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A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes

Bernd Van Snick, Jens Dhondt, Kenny Pandelaere (UGent) , Johny Bertels, Roel Mertens, Didier Klingeleers, Giustino Di Pretoro, Jean Paul Remon (UGent) , Chris Vervaet (UGent) , Thomas De Beer (UGent) , et al.
(2018) INTERNATIONAL JOURNAL OF PHARMACEUTICS. 549(1-2). p.415-435
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Abstract
In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors.
Keywords
Material characterization, In silico design, Continuous direct compression, Multivariate data analysis, Pharmaceutical drug product development, Principal component analysis, CONTINUOUS DIRECT COMPRESSION, SCREW WET GRANULATION, FLOW PROPERTIES, TRIBO-ELECTRIFICATION, LACTOSE POWDERS, PARTICLE-SHAPE, ATTRIBUTES, IMPACT, SIZE, FUNCTIONALITY

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MLA
Van Snick, Bernd, et al. “A Multivariate Raw Material Property Database to Facilitate Drug Product Development and Enable In-Silico Design of Pharmaceutical Dry Powder Processes.” INTERNATIONAL JOURNAL OF PHARMACEUTICS, vol. 549, no. 1–2, 2018, pp. 415–35, doi:10.1016/j.ijpharm.2018.08.014.
APA
Van Snick, B., Dhondt, J., Pandelaere, K., Bertels, J., Mertens, R., Klingeleers, D., … Vanhoorne, V. (2018). A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes. INTERNATIONAL JOURNAL OF PHARMACEUTICS, 549(1–2), 415–435. https://doi.org/10.1016/j.ijpharm.2018.08.014
Chicago author-date
Van Snick, Bernd, Jens Dhondt, Kenny Pandelaere, Johny Bertels, Roel Mertens, Didier Klingeleers, Giustino Di Pretoro, et al. 2018. “A Multivariate Raw Material Property Database to Facilitate Drug Product Development and Enable In-Silico Design of Pharmaceutical Dry Powder Processes.” INTERNATIONAL JOURNAL OF PHARMACEUTICS 549 (1–2): 415–35. https://doi.org/10.1016/j.ijpharm.2018.08.014.
Chicago author-date (all authors)
Van Snick, Bernd, Jens Dhondt, Kenny Pandelaere, Johny Bertels, Roel Mertens, Didier Klingeleers, Giustino Di Pretoro, Jean Paul Remon, Chris Vervaet, Thomas De Beer, and Valérie Vanhoorne. 2018. “A Multivariate Raw Material Property Database to Facilitate Drug Product Development and Enable In-Silico Design of Pharmaceutical Dry Powder Processes.” INTERNATIONAL JOURNAL OF PHARMACEUTICS 549 (1–2): 415–435. doi:10.1016/j.ijpharm.2018.08.014.
Vancouver
1.
Van Snick B, Dhondt J, Pandelaere K, Bertels J, Mertens R, Klingeleers D, et al. A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes. INTERNATIONAL JOURNAL OF PHARMACEUTICS. 2018;549(1–2):415–35.
IEEE
[1]
B. Van Snick et al., “A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes,” INTERNATIONAL JOURNAL OF PHARMACEUTICS, vol. 549, no. 1–2, pp. 415–435, 2018.
@article{8614526,
  abstract     = {{In current study a holistic material characterization approach was proposed and an extensive raw material property database was developed including a wide variety of APIs and excipients with different functionalities. In total 55 different materials were characterized and described by over 100 raw material descriptors related to particle size and shape distribution, specific surface area, bulk, tapped and true density, compressibility, electrostatic charge, moisture content, hygroscopicity, permeability, flowability and wall friction. Principal component analysis (PCA) was applied to reveal similarities and dissimilarities between materials and to identify overarching properties. The developed PCA model allows to rationalize the number of critical characterization techniques in routine characterization and to identify surrogates for use during early drug product development stages when limited amounts of active pharmaceutical ingredients are available. Additionally, the developed database will be the basis to build predictive models for in silico process and formulation development based on (a selection of) property descriptors.}},
  author       = {{Van Snick, Bernd and Dhondt, Jens and Pandelaere, Kenny and Bertels, Johny and Mertens, Roel and Klingeleers, Didier and Di Pretoro, Giustino and Remon, Jean Paul and Vervaet, Chris and De Beer, Thomas and Vanhoorne, Valérie}},
  issn         = {{0378-5173}},
  journal      = {{INTERNATIONAL JOURNAL OF PHARMACEUTICS}},
  keywords     = {{Material characterization,In silico design,Continuous direct compression,Multivariate data analysis,Pharmaceutical drug product development,Principal component analysis,CONTINUOUS DIRECT COMPRESSION,SCREW WET GRANULATION,FLOW PROPERTIES,TRIBO-ELECTRIFICATION,LACTOSE POWDERS,PARTICLE-SHAPE,ATTRIBUTES,IMPACT,SIZE,FUNCTIONALITY}},
  language     = {{eng}},
  number       = {{1-2}},
  pages        = {{415--435}},
  title        = {{A multivariate raw material property database to facilitate drug product development and enable in-silico design of pharmaceutical dry powder processes}},
  url          = {{http://doi.org/10.1016/j.ijpharm.2018.08.014}},
  volume       = {{549}},
  year         = {{2018}},
}
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