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Multivariate statistical quality control of a pharmaceutical manufacturing process using near infrared spectroscopy and imaging microscopy

O'Neil, Andrew James; (2000) Multivariate statistical quality control of a pharmaceutical manufacturing process using near infrared spectroscopy and imaging microscopy. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Multivariate Statistical Quality Control of a Pharmaceutical Manufacturing Process Using Near Infrared Spectroscopy And Imaging Microscopy The ability of near infrared (NIR) reflectance and transmittance spectroscopy and near infrared imaging microscopy to enable multivariate statistical quality control of an entire pharmaceutical tablet manufacturing process has been demonstrated. Statistical quality control of process intermediates at each of the processes' stages (raw materials dispensing, powder blending and tabletting of blend) required construction of a multivariate model from a reference set of NIR spectroscopic measurements of process intermediates. With blends and tablets, these measurements were collected from a number of different batches where the process was known to have operated within specification and within a state of statistical control. With the powdered raw materials, measurements were made of pharmaceutical grade materials. Using the multivariate models, it was shown possible to assess the quality of raw materials by NIR spectroscopy and determine their suitability for use in manufacture. Simultaneous determination of powdered pharmaceutical raw materials' identities and their accurate particle size distributions were obtainable from a single averaged NIR spectrum. The models developed from NIR measurements of blends and tablets enabled a level of quality control at each of these process stages superior to current reference analytical laboratory measurements of these. Significant trends in process deviation could be identified from an averaged NIR spectrum even at the blend stage despite within specification reference laboratory data. These batches of blends ultimately produced tablets of lower quality. This included tablet friability, increased tablet thickness and prolonged tablet dissolution time. NIR microscopic imaging of these lower quality pharmaceutical blends was examined to provide more detailed diagnostic information. The spatial locations and size of drug substance particles could be readily identified and in some instances showed unmilled drug substance particles. This demonstrated the potential of NIR imaging microscopy for on-line or at-line quality control of the blending stage.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Multivariate statistical quality control of a pharmaceutical manufacturing process using near infrared spectroscopy and imaging microscopy
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest.
Keywords: Health and environmental sciences; Pharmaceutical manufacturing
URI: https://discovery.ucl.ac.uk/id/eprint/10105310
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