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/Data-driven Predictive Modeling For Cell Line Selection In Biopharmaceutical Production
Abstract

A method for facilitating selection of cell lines to advance to a next stage of cell line screening includes receiving first attribute values for the candidate cell lines measured using an opto-electronic cell line generation and analysis system, and acquiring second attribute values that include one or more attribute values measured at a cell pool screening stage of the candidate cell lines. The method also includes determining a ranking of the candidate cell lines according to a product quality attribute associated with hypothetical small-scale screening cultures. Determining the ranking includes predicting, for each of the candidate cell lines, a value of the product quality attribute by analyzing the first and second plurality of attribute values using a machine learning based regression estimator, and comparing the predicted values. The method also includes causing an indication of the ranking to be presented to a user via a user interface.

Full Text

What is claimed is:

A method for facilitating selection of cell lines to advance to a next stage of cell line screening includes receiving first attribute values for the candidate cell lines measured using an opto-electronic cell line generation and analysis system, and acquiring second attribute values that include one or more attribute values measured at a cell pool screening stage of the candidate cell lines. The method also includes determining a ranking of the candidate cell lines according to a product quality attribute associated with hypothetical small-scale screening cultures. Determining the ranking includes predicting, for each of the candidate cell lines, a value of the product quality attribute by analyzing the first and second plurality of attribute values using a machine learning based regression estimator, and comparing the predicted values. The method also includes causing an indication of the ranking to be presented to a user via a user interface.
Timeline
Filed
03/05/2026
Published
07/09/2026
Granted
Not Available
IPC Codes(3)
C12M 1/00:Apparatus for enzymology or microbiology
C12M 1/36:including condition or time responsive control, e.g. automatically controlled fermentors
G16B 40/00:ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding