Abstract: The present invention relates to a method and system for predicting performance of biopharmaceutical manufacturing processes by measuring a parameter of the biopharmaceutical manufacturing process at a predetermined sampling frequency, wherein said parameter is measured for n number of runs of said process, sequentially joining the parameter data of the n number of runs in a single continuous time-series manner, to generate a transformed data, training a time series analysis model for forecasting performance of the biopharmaceutical manufacturing process, based on a plurality of transformed data generated corresponding to a plurality of parameters, measuring the plurality of parameters at a predetermined timepoint, and using said measurement to reinforce and improve the trained time series analysis model, and predicting the plurality of parameters for a future run of the biopharmaceutical manufacturing process, based on the trained time series analysis model.

Abstract: The invention relates to the analysis of carbohydrates, such as N-glycans and O-glycans found on proteins. The invention relates, in part, to glycan labeling with formulas/compounds enhancing their detection and/or analysis by methods such as capillary electrophoresis, liquid chromatography and mass spectrometry. These detection methods may be useful in studying glycosylation patterns of biological or medical samples, or for assessing protein production, protein quality/purity, for comparing innovator and biosimilar glycosylated proteins, or for selecting proteins with the desired glycosylation.