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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Prediction of drug bioavailability based on molecular structure
TL;DR: The structure–pharmacokinetic relationship developed in the current study highlighted solubility and partitioning characteristics that may be useful in designing drugs with appropriate bioavailability.
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Prediction of a stable microemulsion formulation for the oral delivery of a combination of antitubercular drugs using ANN methodology.
TL;DR: A novel microemulsion formulation capable of delivering rifampicin and isoniazid in combination was created to allow for their differences in solubility and potential for chemical reaction and the developed model allowed better understanding of the process ofmicroemulsion formation and stability within pseudoternary colloidal systems.
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Essential oils and functional herbs for healthy aging.
TL;DR: Cognitive stimulation with medical food and medical herbs could delay development of cognitive decline, and improve the quality of life of Alzheimer’s disease patients.
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Analysing the crystal purity of mebendazole raw material and its stability in a suspension formulation.
TL;DR: The quantitative results obtained for the binary crystal form mixtures clearly demonstrate the strong potential of ATR-FTIR for use in the determination of the polymorphic content not only in bulk pharmaceuticals but also in liquid formulations.
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Qualitative and quantitative high performance thin layer chromatography analysis of Calendula officinalis using high resolution plate imaging and artificial neural network data modelling
TL;DR: A novel method for quality control of herbal products, based on HPTLC separation, high resolution digital plate imaging and ANN data analysis has been developed and can be adopted for routine evaluation of the phytochemical variability in calendula plant extracts.