Cambridge University Hospitals NHS Foundation Trust has welcomed the launch of the Zenith supercomputer funded by the Department for Science, Industry and Technology.
Said to offer researchers the ability to study health data on an “unprecedented scale”, the supercomputer will also support and inform the development of AI tools for patient care across the NHS.
The AI Centre for Value-Based Healthcare is reportedly collaborating with Zenith on the project to help ensure the supercomputer’s power is deployed “responsibly and securely”.
Sarah Burge, CUH director of clinical integration, referred to the launch as a “significant step-up” in efforts to improve healthcare using AI. “In Cambridge, we will have the computing speed and power needed to make AI relevant to care at the scale of the NHS,” Burge said. “It can help us to learn from the lived experiences of millions of patients to improve detection, diagnosis and treatment for the future. It won’t just shape how we treat patients but will help inform how we plan and deliver care.”
With the addition of Zenith, supercomputing power in Cambridge has increased sixfold, according to CUH. The new supercomputer replaces the previous model, DAWN, that was responsible for supporting more than 350 research projects under the national AI research resource.
“The future Cambridge Cancer Research Hospital is being designed from the ground up with innovations like this in mind and will provide the ideal environment for the real-time translation of such AI discoveries into patient care,” CUH states.
Wider trend: Health AI
For a recent HTN Now session focusing on AI in healthcare, HTN was joined by an expert panel including Simon Brown, head of digital at Royal Papworth Hospital NHS Foundation Trust; Wahida Jabarzai, clinical AI and automation delivery lead at University Hospitals of Northamptonshire (UHN) and University Hospitals of Leicester (UHL); and Julian Wiggins, healthcare solution director at Rackspace Technology. Our panel considered the wider challenge of AI adoption, looking at what makes a successful deployment, introducing AI safely and sustainably at scale, and some of the use cases currently delivering value across their organisations.
The MHRA has published findings from the National Commission into the Regulation of AI in Healthcare research, pointing to the need to balance a desire to use AI in improving patient care and supporting healthcare professionals, with “safe, fast and trusted” regulation. A call for evidence ran from December 2025 to February 2026, receiving a total of 761 responses. This posed questions around required changes to the current regulatory framework, monitoring of AI products in healthcare, liability and responsibility. Almost three-quarters of respondents (73 percent) disagreed or strongly disagreed that the current regulatory framework is sufficient to ensure safety and performance standards; with 61 percent disagreed or strongly disagreed with its effectiveness in tackling data governance and data privacy. 61 percent also thought current requirements for clinical evidence are insufficient, and 65 percent pointed to a need for more to be done on post-market surveillance.
The Medicines and Healthcare products Regulatory Agency has announced plans to launch a regulatory AI sandbox with the aim to explore how artificial intelligence can support medicines development and safety. The sandbox, funded by the Regulatory Innovation Office, will enable AI tools to be tested that have the potential to predict how medicines will be absorbed, processed, or whether they may cause harm. The sandbox will also be used to inform the MHRA about the reliability of whether AI tools can support in deciding the safety of new medicines.
