Revolutionizing Ayurvedic Herbology, Drug Discovery and Drug Development Supported by Artificial Intelligence

Abstract

Aim/Objective: In this review an attempt is made to evaluate the advantages and limitations of Artificial Intelligence in Ayurvedic Herbology and Drug Discovery and Development. Material and Methods: A comprehensive literature search was conducted to identify relevant studies and articles on the integration of AI and Ayurveda. The search included databases such as PubMed, Google Scholar, and relevant journals. The collected data was analyzed to present a comprehensive overview of the topic. Discussion: AI integration into Ayurvedic pharmacology can advance predictive modelling of drug effects and support personalized treatment plans. In pharmaceuticals, AI can optimize formulations and improve quality control. In pharmacognosy, AI aids in accurate plant identification and phytochemical analysis. AI-driven drug discovery can identify new compounds and synergistic effects in polyherbal formulations. Additionally, AI can ensure drug authenticity through block chain and spectral analysis, enhancing the purity and safety of Ayurvedic products. Conclusion: AI has the potential to revolutionize the Dravya sector in Ayurveda by improving accuracy, efficiency, and personalization. This integration marks a significant advancement towards a technologically sophisticated approach to traditional medicine, promising better patient outcomes and broader acceptance of Ayurveda globally.