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EPSRC Centre for Doctoral Training in Data-Driven Healthcare (DRIVE-Health)

Lead Research Organisation: King's College London
Department Name: Bioinformatics

Abstract

DRIVE-Health will train a minimum of 85 PhD health data scientists and engineers with the skills to deliver data-driven, personalised, sustainable healthcare for 2027 and beyond. Co-created with the NHS Trusts, healthcare providers, patients, healthtech, pharma, charities and health data stakeholders in the UK and internationally, it will build on the successes of its King's College London seed-funded and industry-leveraged pilot. Led by an established team, further growing the network of funding partners and collaborators built over the past four years, it will leverage an additional £1.45 of investment from King's and partners for every £1 invested by EPSRC.

A CDT in data driven health is needed to deliver the EPSRC Priority for Transforming Health and Healthcare, EPSRC Health Technologies Strategy, and on challenges laid out in the UK Government's 2022 Plan for Digital Health and Social Care envisaging lifelong, joined-up health and care records, digitally-supported diagnoses and therapies, increasing access to NHS services through digital channels, and scaling up digital health self-help. This ambition is made possible by the increasing availability of real-world routine healthcare data (e.g. electronic health care record, prescriptions, scans) and non-healthcare sources (e.g. environmental, retail, insurance, consumer wearable devices) and the extraordinary advances in computational power and methods required to process it, which includes significant innovations in health informatics, data capture and curation, knowledge representation, machine learning and analytics.

However, for these technological and data advances to deliver their full potential, we need to think imaginatively about how to re-engineer the processes, systems, and organisations that currently underpin the delivery of healthcare. We need to address challenges including transformation of the quality, speed and scale of multidisciplinary collaborations, and trusted systems that will facilitate adoption by people. This will require a new generation of scientists and engineers who combine technical knowledge with an understanding of how to design effective solutions and how to work with patients and professionals to deliver transformational change.

DRIVE-Health's unique cohort-based doctoral research and training ecosystem, embedded across partner organisations, will equip students with specialist skills in five scientific themes co-produced with our partners and current students:

(T1) Sustainable Healthcare Data Systems Engineering investigates methods and frameworks for developing scalable, integrated and secure data-driven software systems
(T2) Multimodal Patient Data Streams will enable the vision of a highly heterogeneous data environment where device data from wearables, patient-generated content and structured/unstructured information from electronic health records can combine seamlessly
(T3) Complex Simulations and Digital Twins focuses on the paradigm of building simulated environments, including healthcare settings or virtual patients, to make step-change advances in individual predictive models and to inform clinical and organisational decision-making.
(T4) Trusted Next-Generation Clinical User Interfaces will place usability front and centre to ensure health data science applications are usable in clinical settings and are aligned with users' workflows
(T5) Co-designing Impactful Healthcare Solutions, is a cross-cutting theme that ensures co-production and co-design in the context of health data science, engagement with stakeholders, evaluation techniques and achieving maximum impact.

The theme training will be complemented with a cohort and programme-wide approach to personal, career, professional and leadership development. Students will be trained by an expert pool of 60+ supervisors from KCL and across partners, delivering outstanding supervision, student mentoring, opportunities, research quality and impact.

Organisations

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/Y035216/1 31/03/2024 29/09/2032
2927110 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Akshit Achara
2927813 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Tomas Solomon
2927752 Studentship EP/Y035216/1 30/09/2024 29/09/2028 ABED MOSA AL REFAEE
2927802 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Olivia Dann
2927784 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Saif Latifi
2927791 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Idris Matine
2927739 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Linda Bryant
2927888 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Yusuf Abdulle
2927866 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Ziyuan Cai
2927773 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Emily Gillings
2927837 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Aleksandra Korbacz
2927607 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Narges Matinazad
2927216 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Binh Vu
2927884 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Kamara Israel-McLeish
2927823 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Patrick Campbell
2947144 Studentship EP/Y035216/1 30/09/2024 29/09/2028 Mehmet Avci
2939755 Studentship EP/Y035216/1 01/02/2025 31/01/2029 Renato Dos Santos
2939612 Studentship EP/Y035216/1 01/02/2025 31/01/2029 Niko Moeller-Grell