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Lennard Lee, NDM, Oxford University
Led from the Centre for Immuno-Oncology within Oxford’s Nuffield Department of Medicine, the AI Cancer Scientist project addresses a long-standing challenge in cancer research – that translating complex immunology into viable vaccine candidates is slow, fragmented, and difficult to scale. Developing effective cancer vaccines can take 10-15 years, in part because hypothesis generation, experimental testing, and data analysis are often separated across different teams, tools, and timeframes.
The AI Cancer Scientist aims to test whether running these steps together as a single, continuous process can accelerate progress. For the first time in cancer research, the project will seek to bring together AI models of tumour-immune recognition, automated laboratory experimentation, and sovereign UK AI supercomputing into one integrated discovery platform.
At the centre of the planned system are automated research pods. These are designed to support AI systems that generate vaccine hypotheses, design and run immune-function experiments using laboratory automation, analyse results, and iteratively refine cancer vaccine targets and formulations at scale. By integrating modelling, experimentation, and computation into a closed loop, the team will assess whether AI Scientist approaches can deliver a step change in the speed and efficiency of translating cancer immunology into patient-ready vaccine candidates.
Read the full story on the Nuffield Department of Medicine website.