Open Access
Спектроскопическое исследование кинетики высвобождения водонерастворимого препарата гризеофульвин из ватеритных контейнеров в водной среде
Author(s) -
М.С. Савельева,
Е.В. Ленгерт,
A. M. Abramova,
С. Н. Штыков,
Ю.И. Свенская
Publication year - 2021
Publication title -
optika i spektroskopiâ
Language(s) - English
Resource type - Journals
eISSN - 2782-6694
pISSN - 0030-4034
DOI - 10.21883/os.2021.06.50976.5k-21
Subject(s) - nanocarriers , vaterite , chemistry , aqueous solution , drug delivery , bioavailability , solvent , controlled release , solubility , drug carrier , raman spectroscopy , chemical engineering , materials science , nanotechnology , chromatography , organic chemistry , pharmacology , medicine , engineering , carbonate , aragonite , physics , optics
The bioavailability improvement of hydrophobic drugs is one of the major problems in pharmaceutical research as required for the enhancement of their therapeutic efficacy. Encapsulation of such drugs into various micro- and nanocarriers enabling the targeted delivery represents an important strategy here. The process of the designed nanoformulation study generally includes characterization of the payload release profile in model water-based media, which provides a challenge to encapsulated hydrophobic drugs due to their poor solubility in water. Thus, modification of the existed release investigation protocols is required for reliable detection of the liberated hydrophobic drug. Here, we report an optimized multimodal spectroscopic and microscopic study of the release behaviour of griseofulvin (Gf), a water-insoluble antifungal drug, from vaterite carriers. The addition of N, N-dimethylformamide (DMF), a polar aprotic solvent, to aqueous suspensions of Gf-loaded vaterite carriers at the investigated time points right before the UV-Vis spectroscopic measurement allowed us to enhance the accuracy of the released Gf determination. Monitoring of the carrier degradation process by a combination of scanning electron microscopy and Raman spectroscopy demonstrated a good correlation between the obtained data and the payload release kinetics.