(742d) Raman Spectroscopy- Towards the Prediction of Quality Attributes and Application in Cell Culture Process Development
Raman spectroscopy is mainly used for monitoring purposes at production stage, where variations are small and the process is already well defined. However, the exploitation of Raman technology for process development, where different process conditions, media, products or cell lines are tested resulting in a large variability and few experiments at similar conditions, could bring very important benefits, in terms of process understanding, speed and cost reduction. This work presents several ideas, experimental results and recommendations to overcome those challenges in process development.
Different fed-batch cultures, varying in cell lines, products and platform media, were monitored online. In addition, diverse spiking strategies were performed to artificially increase the calibration range as well as the quality of the prediction models. The evaluation of advanced modeling techniques to derive optimal results from the obtained spectral data plays a central role in this work. Those techniques included an in-depth analysis of the pretreatment procedure, wavelength selection and outlier elimination with regards to robust calibration and prediction of the components of interest.
Besides classical parameters such as glucose, lactate, titer and viable cell density, all 20 amino acids could be very well predicted. More than that, even the prediction of quality attributes like aggregates and glycans showed promising results. In addition, the potential of generic models, which can be applied independently of the cell line, process platform and medium, could be proven. This enables the Raman spectroscopy as an online monitoring tool of multiple process variables and its implementation into a supervisory control of a continuous integrated bioprocess to ensure consistent process efficiency and shaping the product qualities.