THE ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN PHARMACOGNOSY: ADVANCES AND APPLICATIONS
Abstract
A new era of natural product research has been brought about by the application of computational intelligence (also known as AI) into pharmacognosy, which has greatly improved the identification, examination, and creation of therapeutic chemicals originating from natural sources. This review comprehensively examines the role of AI in modern pharmacognosy, highlighting recent advances and diverse applications. Key areas of focus include AI-driven methods for natural product identification, compound isolation, bioactivity prediction, and structure elucidation. Machine learning algorithms and neural networks are increasingly utilized to analyze complex biological data, predict pharmacological properties, and streamline the drug discovery process. Furthermore, AI technologies facilitate the optimization of extraction processes and the development of novel formulations, contributing to improved efficacy and safety profiles of natural products. Case studies illustrate successful implementations of AI in pharmacognosy, demonstrating its potential to overcome traditional challenges and accelerate research timelines. This review also highlights some biological activities predicted with the help of AI. It also discusses the ethical considerations, potential limitations, and future directions of AI applications in this field. Overall, AI stands as a transformative tool in modern pharmacognosy, offering unprecedented opportunities for advancing natural product research and development.
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