🔬 Creating accurate calibration models for Raman-based monitoring is challenging and time-consuming.
🧪 Scientists developed orthogonal projection to latent structures (OPLS) models to predict production and culture indicators.
📊 The models accurately predicted glucose and lactate levels across different clones, but had issues with predicting titer levels.
✨ A generic calibration model can be used for glucose and lactate levels, but not for product prediction.
🔬 Raman spectroscopy is useful for monitoring cell cultures, but creating calibration models is still time-consuming.
Introduction:
Raman spectroscopy is increasingly being used as an in-line tool for monitoring cell cultures in biopharmaceutical production. However, creating reliable and accurate calibration models for Raman-based monitoring is a challenging and time-consuming task. This article explores the impact of clonal variations on the development of Raman calibration models and the potential for creating generic calibration models.
- Raman spectroscopy is gaining popularity as an in-line tool for monitoring cell cultures in biopharmaceutical production.
- Creating reliable and accurate calibration models for Raman-based monitoring is a difficult and time-consuming task.
- A study investigated the impact of clonal variations on the development of Raman calibration models.
- The study found that while generic models can predict levels of glucose and lactate, specific clone influences the modeling of expected product titer.
- To overcome limitations, titer calibration models should be developed using a generic calibration modeling approach.
Conclusion:
Raman spectroscopy can be utilized for in-line monitoring of cell cultures in biopharmaceutical production, but creating calibration models to predict product titer still requires specific clone information. The development of generic calibration models is an area of future research to improve the efficiency of Raman-based monitoring.
