Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7626836 | Journal of Pharmaceutical and Biomedical Analysis | 2018 | 10 Pages |
Abstract
Using laser diffraction, the granules have been analyzed for particle sizes and obtaining the summary sieve sizes of >63â¯Î¼m and >100â¯Î¼m. The following influences should be considered for application in routine production: constant changes in water content up to 21% and a product temperature up to 54â¯Â°C. The different stages of optimization result in a “Root Mean Square Error” of 2.54% for the calibration data set and 3.53% for the validation set by using the Kubelka-Munk conversion and first derivative for the near-infrared spectroscopy method for a particle size >63â¯Î¼m. For the near-infrared spectroscopy method using a particle size >100â¯Î¼m, the “Root Mean Square Error” was 3.47% for the calibration data set and 4.51% for the validation set, while using the same pre-treatments. - The robustness and suitability of this methodology has already been demonstrated by its recent successful implementation in a routine granulate production process.
Keywords
MSCKubelka-MunkRMSECMPAGMPEMAAPIRMSENIRPVPPBSLESPLSEuropean Medicines agencyLoss on dryingParticle sizefirst derivativemultiplicative scatter correctionGood Manufacturing PracticePharmaceutical technologyLOD یا Limit of detectionpartial least squareRoot Mean Square Error of Calibrationlight-emitting diodeRoot mean square errorNaproxen SodiumCelluloseLead sulfideCorrelation coefficientNear-infrared spectroscopyWater contentICHActive pharmaceutical ingredientsNear-infraredX-ray diffractionXRDGranulation
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
David Bär, Heiko Debus, Sina Brzenczek, Wolfgang Fischer, Peter Imming,