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Ayurveda in Preventive and Supportive Healthcare: Current Evidence, Safety, and Clinical Integration
Jassim Rahiman K1, Jyoti Prakash2, Laxmi Patel3
1Department of Kayachikitsa (Internal Medicine), All India Institute of Ayurveda, University of Delhi, New Delhi, IND.
Abstract:
Ayurveda represents one of the oldest structured healthcare systems and continues to gain attention within contemporary integrative medicine because of its emphasis on prevention, individualized care, lifestyle regulation, and health maintenance. Despite growing global use, its wider clinical acceptance remains limited by inconsistent evidence quality, heterogeneous formulations, variable treatment protocols, insufficient safety reporting, and challenges in aligning traditional diagnostic concepts with modern biomedical standards. This review critically examines the therapeutic relevance of Ayurveda in modern healthcare, with attention to its applications in metabolic, cardiovascular, gastrointestinal, hepatobiliary, musculoskeletal, inflammatory, mental health, respiratory, immune-related, reproductive, geriatric, and preventive care. A comprehensive narrative approach was used to synthesize evidence from clinical studies, pharmacological investigations, traditional frameworks, and integrative healthcare literature. The review indicates that specific Ayurvedic interventions, including herbal formulations, Panchakarma, Rasayana, yoga, dietary regulation, and lifestyle medicine, may offer supportive value in selected conditions through measurable outcomes such as cardiometabolic risk markers, gastrointestinal symptom scores, pain and functional indices, stress and sleep measures, respiratory symptom control, reproductive-metabolic parameters, and quality-of-life outcomes. Many claims remain insufficiently validated due to methodological weaknesses, limited standardization, and inadequate pharmacovigilance. Emerging Ayurgenomics may help bridge traditional Prakriti-based constitutional assessment with genomic profiles, molecular biomarkers, metabolic phenotypes, inflammatory signatures, and individualized risk stratification. Artificial intelligence and machine learning may further support modernization by digitizing Ayurvedic clinical records, standardizing diagnostic criteria, improving pharmacovigilance, and predicting response to polyherbal therapy. Ayurveda may contribute meaningfully to modern healthcare when applied as complementary and preventive care within regulated, evidence-based, and interdisciplinary systems. Future advancement depends on rigorous trials, validated biomarkers, quality-controlled formulations, transparent safety monitoring, and reproducible digital-clinical datasets.
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