Culture medium formula development method and system based on transfer learning

Abstract

The invention discloses a culture medium formula development method and system based on transfer learning. The method comprises the following steps: (1) obtaining a culture medium pre-training model based on a deep neural network and a culture medium formula data set for training of cells to be developed; (2) pre-training model migration; and (3) carrying out regression prediction on a culture effect value: carrying out culture effect value prediction on a culture medium formula to be predicted by adopting the final model obtained in the step (2). According to the method, a small amount of training data is adopted to carry out migration training on the culture medium pre-training model, so that the training data volume required by development of a specific cell formula is greatly reduced, the development time of the culture medium formula is greatly shortened from 4-6 months to 1-2 months, and the development cost is remarkably reduced.

Description

technical field [0001] The invention belongs to the field of biotechnology, and more specifically relates to a method and system for developing a culture medium formula based on transfer learning. Background technique [0002] Serum-free, animal-free, and chemically defined medium is composed of carbon sources, amino acids, vitamins, trace metal ions, lipids, buffer reagents, and other additives. The traditional medium formula development method is to use one or several classic Based on culture medium (such as DEME / F12), by adding a variety of different components, using single factor test or DOE screening test to find key components, and then using multiple DOE experimental designs such as response surface to optimize the concentration of each component to Obtain the best formula; or optimize the formula by finding out the changes of each component during the cell growth process and the impact on the yield and quality of the target product based on cell metabolism analysis,...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a method and system for developing a culture medium formula based on transfer learning. For the pre-trained model obtained by training a large number of medium formulas, rapid migration training is carried out for specific cells, thereby reducing the amount of training data and AI system training time required for the development of the medium AI recommendation system, and quickly obtaining AI with good prediction accuracy Model, thus solving the problem that the existing culture medium development method requires a large number of culture experiments for specific cells, and solving the technical problems of high training costs, long development cycles, and unusable existing databases caused by the collection of sufficient training data for AI models

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