Control analysis of a pharmaceutical preparation by near-infrared reflectance spectroscopy

Blanco, M.; Coello, J.; Iturriaga, H.; Maspoch, S.; Pezuela, C. de la; Russo, Eleonora

doi:10.1016/0003-2670(94)00275-4

Cited by 37 publications

(20 citation statements)

References 11 publications

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“…ror from spinning cup to probe using 180 samples for C and N of approximately 35 to 38% was similar to that reported by Blanco et al for pharmaceuticals (20 to 37%) when comparing spinning cup and probe derived calibrations. 17 Finally, while the removal of the concentration outliers was of benefit and improved the calibrations, the question arises as to why the samples in question were so labelled. The assay values used for calibration were the same for probe-derived and spinning cup derived spectra, and as the results in Table 4 show, the results for the spinning cup were better for organic C, total N and pH even without removing any samples.…”

Section: Fibre-optic Probe Versus Spinning Cupmentioning

confidence: 99%

Quantitative Analysis of Agricultural Soils Using near Infrared Reflectance Spectroscopy and a Fibre-Optic Probe

Reeves¹,

McCarty²

2001

Journal of Near Infrared Spectroscopy

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The objective of this work was to investigate the usefulness of near infrared (NIR) reflectance spectroscopy in conjunction with a fibre-optic probe for determining various constituents (total N, organic C, active N, biomass and mineralisable N and pH) in agricultural soils. A NIRSystems model 6500 spectrometer equipped with a fibre-optic reflectance probe was used to scan soil samples (n = 180) obtained from experimental plots at two locations with three replicate plots under plow and no till practices at each location with three rates of NH 4 NO 3 for each plot (2 × 3 × 2 × 3 = 36). For each of these, samples were taken from five depths for a total of 2 × 3 × 2 × 3 × 5 or 180 samples. Optimal calibrations were achieved using first derivative spectra, and only data from 1100 to 2300 nm, with every 20 data points averaged from 1900 to 2300 nm. Compared to results achieved using a spinning cup, the use of the probe resulted in more concentration outliers (up to 6% with probe and none with the spinning cup), the reason for which is unknown. Otherwise, the final calibration results were quite similar to those achieved using a spinning cup to obtain spectra, with calibration (outliers removed) R 2 and RMSD/Mean of 0.96, 6.6; 0.95, 6.5; 0.88, 15.3; and 0.80, 19.3; for organic C, total N, active N and biomass N, respectively. The R 2 and RMSD for pH were 0.80 and 4.5 pH units, respectively. In summary, the work presented here demonstrated that NIR spectroscopy, based on data obtained using a fibre-optic probe, can be successfully used to determine compositional parameters of agricultural soils (particularly organic C and total N). However, there appeared to be a greater problem with outliers when using a fibre-optic probe than was true when obtaining spectra using a spinning cup.

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Section: Fibre-optic Probe Versus Spinning Cupmentioning

confidence: 99%

Quantitative Analysis of Agricultural Soils Using near Infrared Reflectance Spectroscopy and a Fibre-Optic Probe

Reeves¹,

McCarty²

2001

Journal of Near Infrared Spectroscopy

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“…Identifi cation involves the confi rmation of a certain chemical entity from its spectrum by matching against the components of a spectral library using an appropriate measure of similarity such as the correlation coeffi cient, 9,26 also known as the spectral match value (SMV). SMV is the cosine of the angle formed by the vectors of the spectrum for the sample and the average spectrum for each product included in the library.…”

Section: Identifi Cation and Q Ualifi Cationmentioning

confidence: 99%

NIR spectroscopy in Pharmaceutical Analysis: Off‐line and At‐line PAT Applications

Romía

Bernàrdez

2010

Process Analytical Technology

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“…Furthermore, there may be variances caused by the sensor/ probe in sample distance, 18 sensor/probe fouling, 19 illumination and detection area, 20 sample size 21 and sensor-spectrometer combinations. [22][23][24] Although these effects are known for single-point measurements using a single fibre optic, there are very few published studies in which a multipoint diffuse reflectance NIR with fibre optic sensor/probe has been used for online measurements. 12,14 Therefore, it is important to determine basic requirements to assist in choosing a proper sensor/probe in a multipoint system capable of recording an accurate NIR spectrum of a sample in motion for chemical identification, and also quantitatively by building suitable calibration models.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Diffuse Reflectance near Infrared Fibre Optical Sensors in Measurements for Chemical Identification and Quantification for Binary Granule Blends

Togashi¹,

Alvarez‐Jubete²,

Rifai³

et al. 2015

Journal of Near Infrared Spectroscopy

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In recent years, the pharmaceutical industry has focused on a better understanding of the real-time manufacturing process with online measurements. Near infrared (NIR) spectroscopy is perhaps the most used and acceptable technique in such a highly regulated industry. However, one of the big challenges in using NIR systems for in-line manufacturing processes is the acquisition of measurements in real-time simultaneously at different locations. To this end, a series of different optical setups were investigated. Results are presented here using a multipoint NIR system based on a Fabry-Pérot Interferometer capable of recording simultaneously four independent spectra in four different points. NIR spectra of cellulose and sucrose granule mixtures were evaluated by the partial leastsquares (PLS) regression method. By interpreting score values, loading of the principal components and the root mean square errors of cross-validation (RMSECV), differences between two sensors composed of fibre optics and the effect of sampling (static or motion) were analysed. Sensors that allow large illumination and detection areas against small granule sizes showed better results in reducing the prediction errors (RMSECV = 1.8%) than sensors with small illumination and detection areas against samples with large granule sizes (RMSECV = 9.6%). These results are important to better understand errors associated with optic fibre probes and their configuration in multipoint NIR spectroscopy for monitoring the pharmaceutical manufacturing process.

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Control analysis of a pharmaceutical preparation by near-infrared reflectance spectroscopy

Cited by 37 publications

References 11 publications

Quantitative Analysis of Agricultural Soils Using near Infrared Reflectance Spectroscopy and a Fibre-Optic Probe

Quantitative Analysis of Agricultural Soils Using near Infrared Reflectance Spectroscopy and a Fibre-Optic Probe

NIR spectroscopy in Pharmaceutical Analysis: Off‐line and At‐line PAT Applications

Evaluation of Diffuse Reflectance near Infrared Fibre Optical Sensors in Measurements for Chemical Identification and Quantification for Binary Granule Blends

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