Literature DB >> 26657202

Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes.

Marten Klukkert1, Jian X Wu2, Jukka Rantanen3, Jens M Carstensen4, Thomas Rades5, Claudia S Leopold6.   

Abstract

Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging as a reliable, rapid technique for estimation of the tablet API content and tablet hardness, as well as determination of tablet intactness and the tablet surface density profile. One of the aims was to establish an image analysis approach based on multivariate image analysis and pattern recognition to evaluate the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using an eccentric as well as a rotary tablet press at compression pressures from 20MPa up to 410MPa. It was found, that UV imaging can provide both, relevant information on chemical and physical tablet attributes. The tablet API content and radial tensile strength could be estimated by UV imaging combined with partial least squares analysis. Furthermore, an image analysis routine was developed and successfully applied to the UV images that provided qualitative information on physical tablet surface properties such as intactness and surface density profiles, as well as quantitative information on variations in the surface density. In conclusion, this study demonstrates that UV imaging combined with image analysis is an effective and non-destructive method to determine chemical and physical quality attributes of tablets and is a promising approach for (near) real-time monitoring of the tablet compaction process and formulation optimization purposes.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Enzyme tablets; Multispectral UV imaging; Multivariate image analysis; PLS; SIMCA; Tablet quality attributes

Mesh:

Substances:

Year:  2015        PMID: 26657202     DOI: 10.1016/j.ejps.2015.12.004

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  5 in total

Review 1.  Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets.

Authors:  Guolin Shi; Longfei Lin; Yuling Liu; Gongsen Chen; Yuting Luo; Yanqiu Wu; Hui Li
Journal:  RSC Adv       Date:  2021-02-23       Impact factor: 3.361

2.  Single Seed Identification in Three Medicago Species via Multispectral Imaging Combined with Stacking Ensemble Learning.

Authors:  Zhicheng Jia; Ming Sun; Chengming Ou; Shoujiang Sun; Chunli Mao; Liu Hong; Juan Wang; Manli Li; Shangang Jia; Peisheng Mao
Journal:  Sensors (Basel)       Date:  2022-10-04       Impact factor: 3.847

3.  Detection of Drechslera avenae (Eidam) Sharif [Helminthosporium avenae (Eidam)] in Black Oat Seeds (Avena strigosa Schreb) Using Multispectral Imaging.

Authors:  Fabiano França-Silva; Carlos Henrique Queiroz Rego; Francisco Guilhien Gomes-Junior; Maria Heloisa Duarte de Moraes; André Dantas de Medeiros; Clíssia Barboza da Silva
Journal:  Sensors (Basel)       Date:  2020-06-12       Impact factor: 3.576

Review 4.  Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring-An Overview.

Authors:  Gamal ElMasry; Nasser Mandour; Salim Al-Rejaie; Etienne Belin; David Rousseau
Journal:  Sensors (Basel)       Date:  2019-03-04       Impact factor: 3.576

Review 5.  Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview.

Authors:  Priyanka Reddy; Kathryn M Guthridge; Joe Panozzo; Emma J Ludlow; German C Spangenberg; Simone J Rochfort
Journal:  Sensors (Basel)       Date:  2022-03-03       Impact factor: 3.576

  5 in total

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