van der Schaar Lab

van der Schaar Lab collaborations recognized with major NHS award

A pair of collaborations between the van der Schaar Lab and researchers from leading academic, medical, and private-sector organizations have been awarded funding in the second round of the NHS AI Lab’s Artificial Intelligence in Health and Care Award.

The winning projects from the most recent round of the AI Award were named in a joint announcement on June 16 by NHSX, the Accelerated Access Collaborative (AAC), and the National Institute for Health Research (NIHR).

Both projects are firmly rooted in real-world healthcare problems, and pair the work of globally renowned biomedical researchers with the van der Schaar lab’s wealth of experience in creating cutting-edge models that provide reliable decision support and actionable intelligence.

Details of the award-winning projects are shared briefly below.

Advance notice of deterioration in cystic fibrosis

Accurately predicting how an individual’s chronic illness is going to progress is critical to delivering better-personalized, precision medicine. Only with such insight can a clinician and patient plan optimal treatment strategies for intervention and mitigation. Yet there is an enormous challenge in accurately predicting clinical trajectories for chronic health conditions such as cystic fibrosis.

The purpose of this project is to use AI with home monitoring to predict sudden dips in the health of adults with cystic fibrosis before they begin to feel unwell, enabling early intervention and helping patients stay well without repeated hospital check-ups. The project is being run as a partnership between the University of Cambridge (Cambridge Centre for AI in Medicine and Department of Medicine), the Royal Papworth Hospital NHS Foundation Trust, Microsoft Research, Magic Bullet and cystic fibrosis centers in Glasgow, Edinburgh and Cardiff. A full announcement has been published on the website of the Cambridge Centre for AI in Medicine.

More information regarding our lab’s research projects related to cystic fibrosis can be found here.

AI systems for improving blood transfusion outcomes

The aim of this collaboration is to develop, improve, and implement AI systems for genetic blood group typing, the automated stocking of blood according to type, and the precision matching of patients to blood units. These new systems could transform the quality and efficiency of blood matching, reduce complications of blood transfusions, and improve clinical care for patients.

This project is a partnership between the van der Schaar Lab and Professor Emanuele Di Angelantonio from the NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Dr William Astle NHSBT, Senior Lecturer in Statistical Science in the MRC Biostatistics Unit, and their collaborators at UCLH, Oxford University and international blood services.

Further details are available on the website of the Cambridge Biomedical Research Centre.

Led by NHSX, the Artificial Intelligence in Health and Care Award is one of the NHS AI Lab’s programs. The competitive award scheme is run by the Accelerated Access Collaborative (AAC) in partnership with the National Institute for Health Research (NIHR). The AI Award is making £140 million available over four years to accelerate the testing and evaluation of artificial intelligence technologies which meet the aims set out in the NHS Long Term Plan.

A list of all winners from the first two rounds of the AI Award has been made public here.

Nick Maxfield

Nick oversees the van der Schaar Lab’s communications, including media relations, content creation, and maintenance of the lab’s online presence.

Nick studied Japanese (BA Hons.) at the University of Oxford, graduating in 2012. Nick previously worked in HQ communications roles at Toyota (2013-2016) and Nissan (2016-2020).

Given his humanities/languages background and experience in communications, Nick is well-positioned to highlight and explain the real-world impact of research that can often be quite esoteric. Thankfully, he is comfortable asking almost endless questions in order to understand a topic.