Real-time monitoring and model-based prediction of purity and quantity during a chromatographic capture of fibroblast growth factor 2.

Process analytical technology combines understanding and control of the process with real-time monitoring of critical quality and performance attributes. The goal is to ensure the quality of the final product. Currently, chromatographic processes in biopharmaceutical production are predominantly monitored with UV/Vis absorbance and a direct correlation with purity and quantity is limited. In this study, a chromatographic workstation was equipped with additional online sensors, such as multi-angle light scattering, refractive index, attenuated total reflection Fourier-transform infrared, and fluorescence spectroscopy. Models to predict quantity, host cell proteins (HCP), and double-stranded DNA (dsDNA) content simultaneously were developed and exemplified by a cation exchange capture step for fibroblast growth factor 2 expressed in Escherichia coliOnline data and corresponding offline data for product quantity and co-eluting impurities, such as dsDNA and HCP, were analyzed using boosted structured additive regression. Different sensor combinations were used to achieve the best prediction performance for each quality attribute. Quantity can be adequately predicted by applying a small predictor set of the typical chromatographic workstation sensor signals with a test error of 0.85 mg/ml (range in training data: 0.1-28 mg/ml). For HCP and dsDNA additional fluorescence and/or attenuated total reflection Fourier-transform infrared spectral information was important to achieve prediction errors of 200 (2-6579 ppm) and 340 ppm (8-3773 ppm), respectively.

Metabolomics of Pichia pastoris: impact of buffering conditions on the kinetics and nature of metabolite loss during quenching.

Mass spectrometry-based metabolomic profiling is a powerful strategy to quantify the concentrations of numerous primary metabolites in parallel. To avoid distortion of metabolite concentrations, quenching is applied to stop the cellular metabolism instantly. For yeasts, cold methanol quenching is accepted to be the most suitable method to stop metabolism, while keeping the cells intact for separation from the supernatant. During this treatment, metabolite loss may occur while the cells are suspended in the quenching solution. An experiment for measuring the time-dependent loss of selected primary metabolites in differently buffered quenching solutions was conducted to study pH and salt concentration-dependent effects. Molecular properties of the observed metabolites were correlated with the kinetics of loss to gain insight into the mechanisms of metabolite leakage. Size and charge-related properties play a major role in controlling metabolite loss. We found evidence that interaction with the cell wall is the main determinant to retain a molecule inside the cell. Besides suggesting an improved quenching protocol to keep loss at a minimum, we could establish a more general understanding of the process of metabolite loss during quenching, which will allow to predict optimal conditions for hitherto not analysed metabolites.