Predictive evaluation of powder X-ray diffractograms of pharmaceutical formulation powders based on infrared spectroscopy.
Powder X-ray diffraction analysis
attenuated total reflectance
infrared analysis
process analytical technology
Journal
Bio-medical materials and engineering
ISSN: 1878-3619
Titre abrégé: Biomed Mater Eng
Pays: Netherlands
ID NLM: 9104021
Informations de publication
Date de publication:
2020
2020
Historique:
pubmed:
8
9
2020
medline:
31
8
2021
entrez:
7
9
2020
Statut:
ppublish
Résumé
To ensure quality and stability, monitoring systems are recommended to analyze pharmaceutical manufacturing processes. This study was performed to predict powder X-ray diffraction (PXRD) patterns of formulation powders through attenuated total reflectance (ATR)-infrared (IR) spectroscopy in a nondestructive manner along with chemometrics. Caffeine anhydrate, acetaminophen, and lactose monohydrate were grinded at six weight ratios. The six sample groups were evaluated using ATR-IR spectroscopy and PXRD analysis. Partial least squares models were constructed to predict the PXRD intensities of the samples from the ATR-IR spectra. The prediction accuracy on the prepared PLS regression models was as high as R2 = 0.993. Linear relationships were obtained between the prediction data set and reference PXRD intensity at each degree. 2D PLS regression coefficient analysis enabled the analysis of the correlation between PXRD patterns and IR spectra.
Sections du résumé
BACKGROUND
BACKGROUND
To ensure quality and stability, monitoring systems are recommended to analyze pharmaceutical manufacturing processes.
OBJECTIVE
OBJECTIVE
This study was performed to predict powder X-ray diffraction (PXRD) patterns of formulation powders through attenuated total reflectance (ATR)-infrared (IR) spectroscopy in a nondestructive manner along with chemometrics.
RESULTS
RESULTS
Caffeine anhydrate, acetaminophen, and lactose monohydrate were grinded at six weight ratios. The six sample groups were evaluated using ATR-IR spectroscopy and PXRD analysis. Partial least squares models were constructed to predict the PXRD intensities of the samples from the ATR-IR spectra. The prediction accuracy on the prepared PLS regression models was as high as R2 = 0.993.
CONCLUSIONS
CONCLUSIONS
Linear relationships were obtained between the prediction data set and reference PXRD intensity at each degree. 2D PLS regression coefficient analysis enabled the analysis of the correlation between PXRD patterns and IR spectra.
Identifiants
pubmed: 32894235
pii: BME206003
doi: 10.3233/BME-206003
doi:
Substances chimiques
Powders
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM