Lecture
Bridging the Bioprocess Visibility Gap with Raman Chemometrics for Real Time PAT
- at -
- B2.137
- Type: Lecture
Lecture description
Bioprocess decisions are often delayed by days because many critical measurements still rely on offline sampling and laboratory assays. This session presents a practical workflow that combines Raman spectroscopy with chemometric and machine learning models to provide real-time, non-invasive estimates of key process and product quality indicators during mammalian cell culture. The end-to-end approach covers spectral acquisition, automated scan quality assessment, preprocessing, model development, validation against reference methods, and real-time inference suitable for at-line or in-line use. We highlight how integrating these capabilities with standardized interfaces, such as SiLA-compliant digital laboratory systems, enables seamless data exchange between instruments, analytical software, and control systems. Key translation challenges—including matrix effects, drift, calibration transfer, and uncertainty reporting—are discussed, illustrating how laboratories can move from offline testing to actionable, real-time decision support aligned with PAT/QbD principles. Attendees will gain a clear understanding of both the technical and operational steps required to bridge the bioprocess visibility gap in modern, connected labs.
