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Title: Modelling and prediction of non-linear scale-up from an Ultra Scale-Down membrane device to process scale tangential flow filtration
Author: Hussain, Mohd Shawkat
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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Ultra scale-down (USD) tools have demonstrated the huge potential for accelerated process development by significantly reducing the material requirements and providing better solutions, as part of the Quality by Design initiative. Key benefits of using USD techniques include the relatively small quantities of feedstock and minimal capital equipment needed to generate large volumes of statistically significant process data in a short period, leading to significant time and cost savings during process development. However, the use of small scale devices such as the stirred cell filtration units have been primarily limited to preliminary testing and initial screening due to their geometric and flow dissimilarities to tangential flow filtration at scale. As a result, process development and optimisation trials are generally carried out using the smallest c commercially available TFF cassettes, the use of which are primarily limited by time and material constraints that are invariably present at the early stages of process development. Therefore, the central focus of this work was to develop a USD methodology and model to accurately predict the performance of large scale tangential flow filtration (TFF) using a USD membrane filtration device. The commercial package COMSOL was used to carry out computational fluid dynamics (CFD) modelling and simulation of the fluid flow dynamics in Pellicon TFF cassettes with different feed screens and a USD membrane device, in order to develop average wall shear rate correlations and channel pressure drops expressed as functions of the respective hydrodynamic conditions across scales. In addition, the impact of non-TFF related factors such as the system and cassette-specific hydraulic resistances on TFF performance was characterised using semi-empirical models. Finally, a scale-up methodology and mathematical model to predict the large scale performance using USD data was developed by combining the various resistances, channel pressure drop correlations and an empirical USD-derived model that characterises the specific feed-membrane interactions. The CFD simulations were independently verified using 2D particle imaging velocimetry to compare experimental data to the CFD simulated data. 100-fold scale-up experiments were carried out based on equivalent averaged wall shear rates (w) as the geometry-independent parameter. Permeate flux excursions were carried out to validate the USD methodology and prediction model, by comparing USD model predictions against the large scale experimental data. Different membranes, feed screens (A, C and V) and feedstock, ranging from simple proteins like Bovine Serum Albumin (BSA) to more complex, multicomponent feed such as Escherichia coli homogenate, were used. Predicted flux and transmission results were in good agreement with the large scale experimental data, showing less than 5% difference across scales, demonstrating the robustness of the non-linear scale-up model. Following the successful validation of the scale-up methodology and prediction model, other potential applications of the USD membrane device such as the optimisation of TFF microfiltration was demonstrated using Saccharomyces cerevisae and Chlorella sorokiniana. Fed-batch concentration experiments using Saccharomyces cerevisae were done to compare the volumetric throughput limits. The USD-predicted capacity limit of 49.2 L/m2 was very similar to the experimental large scale capacity value of 52.0 L/m2, and considered fully scalable within experimental errors. Finally, fouling studies were performed using Chlorella sorokiniana and the USD device to investigate the impact of media type and growth conditions on the filtration performance. The results indicated a strong correlation between soluble fouling species, such as exopolysaccharides and carbohydrates, rather than the algal biomass. A novel, dynamic flux control methodology was developed based on empirically determined critical fluxes expressed as a function of cell concentration. The dynamic control strategy was successfully verified by performing a 50-fold concentration experiment using a hollow fibre module and the USD device. An improvement of greater than 50% in average throughput was achieved using the 3-step flux cascade compared to the traditional flux-time/capacity optimised fluxes, with no observable increase in TMP throughout. The work presented here demonstrates the potential of ultra scale-down tools coupled with a mathematical modelling approach to establish a predictable scale-up performance, which can be used to rapidly develop and optimise tangential flow filtration processes, regardless of differences in geometry, flow configuration and system setup.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available