Pioneering Just-in-Time (JIT) Strategy for Accelerating Raman Method Development and Implementation for Biologic Continuous Manufacturing.
Hanzhou FengZachary D DunnRoli KarguptaJay DesaiChelsea PhuangthongTayi VenkataEmmanuel Appiah-AmponsahBhumit A PatelPublished in: Analytical chemistry (2024)
Raman spectroscopy is a popular process analytical technology (PAT) tool that has been increasingly used to monitor and control the monoclonal antibody (mAb) manufacturing process. Although it allows the characterization of a variety of quality attributes by developing chemometric models, a large quantity of representative data is required, and hence, the model development process can be time-consuming. In recent years, the pharmaceutical industry has been expediting new drug development in order to achieve faster delivery of life-changing drugs to patients. The shortened development timelines have impacted the Raman application, as less time is allowed for data collection. To address this problem, an innovative Just-in-Time (JIT) strategy is proposed with the goal of reducing the time needed for Raman model development and ensuring its implementation. To demonstrate its capabilities, a proof-of-concept study was performed by applying the JIT strategy to a biologic continuous process for producing monoclonal antibody products. Raman spectroscopy and online two-dimensional liquid chromatography (2D-LC) were integrated as a PAT analyzer system. Raman models of antibody titer and aggregate percentage were calibrated by chemometric modeling in real-time. The models were also updated in real-time using new data collected during process monitoring. Initial Raman models with adequate performance were established using data collected from two lab-scale cell culture batches and subsequently updated using one scale-up batch. The JIT strategy is capable of accelerating Raman method development to monitor and guide the expedited biologics process development.
Keyphrases
- raman spectroscopy
- monoclonal antibody
- healthcare
- rheumatoid arthritis
- liquid chromatography
- electronic health record
- end stage renal disease
- chronic kidney disease
- mass spectrometry
- big data
- social media
- quality improvement
- label free
- deep learning
- cross sectional
- health information
- simultaneous determination
- peritoneal dialysis