Conventional biologics manufacturing facilities are typically constructed with a fixed capacity and emphasis on batch operations to produce a single drug product. Strict regulatory requirements pertaining to the production of pharmaceuticals is one of the challenges facing modernization of bioprocessing facilities and adoption of Quality-by-Design (QbD) manufacturing practices. Furthermore, the industry is faced with restructuring its facilities to quickly respond to market forces while continuing to manufacture medications that also meet high quality safety and efficacy criteria. One of the technological solutions available to the biopharmaceutical industry is adoption of continuous biomanufacturing (CbM) alongside integrated process analytics. However, adoption of CbM by industry has moved along slowly. The primary reasons are scarcity of analytics for forecasting bioprocesses, challenges with integrating different unit operations, and issues with product quality control that don't adhere to regulations. It is also difficult, time-consuming, and labor-intensive to implement QbD to comprehend how complex process inputs affect drug critical quality attributes (CQAs). As a result, validation and deployment of integrated process analytical technology (PAT) tools is crucial for enabling in-process controls during CbM processes.
Protein glycosylation is a crucial CQA that must be managed during the upstream mAb synthesis process since it has been shown to affect in vivo drug efficacy. Nearly all significant CQAs, including glycosylation, can be monitored using offline ultra-high-performance liquid chromatography (U/HPLC) based separations in conjunction with UV absorbance, fluorescence, or mass spectrometry (MS) based detectors. Furthermore, there is strong interest to develop complementary in-line Raman spectroscopy-based PAT, calibrated using LC based approaches, for deployment in actual CbM mAb production campaigns. Therefore, in order to facilitate CbM, our team has collaborated with multiple industry partners to establish a fully integrated online PAT system for autonomous mAb CQA analysis. our recent work has shown that it is possible to convert conventional offline techniques with extensive sample preparation (e.g., mAb N-glycosylation analysis) into an automated online PAT platform called the NGLYcanyzer. However, there is a need for further development of this work.
The team will continue development of similar PAT automation approaches for integrated sampling from continuous upstream bench scale to production-scale bioprocesses followed by automated N-glycosylation analysis (among several other CQA) in near real-time. Antibody glycosylation and titer are representative CQAs, alongside several cell culture metabolites (e.g., amino acids), that will be monitored concurrently using an upgraded NGLYcanyzer protocol, and the workflow will be extended to enable its application in diverse process development modalities spanning from 2 mL microscale perfusion to 2 kL larger-scale standard fed-batch and perfusion bioreactor setups. Further, the team intends to generate robust Raman spectroscopy-based chemometric models, for prediction of mAb glycoforms (and other CHO cell culture metabolites), that will be integrated in-line to our PAT workflows. This would enable automated online analysis of multiple CQA to be performed continuously during cell culture, leading to a massive increase in process knowledge.
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Rutgers, The State University of New Jersey
Agilent
Endress + Hauser Optical Analysis
Enzene Biosciences Limited
MilliporeSigma/EMD Serono
Pfizer, Inc.
