In silico design of integrated chromatographic purification processes for therapeutic proteins

Vecchiarello, Nicholas, Anthony
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Karande, Pankaj
Wayne, Bequette
Bennett, Kristin
Love, J Christopher
Cramer, Steven, M
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Chemical engineering
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This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute (RPI), Troy, NY. Copyright of original work retained by author.
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Designing non-affinity downstream processes for biologics poses a significant challenge due to the broad range of design space available for resin selection and buffer conditions. Imposing the design constraint of integrated manufacturing can help to prune this space and improve efficiency at the cost of markedly increasing the complexity during process design. To address this challenge, we developed an in silico-based approach to quickly design and rank a fully inclusive list of integrated downstream processes for their ability to remove impurities using only orthogonally selective multimodal and ion exchange resins. This approach involves the one-time characterization of an impurity database and considers both impurity profiles patterns and product retention behavior to generate and score all possible integrated purification trains. This database was then employed in concert with an in silico process development tool which generates and ranks all possible integrated chromatographic sequences for their ability to remove orthogonal impurities. Top-ranking outputs are then used to guide the experimental development and refinement of purification processes, significantly expediting the development of downstream processes. This approach represents a platformable strategy for rapidly designing purification processes for non-platform molecules. In this work, impurities found in null cell culture fluids were characterized on sets of multimodal, HCIC, and ion exchange resins using fast, high-resolution UPLC assays. This strategy was employed to generate one-time process-related impurity databases for both Pichia pastoris and CHO cell cultures; two industrially relevant cell lines with very different HCP burdens and properties. To demonstrate the effectiveness and versatility of this approach, the in silico tool was tasked with solving purification challenges in both of these systems. For Pichia pastoris, two non-mAb products, hGH and G-CSF, were successfully purified from cell culture fluid resulting in high purity and product recovery. In order to extend the utility of this in silico tool, we performed modifications to our process design approach in order to account for both process-related impurities and product-related impurities. This modified strategy was first shown to be successful for purifying IFN produced in Pichia pastoris, and was then applied to the non-affinity-based purification of a mAb-aggregate challenge in CHO, an expression system with a much higher HCP burden. Although this in silico tool is effective at identifying successful purification processes for specific products, we hypothesized the existence of a small set of optimally orthogonal resins which could be successful for purifying most protein products. As a result, using the concepts and lessons learned from this process development work, we wanted to gain a deeper insight into the nature of orthogonal selectivity and identify resin sets which operate orthogonally in a product-agnostic manner. The extent of an orthogonal separation in preparative chromatography is a concept that many practicing chromatographers intuitively and heuristically understand yet cannot easily quantify. In particular, the extent of orthogonality in multimodal separations can be particularly challenging to intuitively predict due to the complexity and synergy of different modes of interactions. To understand and quantifying these nonintuitive orthogonality trends, we developed a novel mathematical framework to characterize and quantify orthogonality in multimodal systems. Using this, we observed several interesting and unexpected results including the existence of a highly orthogonal pair of resins belonging to the same class/family. Taken together with the in silico tool, the work presented in this thesis is not only instrumental for use in improving the efficiency of process development, but can also have significant utility for the design of next-generation multimodal ligands.
School of Engineering
Dept. of Chemical and Biological Engineering
Rensselaer Polytechnic Institute, Troy, NY
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