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Predicting the physical properties of tablets from ATR-FTIR spectra using partial least squares regression

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Taylor, Michael and Elhissi, Adbelbary (2010) Predicting the physical properties of tablets from ATR-FTIR spectra using partial least squares regression. Pharmaceutical Development and Technology, 16 (2). pp. 110-117. ISSN 1083-7450

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Official URL: http://dx.doi.org/10.3109/10837450903499374

Abstract

Context: The formulation of a new tablet is a time-consuming activity involving the preparation and testing of many different formulations with the aim of identifying one with the desired properties. In complex formulations it may not be clear which excipient is responsible for eliciting a particular property.

Objective: To investigate partial least squares (PLS) regression analysis of ATR-FTIR spectra of tablets as a predictive and investigative tool in the formulation of novel tablet formulations.

Materials: Magnesium stearate, lactose, acetylsalicylic acid and Ac-Di-Sol.

Results and discussion: ATR-FTIR spectra of a simple aspirin tablet formulation with varying amounts of the lubricant magnesium stearate were obtained. PLS models were built using the spectral data as the multivariate variable and various physical properties of the tablets as the univariate variables. PLS models that allowed good predications to be made for samples not included in the training set were obtained for tablet hardness and disintegration time. It was clear from PLS model regression coefficients that magnesium stearate was responsible for the variation in the tablets’ physical properties.

Conclusion: PLS regression in combination with ATR-FTIR spectroscopy has been shown to be a useful approach for the prediction of the physical properties of tablets.


Item Type:Article
Additional Information:This eprint record has not been checked by the Author.
Uncontrolled Keywords (separate with ;):Multivariate, formulation, prediction, spectroscopy
Subjects:R Medicine > RS Pharmacy and materia medica
Schools:School of Pharmacy and Biomedical Sciences
ID Code:1347
Deposited By: Helen Cooper
Deposited On:06 Aug 2010 16:43
Last Modified:13 Jun 2012 15:14

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