THE ROLE OF ARTIFICIAL INTELLIGENCE IN HERBAL MEDICINE FORMULATIONS: A REVIEW

This review examines the increasing influence of artificial intelligence (AI) on ensuring and improving the quality of herbal medicine. It discusses how machine learning, deep learning, and other AI-based techniques are being utilized to improve the identification of medicinal herbs, standardize quality, optimize formulations, and predict interactions between drugs and herbs. These technologies are crucial in addressing ongoing challenges in herbal medicine, including inconsistent quality, adulteration, and a lack of scientific validation. Recent AI advancements include standardizing herbal products, improving treatment recommendations for conditions like hypertension, and supporting the development of formulations that comply with Good Manufacturing Practice (GMP). AI systems also enable personalized treatment by analysing complex relationships between symptoms and herbal components. However, obstacles remain. Major limitations include the scarcity of high-quality, well-maintained datasets, the structural complexity of herbal compounds, high computational requirements, and concerns regarding data privacy and ethics. Furthermore, the "black box" nature of many AI models can make their decision-making processes opaque and difficult to trust. Despite these challenges, AI presents promising opportunities to enhance the safety, reliability, and effectiveness of herbal medicines by integrating traditional knowledge with modern, data-driven approaches. Achieving its full potential will require increased transparency in AI algorithms, improved data quality, robust ethical safeguards, and collaboration among technology specialists, scientists, and practitioners of traditional medicine.