AI-Driven Process Analytical Technology for Real-Time Monitoring of iPSC Aggregate Growth in Bioreactors
Lead Organisation
Rosalind Franklin Institute; Sterling Bio Machines
Theme
The development of novel synthetic biology tools and technologies
Funding
SPARK Award
Project partners: Rosalind Franklin Institute & Sterling Bio Machines
Project focus area: The development of novel synthetic biology tools and technologies
This project developed an AI-powered image analysis system for automated, real-time quality monitoring of induced pluripotent stem cell (iPSC) cultures in bioreactors. Stem cell manufacturing currently relies on subjective manual microscopy to assess culture quality, often only once every 24 hours, which is a bottleneck to reproducible and scalable production of cell therapies. Working together, Sterling Bio Machines and the Rosalind Franklin Institute created a deep learning pipeline capable of three monitoring tasks: segmenting iPSC aggregates with over 99% accuracy, separating individual aggregates within dense clusters at 95% accuracy using a novel neural network architecture, and detecting necrotic cores as an early indicator of aggregate deterioration. The system was deployed as both an interactive browser-based tool and an automated API, containerised for consistent operation across different computing environments. The collaboration demonstrated that AI-based approaches substantially outperform traditional image processing for this application, providing quantitative, reproducible readouts not achievable through manual assessment. Following the success of this project, Sterling Biomachines have spun out Morphokinetics Ltd, a new company dedicated to intelligent Process Analytical Technology for stem cell manufacturing, ensuring the outputs of this grant continue toward commercial deployment and ultimately help reduce the cost of cell therapies for patients.
For more information
For more information on this project, contact us, or view all Engineering Biology SPARK Award winners.
This project funding is part of the Engineering Biology Innovation Network, led by Innovate UK Business Connect in collaboration with Innovate UK and UKRI’s Technology Mission Fund. The network’s goal is to progress innovations, create a commercially focused community and foster new consortia to advance innovations towards commercial applications.