Multi-million EPSRC funding for KCL DRIVE-Health CDT
March 13, 2024
DRIVE-Health has been awarded £7.9 million from The Engineering & Physical Sciences Research Council (EPSRC) for student intake from 2024 onwards. DRIVE-Health is one of 65 CDTs which received funding, totalling more than £1 billion.
Using seed funding from King’s Centre for Doctoral Studies awarded in 2020, DRIVE-Health has trained 30 students to date. Building on this, the new award will support five additional cohorts at King’s, totalling at least 85 talented PhD students. The CDT is expecting to welcome its fourth intake of at least 15 students in October 2024.
DRIVE-Health is the first health data science training centre in the UK to harness cross-sector collaboration across the NHS, industry, enterprise, policy makers, and academia. Working with diverse partners, DRIVE-Health PhD students develop cutting-edge models which leverage healthcare data to improve patient outcomes, streamline operations, and enhance clinical decision-making processes.
EPSRC CDT DRIVE-Health’s vision is informed by three core goals:
- To provide world-class training in health data science research to the next generation of health data scientists, who will have the multidisciplinary skills needed to enable transformations in public health and breakthrough treatments.
- To solve the most challenging problems in data-driven health research through a diverse community of the brightest minds in health data science and an open, collaborative culture which fosters exchange and champions innovation.
- To co-create a translational cross-sector collaboration with the NHS, industry, enterprise, policy makers and academia.
Professor Richard Dobson, Co-Director of DRIVE-Health and Professor of Medical Informatics at King’s IoPPN, says
"As more data from biological, social, genomic, imaging, smart devices, and electronic health records becomes available, there are significant opportunities to revolutionise the way healthcare is delivered. Through DRIVE-Health, we will train some of the brightest minds in health data science to develop cutting-edge tools which utilise data to improve healthcare systems and patient outcomes."
"This is an exciting time for medicine, with new data paradigms creating a novel research and implementation landscape covering the full span from cell to society. Over the next nine years, DRIVE-Health will nurture world-class researchers that will chart that landscape and drive the UK’s health data agenda." Professor Vasa Curcin, Co-Director of DRIVE-Health and Professor of Health Informatics at King’s FoLSM.
The DRIVE-Health PhD Programme (2024-2032) focuses on five key scientific research themes:
- Sustainable health data systems engineering: Investigates methods to develop secure and scalable software systems for healthcare. Theme lead: Dr Zina Ibrahim.
- Multimodal patient data streams: Integrates diverse patient data types for analysis, including wearables and electronic health records. Theme lead: Dr Jorge Cardoso.
- Complex simulations and digital twins: Builds simulated environments to train AI models for healthcare applications. Theme lead: Dr Steffen Zschaler.
- Next-generation clinical user interfaces: Ensures healthcare data science applications are usable in clinical settings. Theme lead: Professor Nick Holliman.
- Co-designing impactful patient-centric healthcare solutions: Co-producing and co-designing healthcare solutions to maximise impact across all themes. Theme lead: Professor Claire Steves.
On top of the £7.9m provided by the EPSRC, DRIVE-Health has received over £5.1m from partners, as well as in-kind contributions worth nearly £4m.
Share
We’re pleased to announce that Dr Petroula Laiou from King's College London , will deliver our May Seminar Series with her talk, "Bridging the Gap: Turning Academic Research into Clinical Innovation " . Petroula will share her journey of translating cutting-edge academic research into a mission-driven MedTech company. The spinout is pioneering a novel approach to forecasting and preventing seizures in people with drug-resistant epilepsy - an innovation rooted in years of interdisciplinary work at the intersection of clinical neuroscience, signal processing, and artificial intelligence. Dr. Laiou will take the audience through the full translational pathway: from identifying an unmet clinical need, designing and analysing first-in-human studies, and developing a seizure prediction algorithm, to securing translational funding, navigating the intellectual property landscape, and filing an international patent (PCT/GB2024/052456). She will reflect on key lessons learned during her time in the King’s MedTech Accelerator Programme - where the team won the Best Innovation award - and share insights on building bridges between academia and industry, shaping a commercialization strategy, and transitioning from researcher to entrepreneur. The talk will also highlight the challenges and rewards of launching a spinout in the healthcare sector and offer practical advice for PhD students and early-career researchers considering the entrepreneurial route. Seminar Series Event: "Bridging the Gap: Turning Academic Research into Clinical Innovation" Date and Time: Wednesday 7 May 2025, 15:00 – 16.00 hrs (BST) Location: The Lorna Wing Room, SGDP Building, Denmark Hill Campus, London, SE5 8AF Attendance: Mandatory for all DRIVE-Health students, therefore please accept the calendar invitation. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend. Dr. Petroula Laiou is a Research Fellow in Predictive Modelling and Clinical Neuroscience at King’s College London. With a background in mathematics, computational physics, and a PhD in signal analysis, her research bridges computer science, neuroscience, and machine learning. Her work focuses on developing predictive models and digital biomarkers for neurological and psychiatric disorders, including epilepsy and depression. Dr. Laiou led the development of a novel seizure forecasting algorithm using intracranial EEG and cortical responses to electrical stimulation—research that led to the filing of an international patent (PCT/GB2024/052456). She is the recipient of multiple research grants, including an MRC award as Principal Investigator, and her translational work was recognised by the King’s MedTech Accelerator Programme, where her team won the Best Innovation award. She has authored over 40 peer-reviewed publications, presented at major international conferences, and actively contributes to interdisciplinary collaborations across academia, hospitals, and industry.
We were thrilled to welcome Charles Friedman from the University of Michigan Medical School , who delivered our March Seminar Series with his talk, "Why AI and Learning Health Systems Need Each Other " . Charles began by advancing the idea that, while both are extremely important: AI is a means and Learning Health Systems (LHS) are an end--and why it is most important to maintain that distinction. He introduced the socio-technical infrastructure required for high-functioning learning systems and argue that this infrastructure provides a framework, actually a schematic, for successfully implementing AI into healthcare. Charles Friedman is Professor of Learning Health Sciences at the University of Michigan Medical School, where he directs the Knowledge Systems Laboratory. He was formerly Founding Chair of the Department of Learning Health Sciences and the Josiah Macy Jr. Professor of Medical Education. He holds joint appointments in the Schools of information and Public Health. He is editor-in-chief of the open-access journal Learning Health Systems and co-chair of the multi-national movement to Mobilize Computable Biomedical Knowledge. Throughout his career, Friedman has developed and studied methods to improve health, education, and research through innovative applications of information technology. Most recently, Friedman has focused his academic interests and activities on the concept of Learning Health Systems that improve health by marrying discovery to implementation, and the socio-technical infrastructure required to sustain these systems. Friedman is a Distinguished Fellow of the American College of Medical Informatics, and a founding fellow of the International Academy of Health Sciences Informatics. He holds an honorary doctorate from the University of Lucerne in Switzerland for his contributions to the science of Learning Health Systems. Prior to coming to Michigan, Friedman held executive positions at the Office of the National Coordinator for Health IT (ONC) in the U.S. Department of Health and Human Services. Immediately prior to his work in the government, he was Associate Vice Chancellor for Biomedical Informatics, and Founding Director of the Center for Biomedical Informatics at the University of Pittsburgh. Seminar Series Event: "Why AI and Learning Health Systems Need Each Other" Date and Time: Wednesday 26 March 2025, 10:00 – 11.00 hrs (BST) Location: The Anatomy Museum, King's Building, Room K6.36, Strand Campus, Strand, London, WC2R 2LS Attendance: Mandatory for all DRIVE-Health students, therefore please accept the calendar invitation. Registration: Alumni and wider King's College London research community all welcome - please email drive-health-cdt@kcl.ac.uk to let us know if you would like to attend.
