Applying computer vision, machine learning and data analytics in the LumiMan system to maximise productivity and resource efficiency in sustainable medicines manufacturing.
A pair of smart glasses now watches every step of medicine production, flagging mistakes as they happen. Medicines manufacturing relies on complex, multi-step processes where human error and overlooked inconsistencies cause costly delays and wasted materials. Existing digital tools like electronic lab notebooks capture only part of the workflow, leaving critical transitions—especially from research to full-scale production—unmonitored. This project extends an existing visual intelligence platform, Lumi, by integrating wearable devices such as LabEye smart glasses to automate real-time data capture across all production stages. The system uses computer vision and machine learning to track liquid levels, reaction phases, and equipment interactions, providing instant feedback to reduce errors. If successful, Lumi could transform pharmaceutical manufacturing from a manually monitored, error-prone process into a continuously automated, data-driven one. The project also develops reaction simulation technology to cut the number of experimental steps needed to design production protocols. A partner will test the system in oligonucleotide manufacturing, a critical step for RNA-based therapies. Faster, more reliable production means life-saving medicines could reach patients sooner, while reducing waste and improving resource efficiency in a sector where even small improvements have large economic and health impacts.
View original technical description
Medicines manufacturing involves complex processes that are often hindered by inefficiencies and human errors, leading to wasted time, resources, and increased costs. Traditional systems, such as electronic lab notebooks (ELNs) and laboratory information management systems (LIMS), do not fully capture or automate key steps in these processes, especially during the transition from research to large-scale production. As a result, errors and inconsistencies go unnoticed, causing delays and failures in manufacturing. Lumi, developed by Reach Industries, is a groundbreaking visual intelligence platform that combines artificial intelligence, computer vision, and advanced data analytics to revolutionize laboratory and manufacturing workflows. Lumi captures real-time data from laboratory environments, automating the observation of critical steps such as liquid levels, reaction phases, and equipment interactions. It provides instant feedback and insights, allowing scientists and engineers to optimize their processes and reduce errors. In this project, we are expanding Lumi's capabilities by integrating wearable devices, such as LabEye smart glasses, to further automate data capture across medicine manufacturing facilities. This will allow for hands-free monitoring, data integration, and error-proof compliance tracking across all stages of production. We will also develop innovative AI and machine learning capabilities to allow Lumi to power full automation of disparate steps in productuin processes. Our partner, CatSci, will develop novel reaction simulation technology to reduce the number of steps needed to develop protocols to produce medicines. They will deploy Lumi in their pilot facility to demonstrate its effectiveness in oligonucleotide manufacturing, a critical step in producing new RNA-based therapies. Lumi's innovation will increase productivity, reduce waste, and improve resource efficiency in medicines manufacturing, ultimately contributing to faster delivery of life-saving medicines to patients. This project aims to set new standards for automation, sustainability, and accuracy in pharmaceutical manufacturing.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know