Advancing continuous biomanufacturing of monoclonal antibodies using an experimentally validated modeling platform

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Project Summary Due to increased demand for biologics, there is an ongoing need to scientifically and commercially advance manufacturing in both upstream cell culture and downstream purification steps. Our goal is to provide an experimental infrastructure complemented by a computational framework to investigate the continuous manufacturing of monoclonal antibodies (mAbs). The modeling approach will be based and validated using specific experimental evidence to enhance our process understanding and improve model performance and utilization during the design phase. The proposed innovations stem from the following objectives that will be delivered as the outcome of this project, namely, 1) To develop a multiscale model for perfusion bioreactor capturing the effects of operating parameters and cell line characteristics on critical quality attributes (CQAs) validated by experimental results; 2) To develop methods for optimizing continuous chromatographic operations, including primary capture and polishing steps, under a range of process conditions for optimal clearance of process- and product-related impurities; and 3) To develop predictive models that will enable determination of optimal operating conditions with direct coupling of upstream and downstream units accounting for product quality attributes. To enable process control, which is the ultimate target of advanced manufacturing, we will explore the design space and identify the relationships between critical process parameters (CPPs), critical material attributes (CMAs), and targeted CQAs. We will develop predictive models for all the important unit operations, validated by experiments, that can be used to determine the design space along with statistical analysis of experimental data to identify all critical parameters/attributes. The validated models will then be used as a virtual tool to perform risk assessment for in-plant downstream operations such as scale-up/start-up/shutdown and compare process operating scenarios. In terms of combining the developed strategies, we envision the integration with a continuous upstream facility to achieve a fully automated continuous biomanufacturing line exploring and optimizing the process interactions. This proof-of-concept line will be used to clearly quantify risk and performance-based metrics.