Rapid and Nondestructive Analysis of Bacillus Calmette–Guerin Polysaccharide Nucleic Acid Injection by near-Infrared Spectroscopy with Chemometrics

Abstract

ABSTRACTA novel quantitative analytical method using near-infrared (NIR) spectroscopy combined with chemometrics has been developed to determine the polysaccharides and nucleic acids for routine quality analysis of Bacillus Calmette–Guerin polysaccharide and nucleic acid injections. A Monte-Carlo method was used to detect and discard outliers and to improve the predictive ability of the model. Various other spectral preprocessing methods such as smoothing, derivative, multiplicative scattering correction, standard normal variables, and orthogonal signal correction methods were used to remove noise and other irrelevant information from the spectra. Sample-set partitioning based on joint x–y distance method was utilized to divide the sample measurements into calibration and validation datasets. The optimal wavelength variables were determined by competitive adaptive weighted sampling. The model was established and cross-validated using partial least square regression. The root mean square errors of cross-validation for polysaccharides and nucleic acids were determined to be 0.0382 and 5.218, and the root mean square errors of prediction were 0.0229 and 6.282. The overall results show that NIR spectroscopy combined with chemometry is effective for the quantitative analysis of Bacillus Calmette–Guerin polysaccharide and nucleic acid injections.