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RAACFDb: Rheumatoid arthritis ayurvedic classical formulations database
Published in Elsevier BV
PMID: 27329782
Volume: 197
Pages: 87 - 91
Ethnopharmacological relevance In the past years, the treatment of rheumatoid arthritis (RA) has undergone remarkable changes in all therapeutic modes. The present newfangled care in clinical research is to determine and to pick a new track for better treatment options for RA. Recent ethnopharmacological investigations revealed that traditional herbal remedies are the most preferred modality of complementary and alternative medicine (CAM). However, several ayurvedic modes of treatments and formulations for RA are not much studied and documented from Indian traditional system of medicine. Therefore, this directed us to develop an integrated database, RAACFDb (acronym: Rheumatoid Arthritis Ayurvedic Classical Formulations Database) by consolidating data from the repository of Vedic Samhita – The Ayurveda to retrieve the available formulations information easily. Materials and methods Literature data was gathered using several search engines and from ayurvedic practitioners for loading information in the database. In order to represent the collected information about classical ayurvedic formulations, an integrated database is constructed and implemented on a MySQL and PHP back-end. Results The database is supported by describing all the ayurvedic classical formulations for the treatment rheumatoid arthritis. It includes composition, usage, plant parts used, active ingredients present in the composition and their structures. Conclusion The prime objective is to locate ayurvedic formulations proven to be quite successful and highly effective among the patients with reduced side effects. The database (freely available at www.beta.vit.ac.in/raacfdb/index.html) hopefully enables easy access for clinical researchers and students to discover novel leads with reduced side effects. © 2016 Elsevier Ireland Ltd
About the journal
JournalData powered by TypesetJournal of Ethnopharmacology
PublisherData powered by TypesetElsevier BV
Open AccessNo
Authors (4)