Data-driven predictive modeling for cell line selection in biopharmaceutical production

A method for facilitating selection of a cell line, from among a plurality of candidate cell lines that produce recombinant proteins, the method comprising:

• measuring, using an opto-electronic cell line generation and analysis system comprising an analytical unit and a cell line generation and growth unit, a first plurality of attribute values for the plurality of candidate cell lines by performing a plurality of optical and assay measurements for the plurality of candidate cell lines, wherein performing the plurality of optical and assay measurements for the plurality of candidate cell lines includes measuring, using the analytical unit, at least cell counts and cell productivity scores at a plurality of physically isolated pens in the opto-electronic cell line generation and analysis system;
• generating, using the opto-electronic cell line generation and analysis system, cells of the plurality of candidate cell lines, at least by moving individual cells into different pens of the plurality of physically isolated pens with one or more photoconductors activated by light patterns, wherein the individual cells are maintained within their respective pens throughout a cell line generation and analysis process;
• acquiring, by one or more processors, a second plurality of attribute values for the plurality of candidate cell lines, wherein the second plurality of attribute values includes one or more attribute values measured at a cell pool screening stage of the plurality of candidate cell lines;
• determining, by one or more processors, a ranking of the plurality of candidate cell lines according to a product quality attribute associated with hypothetical small-scale screening cultures for the plurality of candidate cell lines, wherein determining the ranking includes (i) predicting, for each of the plurality of candidate cell lines, a value of the product quality attribute by analyzing the first plurality of attribute values and the second plurality of attribute values using a machine learning based regression estimator, and (ii) comparing the predicted values;
• and
• causing an indication of the ranking to be presented to a user via a user interface.