Ensemble Kalman Filter for estimation of intracellular nucleotide sugars from extracellular metabolites in monoclonal antibodies

Abstract

The emergence of Quality by Design (QbD) and Process Analytical Technology (PAT) paradigm supported by the FDA imposes a strong motivation for digital transformation in biopharmaceutical industry. The inherent complexity of bioprocess dynamics, batch-to-batch variability resulting from raw materials and process operations, as well as the need for accelerating product manufacturing, makes dynamic soft sensors such as Kalman Filters highly desirable for process development, monitoring, and control. In this work, we develop an Ensemble Kalman Filter framework in the context of monoclonal antibody bioprocessing, where the noise on physical sensors is mitigated for extracellular metabolite states by integrating the process’ dynamic mechanistic model and sensor measurements. More importantly, the framework accurately estimates the nucleotide sugar concentrations, an intracellular state of the cell that is not routinely measured in industry due to experimental complexity. The proposed EnKF soft sensor retrieves this knowledge through state inference, providing valuable insights for monitoring and control of key quality attributes such as glycan distribution.

Dr. Ehecatl Antonio del Rio Chanona

Principal Investigator of OptiML

Antonio del Rio Chanona is the head of the Optimisation and Machine Learning for Process Systems Engineering group based in thee Department of Chemical Engineering, as well as the Centre for Process Systems Engineering at Imperial College London. His work is at the forefront of integrating advanced computer algorithms from optimization, machine learning, and reinforcement learning into engineering systems, with a particular focus on bioprocess control, optimization, and scale-up. Dr. del Rio Chanona earned his PhD from the Department of Chemical Engineering and Biotechnology at the University of Cambridge, where his outstanding research earned him the prestigious Danckwerts-Pergamon award for the best PhD dissertation of 2017. He completed his undergraduate studies at the National Autonomous University of Mexico (UNAM), which laid the foundation for his expertise in engineering.