AI in ethnopharmacology, the pharmaceutical industry, and its applications

Traditional knowledge from medicinal plants receives substantial analysis through the field of ethnopharmacology in its role for drug discovery. AI technology now enhances ethnopharmacology practices through its sophisticated applications in data mining analysis combined with molecular docking systems and bioactivity prediction modeling and clinical validation processes. A review provides insights into how contemporary medicine uses artificial intelligence through machine learning, deep learning, and natural language processing to upgrade drug research while also strengthening pharmacovigilance. Advanced algorithms built around artificial intelligence analyze immense ethnobotanical records to produce predictions about biological agents along with herbal mixtures evaluation while improving quality measures in traditional medicine practices. The implementation of AI technologies allows scientists to conduct omics-based research, including genomic research and metabolic and proteomic studies, to identify pharmaceutical compounds from medicinal plants. AI plays a dual role in sustainability by supporting biodiversity conservation and respecting ethical boundaries when protecting traditional knowledge as per the study findings. The incorporation of AI technology into ethnopharmacology shows promising potential for developing evidence-based herbal medicine even though standardization and validation tasks and regulatory frameworks require improvement. Modern pharmaceutical sciences will benefit from AI-powered databases, automated clinical trials, and AI-driven drug repurposing structures to unite traditional knowledge with contemporary pharmaceutical sciences.