Simultaneous analysis of moisture, active component and cake structure of lyophilized powder for injection with diffuse reflectance FT-NIR chemometrics.
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%.
School of Pharmacy, Chongqing Medical University, Chongqing 400016, People's Republic of China.
Yang
Y
Li
Qi
Q
Fan
Sha
S
Liu
Liqiong
L
Wang
D055598:Chemical Phenomena; D007267:Injections; D008958:Models, Molecular; D016571:Neural Networks, Computer; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011208:Powders; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D013223:Statistics as Topic; D013678:Technology, Pharmaceutical; D014867:Water / Q000032:analysis*
D004364:Pharmaceutical Preparations; D011208:Powders; D014867:Water