Spectroscopic data analysis, software

Samples of each polymer were equilibrated at different relative humidities by storage over saturated salt solutions in desiccators. The equilibrated samples were then examined using FT Raman spectroscopy and differential scanning calorimetry (DSC). Gravimetry was used to assess the water vapor sorption profile. Chemometric analysis of spectroscopic data was performed using a commercial software package. Unscrambler (Camo.). 

A Variable Angle Spectroscopic EUipsometer of the type M200-F (J.A. Woollam Co. Inc., Lincoln, USA) with a spectral range from 245 to 995 nm was used to determine the thickness of the adsorbed polymer layers. Measurements were performed in ambient at three different angles (65, 70, and 75° with respect to the surface normal). For each polymer adlayer, i.e. Sil-PEG (from toluene), Sil-PEG (from acidic aqueous solution), and PLL-g-PEG (from aqueous HEPES buffer), five samples were prepared to obtain statistical data. The measurements were fitted with multilayer models using WVASE32 analysis software. The analysis of optical constants was based on a bulk silicon/ SiOj, layer, fitted in accordance with the Jellison model. After adsorption of the molecules, the adlayer thickness was determined using a Cauchy model A = 1.45, B = 0.01, C = 0). 

Most operations of the instrument are under computer control. The spectrum is recorded as a series of data points, along a linear axis of magnetic field. The signal-to-noise ratio can be improved by repetitive scanning and signal averaging. Fourier transform techniques are normally only used for analysis of pulsed EPR experiments. There is a range of different software for analysis of the spectroscopic data, in particular for simulation. 

The number of facilities capable of performing in vivo 19F MR spectroscopy is limited, in part due to the substantial hardware and software requirements associated with data acquisition and analysis. Because there is no reimbursement for MR spectroscopic examinations in the United States [54, 55], the number of clinical applications will continue to lag behind development of structural MR imaging. 

Fortunately, instrument manufacturers have been quick to attempt to satisfy both of these needs. The challenge now to the pharmaceutical scientist is the organization of the many data sets into presentation quality so that scientists and managers can make correct decisions quickly. Software has been developed to speed the collation, analysis, and presentation of the many spectroscopic characterization techniques necessary. Detection limits for mass spectrometers are now approaching the zeptomole level, and NMR spectrometers have recently seen dramatic increases in the sensitivity down... 

In contrast to the well-known difficulties of traditionally applied quantitative IR spectroscopy of mixtures in solid (powdered) samples, the near-infrared reflectance analysis (NIRA) technique [32] has gained importance over the last decade and can now be implemented on a variety of commercially available Instruments In a number of applications to Industrial, agricultural and pharmaceutical analyses. Both the NIRA instruments equipped with grating monochromators and those fitted with filter systems feature built—In microprocessors with software suited to the Intrinsic characteristics of this spectroscopic alternative. Filter Instruments generate raw optical data for only a few wave-... 

Spectroscopic methods can provide fast, non-destructive analytical measurements that can replace conventional analytical methods in many cases. The non-destructive nature of optical measurements makes them very attractive for stability testing. In the future, spectroscopic methods will be increasingly used for pharmaceutical stability analysis. This chapter will focus on quantitative analysis of pharmaceutical products. The second section of the chapter will provide an overview of basic vibrational spectroscopy and modern spectroscopic technology. The third section of this chapter is an introduction to multivariate analysis (MVA) and chemometrics. MVA is essential for the quantitative analysis of NIR and in many cases Raman spectral data. Growth in MVA has been aided by the availability of high quality software and powerful personal computers. Section 11.4 is a review of the qualification of NIR and Raman spectrometers. The criteria for NIR and Raman equipment qualification are described in USP chapters <1119> and < 1120>. The relevant highlights of the new USP chapter on analytical instrument qualification <1058> are also covered. Section 11.5 is a discussion of method validation for quantitative analytical methods based on multivariate statistics. Based on the USP chapter for NIR <1119>, the discussion of method validation for chemometric-based methods is also appropriate for Raman spectroscopy. The criteria for these MVA-based methods are the same as traditional analytical methods accuracy, precision, linearity, specificity, and robustness however, the ways they are described and evaluated can be different. 

---