A METHOD OF PREDICTING A PERFORMANCE CHARACTERISTIC OF A PLANT OR YEAST HYDROLYSATE AND ITS USE

摘要

The present invention relates to a method of predicting a performance characteristic of a plant or yeast hydrolysate, wherein a plant or yeast hydrolysate sample is measured with 2D fluorescence spectroscopy in powder form. Said method comprises the steps for providing a model based on a predetermined value of a manufacturing parameter of interest. For this purpose a training set consisting of predetermined manufacturing parameter of interest (e.g volumetric productivity parameter, virus titer or cell number) and fluorescence spectroscopic data is used. The fluorescence spectroscopic data is correlated to the values of the manufacturing parameter of interest to obtain a calibration model/model parameters by applying multivariate data analysis. This calibration model is being used to predict the manufacturing parameter of interest for new samples dedicated for the manufacturing process. This prediction is used for a decision to accept or reject the lot which corresponds to the respective sample for use in the manufacturing process or for further evaluation depending on the pre-defined range of the manufacturing parameter of interest. The invention further relates to a method for preparation of a cell culture medium, preferably an animal protein free cell culture medium, a method for cultivating cells, a method for producing a recombinant target protein, a method for producing an immunogenic composition, whereby the above method of predicting a performance characteristic has been used for selecting the plant or yeast hydrolysate to be used in the manufacturing process.

主权项

1. Method of predicting a performance characteristic of a plant or yeast hydrolysate measured in powder form comprising the steps of:
a) providing a training set comprising a plurality of plant or yeast hydrolysate samples, each sample having a predetermined value of a manufacturing parameter of interest, b) irradiating a sample of said training set with light of a plurality of wavelengths in a predetermined range, c) determining at least one measured value indicative of radiation emitted from the sample, d) repeating steps b) and c) for all samples of said training set, e) performing multivariate data analysis of the at least one measured value determined for each of the plurality of samples and corresponding predetermined manufacturing parameters of interest to obtain model parameters correlating the at least one measured value determined for each of the plurality of samples with the corresponding predetermined manufacturing parameters of interest, f) obtaining information correlated to the manufacturing parameter of interest of a new sample different from the samples of said training set from an at least one measured value indicative of radiation emitted from the sample according to step c) after irradiating said sample according to step b) by using those model parameters obtained in step e), g) obtaining predictive information related to the performance characteristic of the new sample by determining whether said manufacturing parameter of interest falls into a predetermined range.