Near-infrared Chemical Imaging for Characterizing Pharmaceutical Dosage Forms

2016 ◽  
pp. 1513-1520
Keyword(s):  
Near Infrared ◽  
Chemical Imaging ◽  
Dosage Forms ◽  
Pharmaceutical Dosage Forms

Optimisation of Magnification Levels for near Infrared Chemical Imaging of Blending of Pharmaceutical Powders

2007 ◽  
Vol 15 (3) ◽  
pp. 137-151 ◽  
Author(s):  
Hua Ma ◽  
Carl A. Anderson
Keyword(s):  
Near Infrared ◽  
Image Data ◽  
Principal Component ◽  
Chemical Imaging ◽  
Field Of View ◽  
Pharmaceutical Dosage Forms ◽  
Component Distribution ◽  
Circular Field ◽  
Pharmaceutical Powder ◽  
Magnification Level

A critical parameter in the evaluation of pharmaceutical dosage forms by hyperspectral imaging is the level of magnification. If the magnification (as set by the optical objective) is inadequate to resolve the relevant features, then the value of the imaging is diminished; if the magnification level is greater than is required, then the field of view is unnecessarily reduced. The purpose of this study was to determine an optimum magnification level for the study of powder mixing. Relevant features in this system include distribution of individual components within samples and the overall content of a given sample. In the present study, three magnification levels of near infrared (NIR) chemical imaging objectives were evaluated for their effects on imaging a blend of pharmaceutical materials (powders). High, medium and low objective magnification levels were investigated by comparing the resulting blend surface images of a two-component (salicylic acid and lactose) pharmaceutical powder mixture. Multiple images from high and medium magnification were concatenated so that an equivalent field of view was obtained for all magnification levels. Univariate images, principal component analysis score images, partial least squares predicted images and spectra extracted from different intensity regions in the area images were analysed qualitatively and quantitatively for comparison. A series of images spanning a strip across the centre of the circular field were collected at each magnification level and compared with respect to surface features elucidated and area of blend surface imaged. Analyses of images indicate that the three magnification levels delineate the component distribution for this particular powder system similarly. Images obtained at the low magnification level demonstrated adequate resolution and provided the broadest view of the blend surface. It is concluded that the low optical magnification level was adequate for the system being studied and is the preferred mode for pharmaceutical powder blend image data collection for this system.

Near infrared transmittance analysis for the assay of solid pharmaceutical dosage forms

The Analyst ◽  
1999 ◽  
Vol 124 (5) ◽  
pp. 755-758 ◽  
Author(s):  
P. Corti ◽  
E. Dreassi ◽  
G. Ceramelli ◽  
S. Mattii
Keyword(s):  
Near Infrared ◽  
Dosage Forms ◽  
Pharmaceutical Dosage Forms ◽  
Infrared Transmittance

A Comparison of near Infrared Method Development Approaches Using a Drug Product on Different Spectrophotometers and Chemometric Software Algorithms

2009 ◽  
Vol 17 (5) ◽  
pp. 233-244 ◽  
Author(s):  
Assad Kazeminy ◽  
Saeed Hashemi ◽  
Roger L. Williams ◽  
Gary E. Ritchie ◽  
Ronald Rubinovitz ◽  
...  
Keyword(s):  
Method Development ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Dosage Forms ◽  
Multivariate Models ◽  
Data Set ◽  
Pharmaceutical Dosage Forms ◽  
Pre Treatment ◽  
Instrument Configuration

It is well known that spectral variability in near infrared (NIR) spectroscopy can be attributed to the analyst, sample, sample positioning, instrument configuration and software (in both algorithm formats and structures used as well as in the execution of data pre-treatment and analysis). It is often acknowledged that the single largest factor impacting NIR results is sample presentation. However, what is obvious but not often acknowledged is that there are instrumental and software differences as well. These differences, evident in the quality of the spectra, may impact the chemometrics that are subsequently performed and, possibly, the results obtained from the multivariate statistical models. In order to investigate just what are these sources of variability, and just how much these variations may impact the results of the multivariate models for predicting the identification of pharmaceutical dosage forms, a study has been conducted. To the authors' knowledge, no other systematic study of this kind has been published. In this study, we are interested in learning what variability, if any, the choices for instrument and software have on the development of a NIR method for the identification of pharmaceutical dosage forms. Furthermore, we would like to learn what and how do the choices made early on in the experimental design impact the final quality of the spectra and the resulting multivariate models obtained from these spectra. A study protocol was designed, using a common data set consisting of four formulations of Ibuprofen, involving three investigating parties, namely, US FDA, USP and Irvine Pharmaceutical Services and using three NIR instruments, namely (listed in alphabetical order), a Bruker spectrometer, a Büchi spectrometer and a Foss spectrometer. Based on the results and despite differences in instrument configuration [dispersive or Fourier Transform (FT)], number of spectral data points, principal components analysis (PCA) or factorisation algorithms, and validation modelling approach, exact and accurate spectroscopic results can be achieved using NIR spectroscopy for discriminate analysis. More importantly, this study shows that the same NIR method spectral range and pre-treatment parameters can be used, and that nearly the same multivariate models can be obtained, despite instrumental and software differences, to accurately predict the identity of pharmaceutical dosage forms.

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