کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
2484566 | 1114318 | 2016 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Pharmaceutical Applications of Relaxation Filter-Selective Signal Excitation Methods for 19F Solid-State Nuclear Magnetic Resonance: Case Study With Atorvastatin in Dosage Formulation
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
داروسازی، سم شناسی و علوم دارویی
اکتشاف دارویی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
We recently developed several new relaxation filter-selective signal excitation (RFS) methods for 13CÂ solid-state nuclear magnetic resonance (NMR) that allow 13C signal extraction of the target components from pharmaceuticals. These methods were successful in not only qualification but also quantitation over the wide range of 5% to 100%. Here, we aimed to improve the sensitivity of these methods and initially applied them to 19F solid-state NMR, on the basis that the fluorine atom is one of the most sensitive NMR-active nuclei. For testing, we selected atorvastatin calcium (ATC), an antilipid BCS class II drug that inhibits 3-hydroxy-3-methylglutaryl-coenzyme A reductase and is marketed in crystalline and amorphous forms. Tablets were obtained from 2 generic drug suppliers, and the ATC content occurred mainly as an amorphous form. Using the RFS method with 19F solid-state NMR, we succeeded in qualifying trace amounts (less than 0.5% w/w level) of crystalline phase (Form I) of ATC in the tablets. RFS methods with 19F solid-state NMR are practical and time efficient and can contribute not only to the study of pharmaceutical drugs, including those with small amounts of a highly potent active ingredient within a formulated product, but also to the study of fluoropolymers in material sciences.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Pharmaceutical Sciences - Volume 105, Issue 3, March 2016, Pages 1233-1238
Journal: Journal of Pharmaceutical Sciences - Volume 105, Issue 3, March 2016, Pages 1233-1238
نویسندگان
Mamiko Nasu Asada, Takayuki Nemoto, Hisashi Mimura,