Quantitative Analysis of Monoclonal Antibody Formulations Using Image and Fluorescence Correlation Spectroscopies

  • Maryam Shah

Student thesis: Phd


Biopharmaceuticals (e.g. monoclonal antibodies (mAbs)) must comply with regulations (i.e. United States Pharmacopeia (USP) ) regarding their characterisation and stability. mAbs contain hydrophilic and hydrophobic areas (the latter normally buried inside the bio-macromolecule). Stress conditions (such as high temperature, freezing, shaking etc.) or high concentrations may lead to the exposure of hydrophobic surfaces (i.e. following unfolding) and subsequently lead to the formation of protein aggregates. Furthermore, high concentrated mAb products (i.e. >100mg/ml) have the increased risk of intermolecular interactions which is correlated with high viscosity. These issues pose significant challenges to the economic manufacture of safe and effective protein therapeutics. Current technologies in characterising protein formulations possess limitations in regards to size ranges, specificity, interacting with solution components and concentration; thus there is a current drive in the development of novel applications. This thesis studies the application of two fluorescence-based techniques in characterising mAb solutions, in the context of downstream processing and formulation: Raster image correlation spectroscopy (RICS) analyses to assess aggregation propensity; and fluorescence correlation spectroscopy (FCS) in retrieving viscosity information. An important step for both methods is the identification of appropriate (non-covalent) fluorescent probes. To validate the application of RICS in charactering mAb aggregates in industrially relevant formulations, particle formation (size and counts) in pre-filled syringes was evaluated as a function of polysorbate-20 (PS-20) concentration, following agitation stress. PS-20 limited agitation-induced aggregation whilst increasing the amount of silicone oil sloughing. Thus no correlation between silicone oil and aggregation was observed. Following extrinsic labelling of aggregates by hydrophobic dye SYPRO Red, RICS demonstrated its high specificity to aggregates in mAb solutions containing surfactant and silicone oil. An improved selectivity was observed in comparison to resonance mass measurement (RMM) and micro-flow imaging (MFI), covering a broader size range and using small sample volumes. Although nonionic surfactants such as PS-20 are widely used, their mechanisms in mAb solutions are poorly understood. This is partly due to analytical limitations of current technologies. The application of FCS with utilising SYPRO Orange is validated in accurately determining the critical micelle concentration of (three) nonionic surfactants, along with the micelle size. Moreover, the FCS/SYPRO Orange application is used to detect polysorbate micelles in the presence of high concentration mAb and thus provides scope to assess micelle behaviour in highly concentrated mAb formulations. As an additional method to measure the microviscosity of mAb solutions, FCS was utilised in measuring the self-diffusion of tracers in a wide range of mAb formulations, over a broad concentration range. The diffusion of different sized tracers was investigated and compared against bulk rheometry measurements. It was established a probe of size equal or larger than the mAb gave relatable information to bulk rheometry. RICS and FCS were (sequentially) applied to mAb solutions subjected to various forms of agitation stress. A correlation was established between aggregation development (size and counts) and changes in solution viscosity. Additionally an inverse relationship of agitation-induced aggregation and protein concentration was observed. The potential of measuring aggregation propensity and solution viscosity using the same system set-up is of great interest to the industry due to small sample material and minimal operating time. Thus the combined application of RICS and FCS has the potential to stand as a tool in the characterisation of mAb (aggregate) solutions, particularly in relation to early formulation devel
Date of Award31 Dec 2018
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorRobin Curtis (Supervisor) & Alain Pluen (Supervisor)

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