Field, Nicholas John; (2018) Investigation of multicomponent adsorption isotherms in chromatography using high-throughput formats. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Adsorption isotherms in chromatography are critical in determining the separation of solutes during column separations. Multicomponent protein adsorption isotherms, which are relevant during the downstream processing of biopharmaceutical products, have received limited study historically. The studies and methodologies which have been assessed have mainly focused on small, simple, chromophore containing proteins which have limited applicability to industrially relevant bio-therapeutics. The reasons why this area of study has received limited attention include the experimental effort associated with generating such large data sets as well as the difficulty in obtaining data of good enough quality. The work explored here presents and optimises the deployment of highthroughput chromatography formats as well as automated liquid handling systems in order to elucidate adsorption isotherms of proteins. Additionally, alternative rapid analytical methods involving the collection of protein UV spectra in conjunction with multivariate data analysis have been applied to quantify protein mixtures. These rapid high-throughput methods decrease the experimental effort associated with multicomponent isotherm studies. 3 binary isotherms and 1 ternary isotherm have been studied for larger, non-chromophore containing model proteins. The propagation of error in single component and multicomponent isotherms has been investigated to understand what drives the propensity for error as well as methods to mitigate problematic regions of investigation. The fitting of the multicomponent ion exchange isotherms across multiple salt levels to isotherm formalisms proved elusive which precluded their application for in silico modelling of column separation. Short of that a heuristic optimisation of a binary mixture was achieved quantifying eluted fractions using the UV spectra multivariate method.

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