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Artificial Intelligence and Machine Learning in Drug Discovery and Development
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Author(s): Sakshi Garg (KIET School of Pharmacy, KIET Group of Institutions, India), Kunal Arora (Sawmi Vivekanand Subharti University, India), Sumita Singh (Sawmi Vivekanand Subharti University, India)and K. Nagarajan (KIET School of Pharmacy, KIET Group of Institutions, India)
Copyright: 2024
Pages: 20
Source title:
Artificial Intelligence in the Age of Nanotechnology
Source Author(s)/Editor(s): Wassim Jaber (ESPCI Paris - PSL, France)
DOI: 10.4018/979-8-3693-0368-9.ch003
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Abstract
Over the past decade, artificial intelligence (AI) has significantly reshaped formulation development, drug discovery, and delivery processes. This study examines how AI and its technologies are enhancing efficiency and precision in pharmaceutical research. Crafting novel medications is crucial in the journey of drug development, offering the potential for enhanced bioavailability and targeted distribution. The conventional trial-and-error approach to formulation development, however, demands extensive resources and time-consuming in vitro and in vivo experiments. This article outlines the role of machine learning workflows in optimizing medication formulation processes, with a focus on structure-based and ligand-based drug design. Nanotechnology's potential for revolutionizing healthcare, including drug delivery and microscopic interventions, hinges on data science. Moreover, the exciting prospect of AI-powered nanobots holds promise for targeted drug delivery and tumor treatment with minimal patient impact.
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