CPI joins Canada-UK collaboration developing AI-powered bioreactors to revolutionise biopharmaceutical manufacturing

The AI-optimised BALANCE (Bioreactor Automation for Learning and Adaptive Networked Control of Experiments) platform will leverage CPI’s bioreactor technologies, Nicoya’s real-time sensing and control systems, integrated with automation from Labman Automation, and AI development by Basetwo to make bioprocessing smarter, more efficient, and faster.

The 20-month collaboration, led by Labman, is supported by a $2 million grant from Innovate UK and the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP) through a Canada-UK Collaborative R&D initiative. The goal of the project is to deliver an AI-optimised demonstrator platform integrating bioreactor technologies with real-time sensing and control systems. It will leverage the joint expertise of the partners, bringing together the latest in AI, automation, and real-time process control to streamline upstream bioprocessing, ensuring higher yields, lower costs, and improved scalability for next-generation therapeutics. This aims to enhance the precision and efficiency of biologic drug production, offering a smarter, faster path to market.

Bioprocessing is an often-inefficient part of manufacturing that can slow down biopharma development. Optimising bioprocessing requires making bioreactor operation more dynamic, relying on real-time data from biosensors. At the core of the BALANCE initiative is a closed-loop AI control system powered by Basetwo’s digital twin platform. The machine learning models will interpret real-time data from the bioreactor and biosensors, enabling adaptive control of experimental conditions for real-time optimisation of bioreactor performance. Labman will build an automated modular sampling platform that will automate molecular analysis, integrating seamlessly with Nicoya’s Alto SPR biosensor for instant yield data and adaptive process control.

Basetwo’s digital twin technology further enhances efficiency by predicting quality outcomes and reducing reliance on costly lab testing. CPI will validate and benchmark the system, ensuring practical scalability and commercial viability for biologics manufacturing.

This project marks a major step forward in digital bioprocessing, paving the way for increased efficiency, reduced variability, and faster time-to-market for breakthrough biologics. As an AI-driven testbed for next-generation model-based process control, the platform holds transformative potential for pharma and biotech industries striving for scalable, cost-effective production solutions.

Brendan Fish, Director of Biologics at CPI, said:

“Pharmaceutical companies know they must embrace digitalisation to stay competitive, but integrating digital technologies has been challenging in an industry that can be slow to evolve. Through collaboration, BALANCE is bridging this gap by validating and scaling AI-driven bioprocessing solutions to accelerate adoption and translate advancements into real-world impact for biologics manufacturing.”

Ryan Denomme, co-founder and CEO of Nicoya, said:

“Until now, sensing technology has been too slow and complex to enable truly reactive bioprocessing. Label-free biosensing is critical to unlocking the potential for automation and AI to drive efficiency in biomanufacturing, overcoming the complexity inherent in systems dealing with the diversity of living organisms. We look forward to working with our BALANCE partners to solve a bottleneck that can accelerate drug development.”

Thomas Smith, Head of Bioprocess Automation at Labman, said:

“This is the next step for biologics and drug manufacturing, integrating Industry 4.0 approaches for bioprocessing. By combining advanced sensing, AI and automation, we aim to accelerate process development, improve consistency, and create smarter, more efficient biomanufacturing workflows.”

Thouheed Abdul Gaffoor, CEO at Basetwo, said:

“AI-enabled digital twins is the next frontier in intelligent manufacturing. By combining our hybrid modelling approach with advanced sensing and automation, this collaboration moves us closer to autonomous biomanufacturing, cutting time, cost, and variability in producing life-saving therapeutics.”