Romanian Society of Pharmaceutical Sciences

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1H – NMR SPECTROSCOPY AND MULTIVARIATE ANALYSIS APPLICATION ON IDENTIFYING SYNTHETIC DRUGS IN ADULTERATED PAIN RELIEVER HERBAL MEDICINE

DHARMASTUTI CAHYA FATMARAHMI 1, RATNA ASMAH SUSIDARTI 2, RESPATI TRI SWASONO 3, ABDUL ROHMAN 2,4*

1Doctoral Program in Pharmaceutical Sciences, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara, Yogyakarta, 55281, Indonesia 2Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara, Yogyakarta, 55281, Indonesia 3Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia
4Institute of Halal Industry and System (IHIS), Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia

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The increasing number of adulteration traditional herbal medicine reports followed the growing consumption of traditional herbal medicine. This phenomenon needs quality control to prevent consumer take adulterated herbal medicine. Spectroscopy proton NMR has advantages over other analytical techniques to analyse synthetic drugs contaminant in herbal medicine products. The samples are three pain reliever herbal products, diclofenac sodium, metamizole, prednisone, and binary mixture samples. All samples were measured by 1H - NMR Spectroscopy and further analysed by PCA and OPLS - DA. PCA did not show a good result in clustering pure pain reliever herbal medicine and adulterated medicine. The value of R2X and Q2, respectively are 0.84 and 0.559. OPLS - DA proves a powerful method to distinguish the samples. The model built presented a good fit and good predictivity. The value of R2X, R2Y, and Q2, sequentially are 0.916, 0.846, 0.534. The metabolite fingerprinting performed by 1H - NMR coupled with multivariate analysis mainly OPLS - DA carried out a good result to discriminate pure and adulterated pain reliever herbal medicine with synthetic drugs. The prospect of this study is this development method could be applied for the improvement of traditional herbal medicine quality control.