PubMed · 14756176
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A Rimpler. 2003. Applications.. https://doi.org/10.1093/oxfordjournals.rpd.a006386
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The FDA process analytical technology (PAT) initiative will materialize in a significant increase in the number of installations of spectroscopic instrumentation. However, to attain the greatest benefit from the data generated, there is a need for calibration procedures that extract the maximum information content. For example, in fermentation processes, the interpretation of the resulting spectra is challenging as a consequence of the large number of wavelengths recorded, the underlying correlation structure that is evident between the wavelengths and the impact of the measurement environment. Approaches to the development of calibration models have been based on the application of partial least squares (PLS) either to the full spectral signature or to a subset of wavelengths. This paper presents a new approach to calibration modeling that combines a wavelength selection procedure, spectral window selection (SWS), where windows of wavelengths are automatically selected which are subsequently used as the basis of the calibration model. However, due to the non-uniqueness of the windows selected when the algorithm is executed repeatedly, multiple models are constructed and these are then combined using stacking thereby increasing the robustness of the final calibration model. The methodology is applied to data generated during the monitoring of broth concentrations in an industrial fermentation process from on-line near-infrared (NIR) and mid-infrared (MIR) spectrometers. It is shown that the proposed calibration modeling procedure outperforms traditional calibration procedures, as well as enabling the identification of the critical regions of the spectra with regard to the fermentation process.
Partial least-squares (PLS) calibration models have been generated from a series of near-infrared (near-IR) and Raman spectra acquired separately from sixty different mixed solutions of glucose, lactate, and urea in aqueous phosphate buffer. Independent PLS models were prepared and compared for glucose, lactate, and urea. Near-IR and Raman spectral features differed substantially for these solutes, with Raman spectra enabling greater distinction with less spectral overlap than features in the near-IR spectra. Despite this, PLS models derived from near-IR spectra outperformed those from Raman spectra. Standard errors of prediction were 0.24, 0.11, and 0.14 mmol L(-1) for glucose, lactate, and urea, respectively, from near-IR spectra and 0.40, 0.42, and 0.36 mmol L(-1) for glucose, lactate, and urea, respectively, from Raman spectra. Differences between instrumental signal-to-noise ratios were responsible for the better performance of the near-IR models. The chemical basis of model selectivity was examined for each model by using a pure component selectivity analysis combined with analysis of the net analyte signal for each solute. This selectivity analysis showed that models based on either near-IR or Raman spectra had excellent selectivity for the targeted analyte. The net analyte signal analysis also revealed that analytical sensitivity was higher for the models generated from near-IR spectra. This is consistent with the lower standard errors of prediction.
A high-performance liquid chromatography method was established for simultaneously determining seven major components, i.e. protocatechuic aldehyde, notoginsenoside R(1), ginsenoside Rg(1), salvianolic acid B, ginsenoside Rb(1), cryptotanshinone and tanshinone IIA in Fufang Danshen tablet, a commonly used traditional Chinese medicinal combined prescription mainly derived from the roots of Salvia miltiorrhiza and Panax notoginseng. These seven compounds, belonging to the chemical types of phenolic acids, diterpenoid quinones and saponins, were simultaneously separated on Zorbax C(18) column (250 x 4.6 mm, 5.0 microm) with the column temperature at 30 degrees C. The mobile phase was composed of (A) aqueous phosphoric acid (0.1%, v/v) and (B) acetonitrile using a gradient elution of 7-17% B at 0-10 min, 17-20% B at 10-12 min, 20-21% B at 12-16 min, 21% B at 16-32 min, 21-29% B at 32-40 min, 29-35% B at 40-55 min, 35-65% B at 55-65 min and 65-80% B at 65-80 min; the flow rate was 1.0 mL/min. Detection wavelengths were set at 203 nm for notoginsenoside R(1), ginsenoside Rg(1) and ginsenoside Rb(1), 281 nm for protocatechuic aldehyde, salvianolic acid B, and 270 nm for cryptotanshinone and tanshinone IIA. All calibration curves showed good linear regression (r(2) > 0.9992) within test ranges. The established method showed good precision and accuracy with overall intra-day and inter-day variations of 0.15-4.35 and 0.61-5.17% respectively, and overall recoveries of 94.8-102.1% for the seven compounds analyzed. The developed method has been successfully applied to simultaneous evaluation of the intrinsic quality of both Danshen and Sanqi in Fufang Danshen tablets from different pharmaceutical companies.