ARTIFICIAL INTELLIGENCE-DRIVEN PHYTOCHEMICAL DISCOVERY AND GENOMIC TARGET IDENTIFICATION FOR PRECISION AYURVEDIC DRUG DEVELOPMENT

Abstract

Ayurvedic drug development is increasingly positioned at the intersection of traditional knowledge, phytochemical science, and precision medicine, yet its progress is constrained by complex formulations, variable botanical composition, limited target validation, and fragmented molecular evidence. This review examines how artificial intelligence can accelerate phytochemical discovery, identify genomic targets, and support individualized Ayurvedic therapeutics. Relevant literature on machine learning, deep learning, cheminformatics, molecular docking, network pharmacology, pharmacogenomics, multi-omics, and Prakriti-based stratification was critically synthesized. Current evidence indicates that AI can improve compound annotation, dereplication, bioactivity prediction, drug-likeness assessment, toxicity screening, and lead prioritization while reducing the experimental search space. Network pharmacology and systems biology provide appropriate frameworks for modelling the multi-component, multi-target, and multi-pathway actions of Ayurvedic formulations. Genomic, transcriptomic, proteomic, metabolomic, and epigenomic integration can strengthen target discovery, biomarker identification, mechanistic validation, and responder stratification. Prakriti-informed pharmacogenomics may enhance treatment selection and dosing when constitution-based phenotypes are linked to reproducible molecular signatures. Translation remains limited by inconsistent botanical standardization, heterogeneous datasets, algorithmic opacity, inadequate external validation, population bias, and uncertain regulatory pathways. Progress requires curated interoperable databases, explainable models, laboratory confirmation, prospective clinical trials, pharmacovigilance, and protection of traditional knowledge. Integrating AI with validated Ayurvedic principles can establish a more rigorous, scalable, and clinically credible pathway toward safe, standardized, and personalized phytotherapeutic development across diverse populations and healthcare settings globally.