Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

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Leveraging Al for Drug Discovery: Techniques and Applications

Authors
Damalla Jyothi1, *, K. Anuradha2, Indigibilli Sahithi3, N. Sreekanth4, N. Srinivas5, Rakesh Reddy6
1Assistant professor, Department of Data Science, MLR Institute of Technology, Dundigal, Hyderabad, Telangana, India
2Assistant Professor, Department of Computer Science and Engineering (AI&ML), CVR College of Engineering, Hyderabad, Telangana, India
3Assistant professor, Department of Computer Science and Engineering- Internet of Things, Mallareddy Engineering College (Autonomous), Maisammaguda, Dhulapally, Medchal, Telangana, India
4Professor of ECE, Mallareddy Engineering College for Women Hyderabad, Hyderabad, Telangana, India
5Associate Professor, CSE department, Vignana Bharathi Institute of Technology Aushapur(V), Ghatkesar, Hyderabad, Telangana, India
6Assistant Professor Department of CSE Keshav Memorial Institute of Technology, Hyderabad, Telangana, India
*Corresponding author. Email: damallajyothii@gmail.com
Corresponding Author
Damalla Jyothi
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_134How to use a DOI?
Keywords
AI; Healthcare; big data; Natural language processing; Python AI applications; Machine learning; Deep learning; Alpha Go; protein folding; AI applications in drug discovery; AI in Big Pharma and biotech; drug discovery and development; drug design
Abstract

Artificial Intelligence (AI) is revolutionalising drug discovery by increasing the rate, precision and creativity in the search for potential drug leads. From the customary approaches of modelling molecular structures to the modern era of enhancement of drug-target communication, applications of artificial intelligence are changing the face of conventional methods. In this paper, we will discuss the primary AI methods that find enlightening applications in drug discovery and development which includes machine learning, deep learning, and reinforcement learning. We focus on experience in the last couple of years and perspectives for the further usage of AI for escalating the speed and effectiveness at a help inexpensive and targeted drug development.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_134How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Damalla Jyothi
AU  - K. Anuradha
AU  - Indigibilli Sahithi
AU  - N. Sreekanth
AU  - N. Srinivas
AU  - Rakesh Reddy
PY  - 2025
DA  - 2025/05/23
TI  - Leveraging Al for Drug Discovery: Techniques and Applications
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1608
EP  - 1617
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_134
DO  - 10.2991/978-94-6463-718-2_134
ID  - Jyothi2025
ER  -