2010
DOI: 10.1016/j.jpba.2009.12.009
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Influence of physical factors on the accuracy of calibration models for NIR spectroscopy

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Cited by 47 publications
(21 citation statements)
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“…Among the models presented in Table III, it can be seen that for ascorbic acid, model (j) has better prediction ability than other models. The (j) model has higher values for R 2 and lower values for RMSECV and bias than other models, notably models (g), (h) and (k). At the same time, it can be seen also in Table III, that for sodium ascorbate, model (h) is the model with a better prediction ability.…”
Section: Ascorbic Acid and Sodium Ascorbate Assay In Powder Blends Fomentioning
confidence: 92%
“…Among the models presented in Table III, it can be seen that for ascorbic acid, model (j) has better prediction ability than other models. The (j) model has higher values for R 2 and lower values for RMSECV and bias than other models, notably models (g), (h) and (k). At the same time, it can be seen also in Table III, that for sodium ascorbate, model (h) is the model with a better prediction ability.…”
Section: Ascorbic Acid and Sodium Ascorbate Assay In Powder Blends Fomentioning
confidence: 92%
“…The process spectrum is an approach towards including this future variation in a simple efficient manner. The process spectrum approach takes into consideration that during a pharmaceutical manufacturing process the chemical composition is often practically constant and the main changes are in the physical properties of samples [66][67][68]. The components in the formulation may be mixed or wet granulated increasing the particle size and changing the moisture content.…”
Section: Process Spectrum Approachmentioning
confidence: 99%
“…These chemometric measures were used to validate NIRS method to quantify active principal ingredients (API) in tablets [15][16][17][18][19][20][21][22] or powder blends [23,24] as well as excipients in tablets [15,18,22] or powder blends [23], for the quantification of API in injection samples [25] for the determination of adjuvant in vaccines [26], for the quantification of traditional Chinese medicine extracts in intermediates of drug products [27], to quantify the amount protein in controlled release matrix [28], to assess several steps of tableting process [29][30][31] or other processes [32], in commercial alginate powders [33], of polymorphs within API [34][35][36], drug substance in human plasma [37], to monitor on-line blend uniformity of pharmaceutical solid dosage forms [38] or for the monitoring API concentration in powder mixing process [39], to measure water content in various drug products [40][41][42][43][44]. These examples of application of NIRS in pharmaceutical applications demonstrate, if it still needs to, the broad applicability of such techniques in the development and control of pharmaceutical drug products.…”
Section: Traditional Chemometric Validationmentioning
confidence: 99%