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Convergence of Data Science-AI-Green Chemistry-Affordable Medicine: Transforming Drug Discovery
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Author(s): B. Rebecca (Department of Computer Science and Engineering (Data Science), Marri Laxman Reddy Institute of Technology and Management, Hyderabad, India), K. Pradeep Mohan Kumar (Department of Computing Technologies, SRM Institute of Science and Technology, Chennai, India), S. Padmini (Department of Computing Technologies, SRM Institute of Science and Technology, Chennai, India), Bipin Kumar Srivastava (Department of Applied Sciences, Galgotias College of Engineering and Technology, India), Shubhajit Halder (Department of Chemistry, Hislop College, Nagpur, India)and Sampath Boopathi (Mechanical Engineering, Muthayammal Engineering College, India)
Copyright: 2024
Pages: 26
Source title:
Handbook of Research on AI and ML for Intelligent Machines and Systems
Source Author(s)/Editor(s): Brij B. Gupta (Asia University, Taichung, Taiwan & Lebanese American University, Beirut, Lebanon)and Francesco Colace (University of Salerno, Italy)
DOI: 10.4018/978-1-6684-9999-3.ch014
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Abstract
The drug discovery and design process has been significantly transformed by the integration of data science, artificial intelligence (AI), green chemistry principles, and affordable medicine. AI techniques enable rapid analysis of vast datasets, predicting molecular interactions, optimizing drug candidates, and identifying potential therapeutics. Green chemistry practices promote sustainability and efficiency, resulting in environmentally friendly and cost-effective production processes. The goal is to develop affordable medicines that are not only efficacious but also accessible to a wider population. This chapter explores case studies and emerging trends to highlight the transformation of the pharmaceutical industry and innovation in drug discovery.
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