Document Type
Article
Publication Date
2022
Digital Object Identifier (DOI)
https://doi.org/10.3389/fphar.2022.866827
Abstract
Originating in ancient India, Ayurveda is an alternative medicinal approach that provides substantial evidence for a theoretical-level analysis of all aspects of life. Unlike modern medicine, Ayurveda is based upon tridoshas (Vata, pitta, and Kapha) and Prakriti. On the other hand, the research of all the genes involved at the proteomics, metabolomics, and transcriptome levels are referred to as genomics. Geoclimatic regions (deshanupatini), familial characteristics (kulanupatini), and ethnicity (jatiprasakta) have all been shown to affect phenotypic variability. The combination of genomics with Ayurveda known as ayurgenomics provided new insights into tridosha that may pave the way for precision medicine (personalized medicine). Through successful coordination of “omics,” Prakriti-based treatments can help change the existing situation in health care. Prakriti refers to an individual’s behavioral trait, which is established at the moment of birth and cannot be fully altered during one’s existence. Ayurvedic methodologies are based on three Prakriti aspects: aushadhi (medication), vihara (lifestyle), and ahara (diet). A foundation of Prakriti-based medicine, preventative medicine, and improvement of life quality with longevity can be accomplished through these ayurvedic characteristics. In this perspective, we try to understand prakriti’s use in personalized medicine, and how to integrate it with programs for drug development and discovery.
Rights Information
This work is licensed under a Creative Commons Attribution 4.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Frontiers in Pharmacology, v. 13, art. 866827
Scholar Commons Citation
Huang, Zoufang; Chavda, Vivek P.; Bezbaruah, Rajashri; Uversky, Vladimir N.; Palagati, Sucharitha; Patel, Aayushi B.; and Chen, Zhe-Sheng, "An Ayurgenomics Approach: Prakriti-based Drug Discovery and Development for Personalized Care" (2022). Molecular Medicine Faculty Publications. 929.
https://digitalcommons.usf.edu/mme_facpub/929
