کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8513622 1556497 2018 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modeling and Prediction of Drug Dispersability in Polyvinylpyrrolidone-Vinyl Acetate Copolymer Using a Molecular Descriptor
ترجمه فارسی عنوان
مدل سازی و پیش بینی پراکندگی قابلیت مصرف دارو در پلی وینیل پریرولیدون و وینیل استات کپلیمر با استفاده از یک توصیف مولکولی
موضوعات مرتبط
علوم پزشکی و سلامت داروسازی، سم شناسی و علوم دارویی اکتشاف دارویی
چکیده انگلیسی
The expansion of a novel in silico model for the prediction of the dispersability of 18 model compounds with polyvinylpyrrolidone-vinyl acetate copolymer is described. The molecular descriptor R3m (atomic mass weighted 3rd-order autocorrelation index) is shown to be predictive of the formation of amorphous solid dispersions at 2 drug loadings (15% and 75% w/w) using 2 preparation methods (melt quenching and solvent evaporation using a rotary evaporator). Cosolidified samples were characterized using a suite of analytical techniques, which included differential scanning calorimetry, powder X-ray diffraction, pair distribution function analysis, polarized light microscopy, and hot stage microscopy. Logistic regression was applied, where appropriate, to model the success and failure of compound dispersability in polyvinylpyrrolidone-vinyl acetate copolymer. R3m had combined prediction accuracy greater than 90% for tested samples. The usefulness of this descriptor appears to be associated with the presence of heavy atoms in the molecular structure of the active pharmaceutical ingredient, and their location with respect to the geometric center of the molecule. Given the higher electronegativity and atomic volume of these types of atoms, it is hypothesized that they may impact the molecular mobility of the active pharmaceutical ingredient, or increase the likelihood of forming nonbonding interactions with the carrier polymer.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Pharmaceutical Sciences - Volume 107, Issue 1, January 2018, Pages 334-343
نویسندگان
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