Earticle

초록

영어

Heterogeneity and complexity of the glycosylation on biotherapeutics greatly depend on expression system, process conditions, and environment of cell culture of products. In order to evaluate biosimilarity of antibody drug such as Herceptin®, Remicade®, and Remsima®, we have developed a deep learning model, Deep Y, using intact glycoprotein analysis by LC-MS. Briefly, each antibody drug was independently analyzed to identify its intact glycoprotein composition. As a result, the list of identified intact glycoprotein compositions from each MS data was merged in the intact glycoprotein database, where a total of 34 intact glycoprotein compositions was identified from all three antibody drugs. Independently, the deconvoluted masses and their abundances of antibody drugs generated by Mass Hunter were used as data sets such as training, validation, and test set, for development of a deep learning model using convolutional and fully connected neural network. The accuracy was 100%, 90% and 85% at training, validation and test set, respectively, where the experiments of more than 100 ng/ml were predicted as 100% of accuracy at test set. The DeepY could predict the biosimilarity and distinguish the low quality of mass spectra from all antibody drugs. We will further test the antibody drugs in batch to batch, expand to other original antibody drugs and their biosimilars.

저자

• Heeyoun Hwangl [ Asia-Pacific Glycomics Reference Site, Chungnam National University, Dae.ieon, Korea; Graduate School of Analytical Science and Technology, Chungnam National University, Dae.ieon, Korea; ]
• Unyong Kim [ Glycan Co. Ltd., Sungnam, Korea ]
• Young Suk Seol [ Asia-Pacific Glycomics Reference Site, Chungnam National University, Dae.ieon, Korea; Graduate School of Analytical Science and Technology, Chungnam National University, Dae.ieon, Korea; ]
• Myung Jin Oh [ Asia-Pacific Glycomics Reference Site, Chungnam National University, Dae.ieon, Korea; Graduate School of Analytical Science and Technology, Chungnam National University, Dae.ieon, Korea; ]
• Hyun Joo An [ Asia-Pacific Glycomics Reference Site, Chungnam National University, Dae.ieon, Korea; Graduate School of Analytical Science and Technology, Chungnam National University, Dae.ieon, Korea; ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국당과학회 학술대회

• 간기

  연간

• 수록기간

  2006~2022

• 십진분류

  KDC 517 DDC 614