[P002] Poster

1:00 PM - 1:50 PM JST(4:00 AM - 4:50 AM UTC)

[P01-146] An Advanced Bioprocess Platform Enabling Data Integration, Model Execution, and Process Automation

○Hiroaki YAMANAKA¹, Souichirou SHIMODA¹, Ayaka SUETSUNA¹ (1. Yokogawa Electric Corporation (Japan))

Keywords:

Digitalization,Automation,Data Integration,Bioprocess Control

Bioprocess operations still rely heavily on manual tasks, including daily operation and data collection from diverse analytical and process instruments. These manual procedures increase the risk of human error and limit the practical adoption of AI based predictive control due to fragmented and insufficient data availability. To address these challenges, Yokogawa has developed BioPilot, an advanced bioprocess platform that enables automated data integration, model application, and flexible process automation across the entire bioprocess workflow. BioPilot integrates real time data acquisition, centralized monitoring, and workflow automation based on Yokogawa’s extensive experience in industrial automation. The platform provides a customizable monitoring interface, an integrated dashboard for real time and historical trend visualization, and a visual editor for designing automated process flows. As a representative use case, glucose concentration control was implemented using Raman spectroscopy, where measured data were transmitted via the OPC UA protocol and used for automated feed control. The results demonstrate that BioPilot successfully consolidates heterogeneous equipment and data streams into a single platform, enabling seamless data integration and real time process visibility. Automated glucose control achieved stable concentration maintenance without manual intervention. In addition, integrated data transfer to models enabled concurrent model execution and intervention analysis using both real time and historical data. These results indicate that automated data integration and workflow orchestration significantly reduce manual workload and human error while improving data availability for model based control. By lowering the barrier to implementing predictive models and automation strategies, BioPilot supports faster experimentation, improved reproducibility, and scalable deployment in bioprocess development and manufacturing environments. In conclusion, BioPilot provides an end to end bioprocess platform that integrates data acquisition, model application, and automation. By enabling data driven and predictive bioprocess operations, BioPilot accelerates bioprocess development and unlocks new possibilities in biomanufacturing.