Raman spectroscopy as an alternative rapid microbial bioburden test method for continuous, automated detection of contamination in biopharmaceutical drug substance manufacturing.

The article focuses on the development and validation of an in-line Raman spectroscopy method combined with orthogonal partial least squares discriminant analysis (OPLS-DA) for real-time detection of microbial contamination (bioburden) in pharmaceutical bioreactors producing monoclonal antibodies. This automated, non-destructive approach was tested in reduced-scale and production-scale bioreactors intentionally spiked with various microorganisms and demonstrated high specificity (0.99), sensitivity (0.95), and area under the curve (AUC) of 0.96, outperforming traditional offline compendial plate count methods in time to detection (TTD). The Raman method continuously monitors metabolic and biochemical changes associated with contamination, enabling earlier detection without manual sampling, and met acceptance criteria for decision equivalence to conventional methods. Future work aims to expand model robustness across different cell lines, organisms, and manufacturing scales to further support its application as a viable alternative for in-process bioburden testing in biopharmaceutical manufacturing.