Investigation into process-induced de-aggregation of cohesive micronised API particles

Hoffmann, Magnus; Wray, Patrick S.; Gamble, John F.; Tobyn, Mike

doi:10.1016/j.ijpharm.2015.07.073

Cited by 10 publications

(3 citation statements)

References 42 publications

(40 reference statements)

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“…The API at this stage is typically characterised prior to inclusion in a formulated blend ready for preparation of a final drug product, often with the assumption that the input powder characteristics represent that of the API in the final dosage form. Recent applications of integrated image analysis/spectroscopic tools has provided a means to directly determine the size (and shape) of API particles within formulated samples demonstrating that this assumption is not always appropriate (30)(31)(32)(33) and may indeed have an impact on the downstream processability (e.g. sticking) of such formulations (34).…”

Section: Data Quality and Novel Characterisation Methodsmentioning

confidence: 99%

Enhanced Understanding of Pharmaceutical Materials Through Advanced Characterisation and Analysis

et al. 2018

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The impact of pharmaceutical materials properties on drug product quality and manufacturability is well recognised by the industry. An ongoing effort across industry and academia, the Manufacturing Classification System consortium, aims to gather the existing body of knowledge in a common framework to provide guidance on selection of appropriate manufacturing technologies for a given drug and/or guide optimization of the physical properties of the drug to facilitate manufacturing requirements for a given processing route. Simultaneously, material scientists endeavour to develop characterisation methods such as size, shape, surface area, density, flow and compactibility that enable a stronger understanding of materials powder properties. These properties are routinely tested drug product development and advances in instrumentation and computing power have enabled novel characterisation methods which generate larger, more complex data sets leading to a better understanding of the materials. These methods have specific requirements in terms of data management and analysis. An appropriate data management strategy eliminates timeconsuming data collation steps and enables access to data collected for multiple methods and materials simultaneously. Methods ideally suited to extract information from large, complex data sets such as multivariate projection methods allow simpler representation of the variability contained within the data and easier interpretation of the key information it contains. In this review, an overview of the current knowledge and challenges introduced by modern pharmaceutical material characterisation methods is provided. Two case studies illustrate how the incorporation of multivariate analysis into the material sciences workflow facilitates a better understanding of materials.

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Section: Data Quality and Novel Characterisation Methodsmentioning

confidence: 99%

Enhanced Understanding of Pharmaceutical Materials Through Advanced Characterisation and Analysis

et al. 2018

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“…This all becomes notably more complex when dealing with the characterisation of individual components within multi-component systems. In recent work [8,12,13] the particle size and shape distributions of individual components within multi-component pharmaceutical systems has been extracted in order to monitor the change in the physical nature of formulated drug particles during manufacture. Such approaches utilise spectroscopic tools to chemically classify the particles thus enabling extraction of the characteristics of the individual components.…”

Section: Introductionmentioning

confidence: 99%

Alternative approach for defining the particle population requirements for static image analysis based particle characterization methods

Clarke

Gamble

Jones

et al. 2019

Advanced Powder Technology

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“…At this stage, it is not possible to resolve the image to the level of the primary particles by Raman chemical imaging. The morphology of primary particles is one of the key factors in determining the formulation functions [8,9]. Development of imaging techniques for the primary particles in the aggregation would greatly contribute to formulation research and quality control.…”

Section: Introductionmentioning

confidence: 99%

Visualization of Primary Particles in a Tablet Based on Raman Crystal Orientation Mapping

Moriyama¹,

Onishi²

2015

Pharm Anal Acta

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Objective: The morphology of the primary particles in the active pharmaceutical ingredient (API) is one of the most important determinants for formulation function. However, it has not been possible to visualize primary particles in a tablet using various imaging methods, including spectroscopic mappings, because these particles usually exist as aggregated clusters in tablets. We revealed that the Raman spectrum of crystalline particles is determined depending upon the angle between the crystallographic axis and the polarization direction of the excitation laser. In this paper, we report a method to visualize primary particles within the aggregated cluster based on the Raman spectral change on the boundary of primary particles. Method: Metformin hydrochloride was chosen as a model API for this study. The crystal structure of metformin hydrochloride was solved using X-ray crystal structure analysis. The Raman spectra of metformin hydrochloride crystal along the xyz axes were recorded and resolved into components along the abc axes. Using the abc components, Raman mapping of metformin hydrochloride in tablets was performed to visualize the crystal orientation at each data point. Results: Metformin hydrochloride crystals recrystallized from water/ethanol formed a primitive monoclinic cell. Datasets of five distinct peak areas from the metformin hydrochloride Raman spectrum were used for analyses. Raman crystal orientation mapping (RCOM) from the tablet cross-section provided an image of primary particles within the aggregation cluster of metformin hydrochloride in the tablet. Conclusion: Based on the RCOM, we developed a visualization method for primary API particles in tablets. Because the morphology of primary particles is the key factor of formulation function, this method would contribute to better formulation development and quality control.

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Investigation into process-induced de-aggregation of cohesive micronised API particles

Cited by 10 publications

References 42 publications

Enhanced Understanding of Pharmaceutical Materials Through Advanced Characterisation and Analysis

Enhanced Understanding of Pharmaceutical Materials Through Advanced Characterisation and Analysis

Alternative approach for defining the particle population requirements for static image analysis based particle characterization methods

Visualization of Primary Particles in a Tablet Based on Raman Crystal Orientation Mapping

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