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Optimizing mAb Production with Deep Learning by mostafa is a document available to read on EtoBox.

This study introduces a deep learning method utilizing a hybrid CNN-LSTM architecture to optimize monoclonal antibody (mAb) production processes, achieving significant improvements in titer and productivity. The model was validated with industry data, outperforming traditional statistical and machine learning methods, and identified key parameters such as temperature and pH as critical for production. The research highlights the potential of deep learning in enhancing bioprocess efficiency while addressing

Author

mostafa

Language

EN