Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1223057 | Journal of Pharmaceutical and Biomedical Analysis | 2011 | 4 Pages |
Abstract
This paper establishes a novel method for the simultaneous analysis of moisture, active component and cake structure of lyophilized powder for injection using diffuse reflectance Fourier transform near infrared (FT-NIR) chemometrics. The experiment indicated that the back-propagation artificial neural network (BP-ANN) was suitable for the content predictions of moisture and active component; the root mean square errors of prediction (RMSEPs) were 0.1471 and 0.0082, the correlation coefficients (Rs) of prediction 0.9553 and 0.9891. And the self-organizing map (SOM) was adapted to the discrimination of cake structures; the prediction accuracy was 100.0%.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Yang Li, Qi Fan, Sha Liu, Liqiong Wang,