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

Snick, B. Van; Dhondt, Jens; Pandelaere, K.; Bertels, Johny; Mertens, Roel; Klingeleers, Didier; Pretoro, G. Di; Remon, Jean Paul; Vervaet, Chris; Beer, Thomas De

doi:10.1016/j.ijpharm.2018.08.014

Cited by 79 publications

(39 citation statements)

References 31 publications

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“…The raw materials included in this study were selected from the raw material database described by Van Snick et al (Van Snick et al, 2018a). Furthermore, additional APIs were included as these APIs will be used in an application where the studied feeder will be implemented in a continuous manufacturing line for pharmaceutical semi-solid and liquid formulations (Bostijn et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…The first step is to establish a database containing all the appropriate material properties from a wide selection of representative powders. Such an extensive raw material property database was recently developed by Van Snick et al (Van Snick et al, 2018a), in which more than 50 pharmaceutical powders were characterized in detail using a wide variety of techniques resulting in more than 100 material property descriptors.…”

Section: Introductionmentioning

confidence: 99%

“…This study is an application of the raw material property database developed by Van Snick et al (Van Snick et al, 2018a). While they developed a PCA model and identified the correlated and relevant material property descriptors, the current study aims at linking these relevant material property descriptors with the volumetric and gravimetric feeding behavior of a low feed rate feeder.…”

Section: Introductionmentioning

confidence: 99%

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A multivariate approach to predict the volumetric and gravimetric feeding behavior of a low feed rate feeder based on raw material properties

Bostijn

Dhondt

Ryckaert

et al. 2019

International Journal of Pharmaceutics

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The UGent Institutional Repository is the electronic archiving and dissemination platform for all UGent research publications. Ghent University has implemented a mandate stipulating that all academic publications of UGent researchers should be deposited and archived in this repository. Except for items where current copyright restrictions apply, these papers are available in Open Access. This item is the archived peer-reviewed author-version of: A multivariate approach to predict the volumetric and gravimetric feeding behavior of a low feed rate feeder based on raw material properties

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A multivariate approach to predict the volumetric and gravimetric feeding behavior of a low feed rate feeder based on raw material properties

Bostijn

Dhondt

Ryckaert

et al. 2019

International Journal of Pharmaceutics

Self Cite

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“…Ultimately, it can be claimed that investigating the impact of all the above-noted variables on the diverse processing steps needs a high amount of the given powder, which is not preferable during the early drug development or in case of costly samples. Recently, a research article was published about a multivariate raw material property database that can provide a solution for handling the problem of high powder demand [94]. Fifty five different raw materials inclusive of APIs and numerous distinct excipients were characterized.…”

Section: Powder Characterizationmentioning

confidence: 99%

Continuous Formulation Approaches of Amorphous Solid Dispersions: Significance of Powder Flow Properties and Feeding Performance

et al. 2019

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Preparation and formulation of amorphous solid dispersions (ASDs) are becoming more and more popular in the pharmaceutical field because the dissolution of poorly water-soluble drugs can be effectively improved this way, which can lead to increased bioavailability in many cases. During downstream processing of ASDs, technologists need to keep in mind both traditional challenges and the newest trends. In the last decade, the pharmaceutical industry began to display considerable interest in continuous processing, which can be explained with their potential advantages such as smaller footprint, easier scale-up, and more consistent product, better quality and quality assurance. Continuous downstream processing of drug-loaded ASDs opens new ways for automatic operation. Therefore, the formulation of poorly water-soluble drugs may be more effective and safe. However, developments can be challenging due to the poor flowability and feeding properties of ASDs. Consequently, this review pays special attention to these characteristics since the feeding of the components greatly influences the content uniformity in the final dosage form. The main purpose of this paper is to summarize the most important steps of the possible ASD-based continuous downstream processes in order to give a clear overview of current course lines and future perspectives.

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“…Latent variable modelling (LVM) methods are extensively used in pharmaceutical development to uncover the multidimensional relationships and interactions among raw material properties, process parameters and product quality attribute [36,41,42,87,[89][90][91][92][93]. In this paper, the PLS methods are applied to investigate the influence of raw material physical characteristics, roll compaction descriptors and hydraulic pressures on ribbon critical quality attributes (CQAs), i.e., solid fraction and tensile strength.…”

Section: Latent Variable Modeling In Prediction Of Ribbon Propertiesmentioning

confidence: 99%

Using a Material Library to Understand the Impacts of Raw Material Properties on Ribbon Quality in Roll Compaction

Zhang

et al. 2019

Pharmaceutics

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The purpose of this study is to use a material library to investigate the effect of raw material properties on ribbon tensile strength (TS) and solid fraction (SF) in the roll compaction (RC) process. A total of 81 pharmaceutical materials, including 53 excipients and 28 natural product powders (NPPs), were characterized by 22 material descriptors and were compacted under five different hydraulic pressures. The transversal and longitudinal splitting behaviors of the ribbons were summarized. The TS-porosity and TS-pressure relationships were used to explain the roll compaction behavior of powdered materials. Through defining the target ribbon quality (i.e., 0.6 ≤ SF ≤ 0.8 and TS ≥ 1 MPa), the roll compaction behavior classification system (RCBCS) was built and 81 materials were classified into three categories. A total of 24 excipients and five NPPs were classified as Category I materials, which fulfilled the target ribbon quality and had less occurrence of transversal splitting. Moreover, the multivariate relationships between raw material descriptors, the hydraulic pressure and ribbon quality attributes were obtained by PLS regression. Four density-related material descriptors and the cohesion index were identified as critical material attributes (CMAs). The multi-objective design space summarizing the feasible material properties and operational region for the RC process were visualized. The RCBCS presented in this paper enables a formulator to perform the initial risk assessment of any new materials, and the data modeling method helps to predict the impact of formulation ingredients on strength and porosity of compacts.

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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

Cited by 79 publications

References 31 publications

A multivariate approach to predict the volumetric and gravimetric feeding behavior of a low feed rate feeder based on raw material properties

A multivariate approach to predict the volumetric and gravimetric feeding behavior of a low feed rate feeder based on raw material properties

Continuous Formulation Approaches of Amorphous Solid Dispersions: Significance of Powder Flow Properties and Feeding Performance

Using a Material Library to Understand the Impacts of Raw Material Properties on Ribbon Quality in Roll Compaction

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