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Applications of AI in Computer-Aided Drug Discovery
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Author(s): Reet Kaur Kohli (Amity University, Noida, India), Seneha Santoshi (Amity University, Noida, India), Sunishtha S. Yadav (Amity University, Noida, India)and Vandana Chauhan (Amity University, Noida, India)
Copyright: 2023
Pages: 13
Source title:
Applying AI-Based IoT Systems to Simulation-Based Information Retrieval
Source Author(s)/Editor(s): Bhatia Madhulika (Amity University, India), Bhatia Surabhi (King Faisal University, Saudi Arabia), Poonam Tanwar (Manav Rachna International Institute of Research and Studies, India)and Kuljeet Kaur (Université du Québec, Canada)
DOI: 10.4018/978-1-6684-5255-4.ch005
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Abstract
Drug discovery is the process in which healthcare is approached through identification of potential new therapeutic agents. CADD provides solutions at every stage of drug discovery including the leading challenges of cost and time. CADD has provided an effective solution to this challenge. AI has enabled multiple aspects of drug discovery, including the analysis of high content screening data and the design and synthesis of new molecules. The use of transparent methodologies like AI is crucial, particularly in drug repositioning/repurposing in rare diseases. An abundant variety of methods, in particular the concepts of deep learning, have been used for protein modelling and ligand-based drug discovery along with artificial neural networks for QSAR modelling. Structure-based ligand identification via AI modelling is also explored. AI presents the scientific community and the biopharma industry and its established processes for discovering and developing new medicines with new challenges.
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