Multi-scale design and optimization of antibody production via flexible nets

Area of Science:

• Biotechnology
• Bioprocess Engineering
• Computational Biology

Background:

• Therapeutic antibodies are crucial in medicine, with Chinese Hamster Ovary (CHO) cells being the primary production system.
• Current antibody production relies on inefficient, costly "trial and error" methods for CHO cell manipulation.
• Optimization of antibody manufacturing processes is essential for cost-effectiveness and performance.

Purpose of the Study:

• To develop mathematical models for the systematic and automatic design of antibody production systems.
• To accelerate and enhance the optimization of antibody manufacturing processes.
• To achieve optimal productivity in antibody production through advanced modeling.

Main Methods:

• Development of mathematical models based on Flexible Nets (FNs) formalism.
• FNs accommodate uncertain parameters and nonlinear dynamics for comprehensive modeling.
• Integration of CHO cell metabolic networks with bioreactor dynamics in a multi-scale model.

Main Results:

• The developed mathematical models enable a systematic approach to antibody production system design.
• Flexible Nets (FNs) provide a framework for integrating intracellular and extracellular process variables.
• The multi-scale model facilitates global optimization of antibody manufacturing.

Conclusions:

• Mathematical modeling, specifically using Flexible Nets (FNs), offers a powerful approach to optimize antibody production.
• This systematic design methodology can overcome the limitations of traditional "trial and error" methods.
• The integrated multi-scale model paves the way for automated and highly productive biomanufacturing processes.