The invention discloses an intelligent polypeptide synthesis
process optimization method, equipment and a medium. The method comprises the following steps: 1, loading and preprocessing experimental data of polypeptide synthesis; 2, generating all experimental condition combinations according to experimental data to form a reaction space; 3, converting experimental data into vectorization features; 4, training a
Gaussian process regression model based on vectorization features; 5, predicting a potential result corresponding to each group of experimental condition combination in the reaction space according to the
Gaussian process regression model; candidate experiment parameters of the next round of experiment are screened out from the potential results according to a
Bayesian optimization algorithm; 6, the candidate experiment parameters are applied to an actual experiment, a
verification experiment is executed through a
microreactor synthesis
verification platform, and an experiment result is obtained; and 7, feeding back an experimental result to the
Gaussian process regression model, updating
model parameters, repeating the steps 5-7 for optimization until an experimental target is met, and outputting an optimal experimental result. According to the invention, efficient optimization of the polypeptide synthesis process can be realized.