Near-infrared chemical imaging (NIR-CI) as a process monitoring solution for a production line of roll compaction and tableting |
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| Institution: | 1. Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark;2. Department of Food Science, Faculty of Science, University of Copenhagen, Denmark;3. Department of Pharmaceutic, College of Pharmacy, University of Minnesota, USA;4. Takeda Pharma A/S, Roskilde, Denmark;1. Institute of Chemistry, State University of Campinas – UNICAMP, P.O. Box 6154, 13084-971 Campinas, SP, Brazil;2. Department of Pharmaceutics and Analytical Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Universitetsparken 2, 2100 Copenhagen, Denmark;3. Department of Food Science, Faculty of Sciences, University of Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C, Denmark;1. Department of Chemical and Process Engineering, University of Surrey, Guildford GU27XH, UK;2. Advantest Inc., Princeton, NJ, USA;1. Pfizer Industrial Research Chair on Process Analytical Technology in Pharmaceutical Engineering, Department of Chemical & Biotechnological Engineering, Université de Sherbrooke, Sherbrooke, Quebec, Canada;2. Faculty of Pharmacy, Université Montpellier I, France;3. Process Analytical Science Group, Pfizer, Saint-Laurent, Quebec, Canada;1. Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, Sweden;2. Industrial Doctoral School, Umeå University, Umeå, Sweden;3. Pharmaceutical Development, AstraZeneca R&D, Mölndal, Sweden;1. Department of Engineering Science, Osaka Electro-Communication University, 18-8 Hatsucho, Neyagawa 572-8530, Japan;2. Technology Department, Mitsubishi Tanabe Pharma Factory, 955, Koiwai, Yoshitomi-cho, Chikujo-gun, Fukuoka 871-8550, Japan |
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| Abstract: | In the present study the application of near-infrared chemical imaging (NIR-CI) supported by chemometric modeling as non-destructive tool for monitoring and assessing the roller compaction and tableting processes was investigated. Based on preliminary risk-assessment, discussion with experts and current work from the literature the critical process parameter (roll pressure and roll speed) and critical quality attributes (ribbon porosity, granule size, amount of fines, tablet tensile strength) were identified and a design space was established. Five experimental runs with different process settings were carried out which revealed intermediates (ribbons, granules) and final products (tablets) with different properties. Principal component analysis (PCA) based model of NIR images was applied to map the ribbon porosity distribution. The ribbon porosity distribution gained from the PCA based NIR-CI was used to develop predictive models for granule size fractions. Predictive methods with acceptable R2 values could be used to predict the granule particle size. Partial least squares regression (PLS-R) based model of the NIR-CI was used to map and predict the chemical distribution and content of active compound for both roller compacted ribbons and corresponding tablets. In order to select the optimal process, setting the standard deviation of tablet tensile strength and tablet weight for each tablet batch was considered. Strong linear correlation between tablet tensile strength and amount of fines and granule size was established, respectively. These approaches are considered to have a potentially large impact on quality monitoring and control of continuously operating manufacturing lines, such as roller compaction and tableting processes. |
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| Keywords: | Near-infrared chemical imaging Principal component analysis Partial least squares Roll compaction/dry granulation Ribbon porosity map Ribbon chemical map Tablet chemical map |
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