Abstract: A method for monitoring and/or controlling a biopharmaceutical process includes querying, based on a first spectral scan vector of the biopharmaceutical process, an observation database comprising observation data sets associated with past scans. Each of the observation data sets includes spectral data and a corresponding actual analytical measurement. Querying the observation database includes determining first parameters defining a set of distributions for the first spectral scan vector, and selecting as training data, from among the observation data sets, particular observation data sets based on (i) the first parameters and (ii) other parameters defining respective sets of distributions for the observation data sets. The method also includes calibrating, using the selected training data, a local model specific to the biopharmaceutical process.

Abstract: A method of controlling a cell culture process uses hybrid predictive modeling in a model predictive controller. The method includes, for multiple time intervals, obtaining current values of cell culture attributes associated, and generating a control value for a physical input to the cell culture process. Generating the control value includes predicting future values of the cell culture attributes based on the current values, by using one or more data-driven models to predict future values of a first one or more attributes of the cell culture attributes, and using one or more first principle models to predict future values of a second one or more attributes of the cell culture attributes. Generating the control value also includes determining the control value by optimizing an objective function subject to the predicted future values. The method also includes using the control value to control the physical input to the cell culture process.