NIR-spectroscopy for bioprocess monitoring & control

Introduction The Quality by Design (QbD) approach shows significant benefit in classical pharmaceutical industry and is now on the cusp to a stronger influence on biopharmaceutical applications. Monitoring the critical process parameters (CPP) applying process analytical technologies (PAT) during biotechnological cell cultivations is of high importance in order to maintain a high efficiency and quality of a bioprocess. For parameters like glucose concentration, total cell count (TCC) or viability a robust online prediction is in many applications not yet possible. This gap can be closed with the help of NIR spectroscopy (NIRS), which provides quantitative prediction of single analytes in real-time. For accurate process control based on NIR spectroscopy, special care has to be taken while building the calibration model [1,2]. In cell cultivation almost all analytes are confounded and show large correlation coefficients. Therefore, partial least square (PLS) models are not able to discriminate between the signals of the different analytes. Especially, analytes like glucose or glutamine which are strongly confounded with cell growth need to be evaluated carefully as cell growth is the analyte causing the largest changes in NIR spectra throughout a cultivation run. Spiking experiments are the most efficient way in order to break correlations between critical analytes like glucose and other nutrients or TCC. This strategy should be followed in order to build robust calibration models without correlations [3,4]. Another very critical issue occurring in cell cultivation are batch-to-batch variations. As it is recommended in good modeling practice [5], for robust models it is crucial to use several complete batches for validation which are not part of the calibration set rather than cross validation [6].