BioDT: An Integrated Digital-Twin-Based Framework for Intelligent Biomanufacturing

Abstract

The field of industrial biotechnology has shown an increasing interest in adopting digital twins for improving process productivity and management efficiency. Despite its potential benefits, digital-twin-based biomanufacturing has not been fully implemented. As a preliminary undertaking, we developed an open-source digital twin framework for cell culture. The core models of the digital twin were coded in C++ and compiled as a reusable Python library. A web-based, cloud-native HMI application that links the physical and virtual systems was developed. A microbioreactor digital twin system was implemented using the framework as a proof of concept. The system features a 3D-printed rocking platform that is customized to fit T25 flasks, enabling automated rocking rate and angle control and in-place optical cell density measurement. The digital twin was validated using Chinese Hamster Ovary (CHO) cells and was found to be able to predict the changes in cell density, glucose consumption, lactic acid production, and oxygen uptake rate (OUR). Finally, we performed a case study to demonstrate the system’s practical applicability in Advanced Process Control (APC) by constructing real-time glucose and lactic acid soft sensors, which are in turn used to alert the operator for manual media change or for automated feeding.