Systems biology

Ayurveda, with its emphasis on Prakriti (individual constitution), Tridosha (functional principles), Rasayana (rejuvenation), and lifestyle-based prevention, provides a time-tested framework for personalised and preventive healthcare. In parallel, New Biology, empowered by high-throughput omics technologies, epigenetics, systems biology and network pharmacology offer novel tools to decode biological complexity at multiple scales. This article examines how emerging research in new biology and Ayurveda, is integrating empirical traditions with molecular science by translating traditional views into quantifiable biological correlates. The promise of network pharmacology to reveal the synergistic mechanisms of polyherbal formulations, multi-omics techniques to examine Prakriti and systems modelling to predict health and disease dynamics are discussed. Together, Ayurveda and New Biology form the basis for predictive, preventive and personalised medicine. This approach suggests a scientifically coherent and sustainable model that advances Ayurveda into a data-driven, evidence-based discipline, bridging traditional principles with precision medicine.

Background: Genomics has ushered in a new era of predictive, preventive and personalized medicine. Ayurveda and similar medical systems evolved on traditional scientific principles has long emphasized a personalized approach to health and disease management. Integrating the principles of Ayurveda with advances in genomics, as Ayurgenomics holds the potential to bridge this gap and enhance personalized healthcare. Methods: Online databases: Medline, Pubmed, Embase, AMED, CAMbase and Google Scholar were searched with key words ‘Prakriti’, ‘genomics’, ‘Ayurgenomics’, ‘epigenetics’, ‘Ayurveda’, ‘precision medicine’, ‘personalized medicine’, ‘integrated medicine’ and ‘review’ separately and in combination using appropriate Boolean operators AND and OR. Results: Original research articles selected based on keywords were screened for relevancy, redundancy, English language, full text and repetitions. There was a growing trend in incorporating newer molecular techniques in identifying Prakriti in publications. All relevant clinical trials were included. Findings indicate distinct genetic signatures associated with Prakriti. Certain SNPs including those in gene related to immunity, metabolism and inflammatory regulation have been associated with specific Prakriti types. Collectively, these findings substantiate the hypothesis that Prakriti has a genetic basis reflecting both innate constitution and disease susceptibility. Conclusions: Genomic studies on Prakriti provide a scientific foundation for Ayurveda’s personalized approach to health and disease. Establishing robust correlation between genes and Prakriti could transform healthcare by enabling tailored preventive and therapeutic strategies. Larger multi ethnic studies employing advanced omics tools are required to strengthen evidence and enhance the integration of Prakriti based frameworks with modern precision medicine.