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International Journal of Inflammation
Volume 2018, Article ID 5023429, 18 pages
Review Article

Presenting a New Standard Drug Model for Turmeric and Its Prized Extract, Curcumin

Biologic Pharmamedical Research, 688-2397 King George Blvd., White Rock, BC, V4A7E9, Canada

Correspondence should be addressed to Franco Cavaleri; moc.dem-cigoloib@c.ocnarf

Received 27 September 2017; Accepted 6 December 2017; Published 15 January 2018

Academic Editor: Ke-Wu Zeng

Copyright © 2018 Franco Cavaleri. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Various parts of the turmeric plant have been used as medicinal treatment for various conditions from ulcers and arthritis to cardiovascular disease and neuroinflammation. The rhizome’s curcumin extract is the most studied active constituent, which exhibits an expansive polypharmacology with influence on many key inflammatory markers. Despite the expansive reports of curcucmin’s therapeutic value, clinical reliability and research repeatability with curcumin treatment are still poor. The pharmacology must be better understood and reliably mapped if curcumin is to be accepted and used in modern medical applications. Although the polypharmacology of this extract has been considered, in mainstream medicine, to be a drawback, a perspective change reveals a comprehensive and even synergistic shaping of the NF-kB pathway, including transactivation. Much of the inconsistent research data and unreliable clinical outcomes may be due to a lack of standardization which also pervades research standard samples. The possibility of other well-known curcumin by-products contributing in the polypharmacology is also discussed. A new flowchart of crosstalk in transduction pathways that lead to shaping of nuclear NF-kB transactivation is generated and a new calibration or standardization protocol for the extract is proposed which could lead to more consistent data extraction and improved reliability in therapy.