(130g) Towards Online Control of Protein Glycosylation: Establishing Nutrient Setpoint Control in Bioreactors

Monoclonal antibodies (MAbs), proteins that exhibit high specificity for a target antigen, are used therapeutically in oncology, organ transplantation, inflammatory disease, etc. With more than 200 in development pipelines, MAbs have become the fastest growing sector of the biopharmaceutical industry. As with other manufactured products, MAbs are effective only when their product quality attributes (bioactivity, potency, purity, etc.) lie within a specific range of values. Of the many factors that affect the quality and bioactivity of MAbs, arguably the most important is glycosylation, a post-translational modification in which a carbohydrate chain, termed a glycan, is added to a protein. MAbs validated for use as human therapeutics have precise glycosylation patterns that must be accurately replicated for the MAb to function as intended in vivo. However, unlike other cellular processes such as DNA replication and protein production, glycosylation has no master template; as a result, glycan formation and attachment are subject to variability and are often non-uniform. Furthermore, with current technology, glycosylation patterns can only be determined post-production, and if a batch fails to meet the quality benchmarks for glycosylation patterns, the entire lot must be discarded due to regulatory concerns. The major challenges that manufacturers face in meeting the stringent quality criteria requirements, and the necessity to guarantee the safety and effectiveness of all pharmaceutical products, has prompted the US Food and Drug Administration (FDA) to recommend strongly that manufacturers demonstrate the ability to ensure product quality on-line during production. To date, no such techniques exist for on-line quality control in MAb manufacturing. Our goal is to develop?and validate experimentally?a comprehensive strategy for effective on-line, real-time control of glycosylation patterns, using a combination of multi-scale modeling, hierarchical control, and state estimation. The first phase of the project requires successful establishment of base regulatory control for the key process variables known to affect glycosylation, such as glucose and glutamine media concentrations, reactor temperature, dissolved oxygen (DO), pH, and agitation rate. A typical bioreactor has precise control of temperature, DO, pH, and agitation rate; however, nutrient control and metabolite monitoring is not common place. Through the development of a novel bioreactor system equipped with an OPC interface, feedback control algorithms were implemented to maintain glucose and glutamine media concentrations at desired setpoints. This presentation will focus on the development of various feedback control algorithms for these nutrients. Preliminary results on the bioreactor system's ability to maintain desired nutrient setpoints will be presented along with a discussion of the challenges associated with nutrient control such as data filtering, batch-to-batch variability, sampling limitations, and inherent process nonlinearity.