The Transformative Impact of Artificial Intelligence on Drug Discovery: A Technical Review
DOI:
https://doi.org/10.32628/CSEIT251112284Keywords:
Artificial Intelligence in Drug Discovery, Clinical Trial Optimization, Drug Development Automation, Pharmaceutical Research Innovation, Machine Learning ValidationAbstract
This comprehensive article examines the transformative impact of artificial intelligence on drug discovery and development processes. The article explores traditional challenges in pharmaceutical development, including extended timelines, high costs, and low success rates, which have prompted the industry's shift toward AI-driven solutions. The article investigates how AI applications have revolutionized early research stages, clinical trial management, and validation processes. Through a detailed examination of recent implementations, the article demonstrates AI's significant improvements in target identification, molecular screening, and clinical trial optimization. The article also addresses technical considerations, including data quality requirements, algorithm development challenges, and resource implications for successful AI integration in pharmaceutical research. This article provides insights into emerging trends and future directions while highlighting AI's achievements and limitations in drug discovery.
Downloads
References
Ashfaq Ur Rehman et al., "Role of Artificial Intelligence in Revolutionizing Drug Discovery," Fundamental Research, 9 May 2024. Available: https://www.sciencedirect.com/science/article/pii/S266732582400205X
Kampanart Huanbutta et al., "Artificial intelligence-driven pharmaceutical industry: A paradigm shift in drug discovery, formulation development, manufacturing, quality control, and post-market surveillance," European Journal of Pharmaceutical Sciences, Volume 203, 1 December 2024, 106938. Available: https://www.sciencedirect.com/science/article/pii/S0928098724002513#:~:text=AI%20can%20redefine%20personalized%20medicine,outcomes%20and%20minimizing%20adverse%20reactions
Steven Simoens, Isabelle Huys, "R&D Costs of New Medicines: A Landscape Analysis," Front Med (Lausanne), 2021 Oct 26:8:760762. Available: https://pubmed.ncbi.nlm.nih.gov/34765624/
Michael S. Ringel et al., "Breaking Eroom's Law," Nature, 27 April 2020. Available: https://www.nature.com/articles/d41573-020-00059-3
Debleena Paul et al., "Artificial intelligence in drug discovery and development," Drug Discov Today. 2020 Oct 21;26(1):80–93. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC7577280/#:~:text=AI%20can%20be%20used%20effectively,and%20uncertainty%20of%20the%20data
Stefan Harrer et al., "Artificial Intelligence for Clinical Trial Design," Trends in Pharmacological Sciences, Volume 40, Issue 8, August 2019, Pages 577-591. Available: https://www.sciencedirect.com/science/article/pii/S0165614719301300
Madura KP Jayatunga et al., "How successful are AI-discovered drugs in clinical trials? A first analysis and emerging lessons," Drug Discovery Today, Volume 29, Issue 6, June 2024, 104009. Available: https://www.sciencedirect.com/science/article/pii/S135964462400134X#:~:text=Our%20analysis%20suggests%20that%2C%20in,success%20rates%20than%20historic%20averages
Matthew Hutson, "How AI is being used to accelerate clinical trials," Nature, 13 March 2024. Available: https://www.nature.com/articles/d41586-024-00753-x
Alexandre Blanco-González et al., "The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies," Pharmaceuticals (Basel). 2023 Jun 18;16(6):891. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC10302890/
Lalitkumar K Vora et al., "Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design," Pharmaceutics. 2023 Jul 10;15(7):1916. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC10385763/
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Journal of Scientific Research in Computer Science, Engineering and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.