Literature DB >> 10205599

Qualitative determination of polyvinylpyrrolidone type by near-infrared spectrometry.

K Kreft1, B Kozamernik, U Urleb.   

Abstract

Soluble polyvinylpyrrolidones are very useful and versatile pharmaceutical auxiliaries. The different types of povidone are characterised by their viscosity measured in water, expressed as a K-value. We have developed a rapid, accurate, reliable, and non-destructive near infrared (NIR) spectroscopy method for the determination of PVP type and consequently identification thereof. We have implemented chemometrics onto NIR spectra collected in diffuse reflectance mode using fibre optics to build a qualitative model that enables us to obtain useful analytical information. A principal component analysis and a modelling technique soft independent modelling of class analogy (SIMCA) were applied. An approach to validate the method was developed.

Entities:  

Mesh:

Substances:

Year:  1999        PMID: 10205599     DOI: 10.1016/s0378-5173(98)00265-8

Source DB:  PubMed          Journal:  Int J Pharm        ISSN: 0378-5173            Impact factor:   5.875


  4 in total

1.  Characterization of povidone products by means of 13C-NMR, MALDI-TOF, and electrospray mass spectrometry.

Authors:  Klaus Raith; Andrea V Kühn; Fred Rosche; Raik Wolf; Reinhard H H Neubert
Journal:  Pharm Res       Date:  2002-04       Impact factor: 4.200

2.  Application of NIR spectroscopy for the quality control of mangosteen pericarp powder: quantitative analysis of alpha-mangostin in mangosteen pericarp powder and capsule.

Authors:  Jomjai Peerapattana; Kuniko Otsuka; Makoto Otsuka
Journal:  J Nat Med       Date:  2012-08-25       Impact factor: 2.343

Review 3.  Pharmaceutical assessment of polyvinylpyrrolidone (PVP): As excipient from conventional to controlled delivery systems with a spotlight on COVID-19 inhibition.

Authors:  Mallesh Kurakula; G S N Koteswara Rao
Journal:  J Drug Deliv Sci Technol       Date:  2020-09-02       Impact factor: 3.981

4.  Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine.

Authors:  Lan Sun; Chang Hsiung; Christopher G Pederson; Peng Zou; Valton Smith; Marc von Gunten; Nada A O'Brien
Journal:  Appl Spectrosc       Date:  2016-03-30       Impact factor: 2.388

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.