Herbal Medicine Meets Machine Learning: A Systematic Review of Ai-Powered Innovation in Chronic Inflammation Management Publisher



Shahrezaei A ; Taherkhani S ; Dashti L ; Garmaroodi GA ; Nasirinezhad F
Source: Discover Applied Sciences Published:2026

Abstract

Chronic inflammatory diseases (CIDs) impose a significant global health burden, affecting over 350 million people and incurring annual healthcare costs exceeding $500 billion. While conventional therapies offer symptomatic relief, they are often limited by adverse effects, high costs, and insufficient efficacy in preventing disease progression. Herbal medicines, rooted in traditional systems, present promising alternatives due to their multi-target anti-inflammatory, antioxidant, and immunomodulatory effects. Bioactive compounds like curcumin, resveratrol, and boswellic acids target critical inflammatory pathways such as NF-κB, MAPK, and JAK-STAT. Despite their potential, challenges like variable bioactive content, poor bioavailability, and limited large-scale clinical trials have hindered widespread adoption. While prior reviews have explored AI in traditional medicine broadly, this review uniquely addresses these limitations by integrating traditional phytotherapy with cutting-edge AI-driven innovations, offering a comprehensive synthesis focused on chronic inflammation management through multi-omics, network pharmacology, and nanotechnology applications that distinguishes it by emphasizing microbiome personalization and regulatory implications. AI optimizes herbal therapies by enhancing bioavailability up to 20-fold through nanoformulations and achieving 95% standardization accuracy for compounds like curcumin and boswellic acids. AI-driven network pharmacology and predictive modeling elucidate complex inflammatory pathways, enabling precision therapeutics with 80–90% predictive accuracy in patient stratification, improving outcomes, and reducing adverse events in conditions such as rheumatoid arthritis and inflammatory bowel disease. By leveraging AI for pharmacovigilance and herb-drug interaction predictions, and employing blockchain-enhanced standardization, this review bridges traditional phytotherapy with modern pharmacology. While advancements are significant, gaps persist in global regulatory frameworks and large-scale, multi-center RCTs. Future research should prioritize AI-integrated RCTs and real-time biomarker monitoring to position herbal therapies as a cornerstone of precision medicine by 2030. © The Author(s) 2025.