2023 FDA Science Forum
Advancing understanding of bioreactor and process parameter impacts on antibody product quality outcomes through the development of mass spectrometry-based process analytical technology
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Contributing OfficeCenter for Drug Evaluation and Research
Abstract
Bioprocessing is a complex process through which engineered cells are used as manufacturing plants for generating complex protein biotherapeutics. As living cells, changes in bioreactor conditions and process parameters can have unexpected impacts to their growth parameters and thus, product quality. To address this issue and maintain product quality through process optimization, we have worked with advances in rapid analytical methodologies to characterize bioreactor media parameters and product quality attributes (PQA) in speeds approaching real time. These process analytical technology (PAT) approaches have included complex on-line systems and streamlined at-line instrumentation. Here, we present our ongoing work on predominately mass spectrometry-based instrumentation used to assess bioreactor media metabolites and nutrients, as well as evaluate product quality attributes such as the glycosylation profile of monoclonal antibody (mAb) protein products in less than an hour. At-line instruments tend to be stand-alone “black box” modules with refined user interfaces and ease-of-use, but at high-cost and little user flexibility (i.e. the analytes/parameters that can be studied are predetermined and use expensive pre-packaged kits). On the other hand, current efforts in on-line systems are generally still early in developmental stages due to difficulties in interfacing equipment from different companies. These challenges include both physically connecting the equipment together and getting them to communicate to facilitate a complete analytical platform. Our group has worked with both at-line and on-line approaches, and understand their pros and cons. This will be described along with our continuing work in coupling bioreactor process parameters and product quality outcomes in mAb bioproduction using statistical approaches such as multi-variate data analysis (MVDA).
