Cell Culture Glycosylation Multi-scale Data Driven Mechanistic Modeling (Phase 2)

Application of Next-generation Modeling of Glycosylation to Adaptive Process Control of CQAs in Fed-batch CHO Cell Culture

74% Completed

Industry Need

Laboratory experiments increase new product development cost. Special experiments for predictive model calibration reduces benefits of models.

Use Glycosylation modeling to reduce laboratory experimentation. Calibrate predictive model using AI/ML rather than experiments.

Modelling Software in Open-Source platform (2Q2024)
Model Use Training documentation (2Q2024)
Presentation – Model-based Design of Experiments for Glycosylation in CHO Cell Culture – 2023 AIChE Orlando, FL (Jing, Ma, Braatz (MIT))
Presentation – GlycoPy: A Multiscale Model-based Simulation, Optimization and Optimal Python Package for mAb Glycosylation in Cell Culture – 2023 AIChE Orlando, FL (Ma, Jing, Braatz (MIT))
Presentation – Model-based analysis of glycosylation across cell lines – 2023 BPI Boston, MA (Jing, Ma, Braatz (MIT))