Prediction of drug dissolution from Toremifene 80 mg tablets by NIR spectroscopy.
Design of experiments
Discrimination capability
Dissolution
Near infrared spectroscopy
PLS calibration model
Toremifene
Journal
International journal of pharmaceutics
ISSN: 1873-3476
Titre abrégé: Int J Pharm
Pays: Netherlands
ID NLM: 7804127
Informations de publication
Date de publication:
15 Mar 2020
15 Mar 2020
Historique:
received:
09
09
2019
revised:
08
01
2020
accepted:
09
01
2020
pubmed:
20
1
2020
medline:
6
1
2021
entrez:
20
1
2020
Statut:
ppublish
Résumé
The aim of our study was to justify substitution of dissolution analysis for NIR measurement of Toremifene 80 mg tablets. We studied implementation of a NIRS method by integrating the method development to discrimination power of the dissolution method. Hence, we analyzed 20 DoE tablet batches and studied which of the critical formulation factors affecting dissolution were statistically significant. To study if these factors can be detected by NIRS, PLS calibration models were developed. Finally, PLS model was built to correlate NIR data with the actual dissolution results to predict the released amount of toremifene in 30 min. To obtain the data the tablet batches were measured by NIR using diffuse reflectance technique and multivariate analysis tool was used to calibrate the NIRS models. Correlations between the critical formulation factors and the NIR spectra of Toremifene 80 mg tablet were shown and it was thus justified to develop a NIRS prediction model for dissolution. Variance (R
Identifiants
pubmed: 31954865
pii: S0378-5173(20)30010-7
doi: 10.1016/j.ijpharm.2020.119028
pii:
doi:
Substances chimiques
Tablets
0
Toremifene
7NFE54O27T
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
119028Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. KO, MM and AL are employees of Orion Pharma, Orion Corporation.