. Applications of Artificial Intelligence in Drug Design, Discovery and Development. J App Pharm Sci, 2023; 13 (Suppl 1): i-ii. http://doi.org/10.7324/JAPS.2023.9.1ed

Copyright: © The Author(s). This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
HTML Full Text

Reference

Harrer S. Artificial intelligence for clinical trial design. Trends in Pharmacological Sciences, 2019; 40:577–591. http://doi.org/10.1016/j.tips.2019.05.005

Jane Wakefield, Artificial intelligence-created medicine to be used on humans for first time. https://www.bbc.com/news/technology-51315462, 30, Jan, 2020.

Lamberti M.J. A study on the application and use of artificial intelligence to support drug development. Clinical Therapeutics.2019;41:14141426. http://doi.org/10.1016/j.clinthera.2019.05.018

Miles J., Walker A. The potential application of artificial intelligence in transport. IEE Proceedings-Intelligent Transport Systems, 2006;153:183–198

Paul D, Sanap G, Shenoy S, Kalyane D, Kalia K, Tekade RK. Artificial intelligence in drug discovery and development. Drug Discovery Today. 2021; 26(1): 80-93. http://doi.org/10.1016/j.drudis.2020.10.010.

Pu L. eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates. BMC Pharmacology and Toxicology, 2019;20:2. http://doi.org/10.1186/s40360-018-0282-6

Yang X. Concepts of artificial intelligence for computer-assisted drug discovery. Chemical Reviews. 2019; 119:1052010594. http://doi.org/10.1021/acs.chemrev.8b00728

Zhang L. From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug Discovery Today, 2017; 22: 1680–1685. http://doi.org/10.1016/j.drudis.2017.08.010

https://www.genengnews.com/news/insilico-gains-fdas-first-orphan-drug-designation-for-ai-candidate/, 10, Feb, 2023.

Article Metrics
63 Views 70 Downloads 133 Total

Year

Month

Related Search

By author names