Research In The Application Of Near Infrared Reflected Spectroscopy In Pharmacy Quantitative Analysis

With the rapid development of computation technique and chemometrics, the analytical problems which are aroused by the poor effected information in the near infrared spectroscopy (NIRS), difficulties for regression because of overlapped and conlinear spectra have been solved. Near infrared spectroscopy has become one of the fast (rapid) developments and most mentioned analytical technologies in this century. In this paper, the application of partial least squares regression (PLSR) method for the relationship between the NIR spectra and the contents of components in anti-tuberculosis drug has been studied. The results demonstrated that this method was good at extracting the effect information from the NIR spectra and parsed the problem of overlapped and conlinear spectra. With its advantages of no pretreatment, no pollution, facility, non-destructibility and online measurement, it has been taken as an appealing tool for solving all sorts of analytical problems, for all sorts of samples, such as liquid, dense, coat, powder and solid. In recent years, with the developing of chemometrics, optics, electronics and computer science, NIRS is being applied to numerous fields, including agriculture, food, chemical, pharmaceuticals, textiles, polymers, cosmetics, tobacco and medical.1. The application of near infrared spectra technique with partial least squares regression in determination of pyrazinamide tablets: Applied data pretreatment approaches including Savitzky-Golay smoothing, first derivative and second derivative to dispose the NIR spectra of pyrazinamide tablets, and introduced a novel method using the RSD of the spectra and the correlation coefficient between the absorbance at every wavelength and the contents of the pyrazinamide in the samples to choose the optimal wavelength regions. The original spectra and every pretreated spectrum at each spectra region were applied to develop the quantitative analysis models for determination the contents of the pyrazinamide and stuffs in pyrazinamide tablets respectively. Suitable numbers of the factor for he developed models were selected depended on the root mean squares error of calibration set by cross-validation method (RMSECV) and Predicted Residual Error Sum of Squares (PRESS), and then, the optimum models were selected according as root mean squares error of calibration set (RMSEC), correlation coefficient between the precicted values and actual values (Rc)and the root mean square error of predictive set (RMSEP). All of this model that for determination of pyrazinamide, magnesium stearate, starch, catboxymethyl cellulose and dextrin in pyrazinamide tablets applied the first derivative spectra with the region of 800~1717 nm, their suitable numbers of factor were 8, 6, 7, 7 and 8, RMSEC were 0.1860, 0.0114, 0.0801, 0.0790 and 0.0576, Rc were 0.99950, 0.99753, 0.99915, 0.99910 and 0.99952, RMSEP were 0.2450, 0.0178, 0.0990, 0.0839 and 0.1090. These results indicate that this method is feasible, rapid, non-pretreated, and non-destructed, it have great application foreground.2. The application of near infrared spectra technique with partial least squares regression in determination of lifampicin and isoniazid tablets: Applied data pretreatment approaches including Savitzky-Golay smoothing, first derivative and second derivative to dispose the NIR spectra of lifampicin and isoniazid tablets. The original spectra and every pretreated spectrum at each spectral region were applied to develop the quantitative analysis models for determination the contents of the lifampicin and isoniazid in lifampicin and isoniazid tablets. Suitable numbers of the factor for he developed models were selected depended on the root mean squares error of calibration set by cross-validation method (RMSECV) and Predicted Residual Error Sum of Squares (PRESS), and then, the optimum models were selected according as RMSECV, correlation coefficient between the precicted values by cross-validation method and actual values (Rv) and the root mean square error of predictive set (RMSEP). The model that for determination of the content of lifampicin in lifampicin and isoniazid tablets applied the first derivative spectra with the region of 1100~1374 nm, its suitable numbers of factor were 4, RMSECV was 0.00665, Rv was 0.99277, RMSEP was 0.00493. The model that for determination of the content of isoniazide in lifampicin and isoniazid tablets applied the Savitzky-Golay smoothing spectra with the region of 1100~1374 nm, its suitable numbers of factor were 6, RMSECV was 0.00423, Rv was 0.98901, RMSEP was 0.00393. This method has good predicted abilities and repeatability. These results indicate that this method is feasible, rapid, non-pretreated, and non-destructed, it have great application foreground.In this paper, I studied on extracting information and pretreatment of NIR spectra, applied the PLS to construct a quantitative determination model to predict the amount of pyrazinamide, and compound antituberculosis drug. It's not necessary to pretreat the samples in chemical means. PLS can analyze the overlapped NIR spectra well, it also can reduce interfere of the component. Precision of this method is up to the mustard in the produce process of antituberculosis drug. It can be generalized to on-line and real-time quality control in pharmacy.