Thesis
Measurement, optimisation and control of particle properties in pharmaceutical manufacturing processes
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Engineering and Physical Sciences Research Council
- Date of award
- 2020
- Thesis identifier
- T15540
- Person Identifier (Local)
- 201562518
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- The understanding and optimisation of particle properties connected to their structure and morphology is a common objective for particle engineering applications either to improve materialhandling in the manufacturing process or to influence Critical Quality Attributes (CQAs) linkedto product performance. This work aims to demonstrate experimental means to support a rational development approach for pharmaceutical particulate systems with a specific focus ondroplet drying platforms such as spray drying.Micro-X-ray tomography (micro-XRT) is widely applied in areas such as geo- and biomedicalsciences to enable a three dimensional investigation of the specimens. Chapter 4 elaborateson practical aspects of micro-XRT for a quantitative analysis of pharmaceutical solid productswith an emphasis on implemented image processing and analysis methodologies. Potentialapplications of micro-XRT in the pharmaceutical manufacturing process can range from thecharacterisation of single crystals to fully formulated oral dosage forms. Extracted quantitativeinformation can be utilised to directly inform product design and production for process development or optimisation. The non-destructive nature of the micro-XRT analysis can be furtheremployed to investigate structure-performance relationships which might provide valuable insights for modelling approaches.Chapter 5 further demonstrates the applicability of micro-XRT for the analysis of ibuprofen capsules as a multi-particulate system each with a population of approximately 300 pellets. Thein-depth analysis of collected micro-XRT image data allowed the extraction of more than 200features quantifying aspects of the pellets’ size, shape, porosity, surface and orientation. Employed feature selection and machine learning methods enabled the detection of broken pelletswithin a classification model. The classification model has an accuracy of more than 99.55%and a minimum precision of 86.20% validated with a test dataset of 886 pellets from three capsules.The combination of single droplet drying (SDD) experiments with a subsequent micro-XRTanalysis was used for a quantitative investigation of the particle design space and is describedin Chapter 6. The implemented platform was applied to investigate the solidification of formulated metformin hydrochloride particles using D-mannitol and hydroxypropyl methylcellulosewithin a selected, pragmatic particle design space. The results indicate a significant impact ofhydroxypropyl methylcellulose reducing liquid evaporation rates and particle drying kinetics.The morphology and internal structure of the formulated particles after drying are dominatedby a crystalline core of D-mannitol partially suppressed with increasing hydroxypropyl methylcellulose additions. The characterisation of formulated metformin hydrochloride particles withincreasing polymer content demonstrated the importance of an early-stage quantitative assessment of formulation-related particle properties.A reliable and rational spray drying development approach needs to assess parameters of thecompound system as well as of the process itself in order to define a well-controlled and robustoperational design space. Chapter 7 presents strategies for process implementation to producepeptide-based formulations via spray drying demonstrated using s-glucagon as a model peptide.The process implementation was supported by an initial characterisation of the lab-scale spraydryer assessing a range of relevant independent process variables including drying temperatureand feed rate. The platform response was captured with available and in-house developed Process Analytical Technology. A B-290 Mini-Spray Dryer was used to verify the developmentapproach and to implement the pre-designed spray drying process. Information on the particleformation mechanism observed in SDD experiments were utilised to interpret the characteristics of the spray dried material.
- Advisor / supervisor
- Oswald, Iain D. H.
- Florence, Alastair
- Resource Type
- Note
- Previously held under moratorium from 2 June 2020 until 6 June 2022.
- DOI
- Date Created
- 2020
- Former identifier
- 9912881692502996
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PDF of thesis T15540 | 2021-07-02 | Público | Baixar |