Harnessing Artificial Intelligence for the Discovery and Development of Natural Product-Based Therapeutics

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Gideon Okibe
Humphrey Sam Samuel

Abstract

The incorporation of advanced technologies in the exploration and advancement of therapeutics derived from natural products signifies a groundbreaking phase in research. While traditional approaches to drug discovery have their merits, they often encounter issues related to time and cost-effectiveness. AI's utilization of machine learning (ML) learning (DL) and data analysis has revolutionized the process of discovering, refining, and creating therapeutics. This article explores the efforts between AI and natural product studies emphasizing progressions and uses in developing antibiotics and anticancer medications, delving into the techniques, real-life examples, and future paths of AI-guided drug discovery from sources. Ranging from forecasting bioactivity and protein targets to tuning drug characteristics AI has displayed potential in accelerating the pace and accuracy of pharmaceutical innovations. Despite obstacles, the fusion of AI with natural product investigations holds promise for unveiling treatments that can significantly enhance well-being.

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How to Cite
Okibe, G., & Samuel, H. S. (2024). Harnessing Artificial Intelligence for the Discovery and Development of Natural Product-Based Therapeutics. Faculty of Natural and Applied Sciences Journal of Scientific Innovations, 6(1), 45–57. Retrieved from https://www.fnasjournals.com/index.php/FNAS-JSI/article/view/556
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Articles