S
Snezana Agatonovic-Kustrin
Researcher at I.M. Sechenov First Moscow State Medical University
Publications - 125
Citations - 3642
Snezana Agatonovic-Kustrin is an academic researcher from I.M. Sechenov First Moscow State Medical University. The author has contributed to research in topics: Molecular descriptor & DPPH. The author has an hindex of 28, co-authored 118 publications receiving 2857 citations. Previous affiliations of Snezana Agatonovic-Kustrin include Universiti Teknologi MARA & Monash University Malaysia Campus.
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Biorelevant Dissolution Studies of Pioglitazone Hcl Immediate ReleaseTablets and the Determination of an In Vitro In Vivo Correlation
TL;DR: Good correlation between in vitro drug release and in vivo drug absorption using the biorelevant dissolution test method is demonstrated and shows that food delays the onset of action of the drug significantly.
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Validation of an HPLC method for the simultaneous determination of eletriptan and UK 120.413
TL;DR: Arapid and sensitive RPHPLC method was developed for the routine control analysis of eletriptan hydrobromide and its organic impurity UK 120.413 in Relpax® tablets.
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HPTLC – Bioautographic methods for selective detection of the antioxidant and a-amylase inhibitory activity in plant extracts
TL;DR: In this article, a high-performance thin-layer chromatography (HPTLC) method was developed for quantification of a-amylase inhibitory activity and stigmasterol content in ant plant extracts.
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The Use of UV-Visible Reflectance Spectroscopy as an Objective Tool to Evaluate Pearl Quality
TL;DR: The results of this study shows that the developed UV-Vis spectroscopy-ANN method could be used as a more objective method of assessing pearl quality (grading) and may become a valuable tool for the pearl grading industry.
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Chemometric characterization of wines according to their HPTLC fingerprints
TL;DR: In this paper, the authors used HPTLC peak profiles of 40 mono-and multi-varietal commercial wine samples from four vintages between 2003 and 2012 to determine which major grape varieties are present in a given wine using both high-performance thin-layer chromatography (HPTLC) fingerprinting and multivariate analysis.