DOI: https://doi.org/10.63345/ijrmp.v12.i8.4
Siddharth Nayak
Independent Researcher
Odisha, India
Abstract
The convergence of artificial intelligence (AI) and precision medicine heralds a transformative era in drug development. This manuscript explores the integration of AI techniques into precision medicine strategies, outlining its impact on the discovery, development, and clinical validation of novel therapeutic agents. Emphasis is placed on machine learning, deep learning, and data mining methodologies that contribute to the personalization of drug regimens, thereby enhancing efficacy and reducing adverse effects. Through a comprehensive literature review, analysis of statistical data, and an in-depth discussion of current methodologies, this work highlights both the promising advancements and the challenges that lie ahead in the integration of AI within drug development pipelines. The results indicate that AI-driven strategies not only accelerate drug discovery processes but also significantly improve the accuracy of predictive models, ultimately fostering a more individualized approach to healthcare.
Keywords
Artificial Intelligence; Precision Medicine; Drug Development; Machine Learning; Deep Learning; Data Mining
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