The concept of design space has been taking root as a foundation of in-process control strategies for biopharmaceutical manufacturing processes. During mapping of the process design space, the multidimensional combination of operational variables is studied to quantify the impact on process performance in terms of productivity and product quality. An efficient methodology to map the design space for a monoclonal antibody cell culture process is described. A failure modes and effects analysis (FMEA) was used as the basis for the process characterization exercise. This was followed by an integrated study of the inoculum stage of the process which includes progressive shake flask and seed bioreactor steps. The operating conditions for the seed bioreactor were studied in an integrated fashion with the production bioreactor using a two stage design of experiments (DOE) methodology to enable optimization of operating conditions. A two level Resolution IV design was followed by a central composite design (CCD). These experiments enabled identification of the edge of failure and classification of the operational parameters as non-key, key or critical. In addition, the models generated from the data provide further insight into balancing productivity of the cell culture process with product quality considerations. Finally, process and product-related impurity clearance was evaluated by studies linking the upstream process with downstream purification. Production bioreactor parameters that directly influence antibody charge variants and glycosylation in CHO systems were identified.
Residual host cell protein impurities (HCPs) are a key component of biopharmaceutical process related impurities. These impurities need to be effectively cleared through chromatographic steps in the downstream purification process to produce safe and efficacious protein biopharmaceuticals. A variety of strategies to demonstrate robust host cell protein clearance using scale-down studies are highlighted and compared. A common strategy is the "spiking" approach, which is widely employed in clearance studies for well-defined impurities. For HCPs this approach involves spiking cell culture harvest, which is rich in host cell proteins, into the load material for all chromatographic steps to assess their clearance ability. However, for studying HCP clearance, this approach suffers from the significant disadvantage that the vast majority of host cell protein impurities in a cell culture harvest sample are not relevant for a chromatographic step that is downstream of the capture step in the process. Two alternative strategies are presented here to study HCP clearance such that relevance of those species for a given chromatographic step is taken into consideration. These include a "bypass" strategy, which assumes that some of the load material for a chromatographic step bypasses that step and makes it into the load for the subsequent step. The second is a "worst-case" strategy, which utilizes information obtained from process characterization studies. This involves operating steps at a combination of their operating parameters within operating ranges that yield the poorest clearance of HCPs over that step. The eluate from the worst case run is carried forward to the next chromatographic step to assess its ability to clear HCPs. Both the bypass and worst-case approaches offer significant advantages over the spiking approach with respect to process relevance of the HCP impurity species being studied. A combination of these small-scale validation approaches with large-scale HCP clearance data from clinical manufacturing and manufacturing consistency runs is used to demonstrate robust HCP clearance for the downstream purification process of an Fc fusion protein. The demonstration of robust HCP clearance through this comprehensive strategy can potentially be used to eliminate the need for routine analytical testing or for establishing acceptance criteria for these impurities as well as to demonstrate robust operation of the entire downstream purification process.
The concept of design space has been taking root under the quality by design paradigm as a foundation of in-process control strategies for biopharmaceutical manufacturing processes. This paper outlines the development of a design space for a hydrophobic interaction chromatography (HIC) process step. The design space included the impact of raw material lot-to-lot variability and variations in the feed stream from cell culture. A failure modes and effects analysis was employed as the basis for the process characterization exercise. During mapping of the process design space, the multi-dimensional combination of operational variables were studied to quantify the impact on process performance in terms of yield and product quality. Variability in resin hydrophobicity was found to have a significant influence on step yield and high-molecular weight aggregate clearance through the HIC step. A robust operating window was identified for this process step that enabled a higher step yield while ensuring acceptable product quality.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.