AI-Driven Drug Discovery: Accelerating Pharmaceutical Research Through Machine Learning
DOI:
https://doi.org/10.48047/jrq8s909Keywords:
Artificial Intelligence (AI), Machine Learning, Drug Discovery, Pharmaceutical Research, Molecular DockingAbstract
Artificial Intelligence (AI) has emerged as a transformative force in drug discovery, offering unparalleled
potential to accelerate the pharmaceutical research pipeline. This study explores the application of AIdriven approaches across multiple facets of pharmaceutical development, from drug design to clinical
trials and personalized medicine. We present a comprehensive analysis of AI’s impact on drug discovery,
clinical trial optimization, and personalized treatment strategies, highlighting significant
improvements in prediction accuracy, patient recruitment efficiency, and treatment optimization.
Our findings demonstrate that AI-driven models can enhance the design and synthesis of novel drug
compounds, improving specificity and efficacy while reducing the time and costs associated with
preclinical development.
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