Computational modelling for understanding mechanisms of Alzheimer's disease progression

1) Brief description of the context of the research including potential impact
Alzheimer's disease (AD) is the leading cause of dementia, which is one of the biggest challenges of modern medicine and healthcare. Many hundreds of clinical trials over decades have produced zero disease-modifying interventions/drugs!
Data-driven computational methods have emerged in the wake of the increasing availability of large clinical and neuroimaging datasets. The models themselves provide new utility and key insights into disease, including fine-grained patient assessment (and clinical trial recruitment!) and improved understanding of disease mechanisms.

2) Aims and Objectives
The overarching objective of this project is to produce a quantum leap in the understanding of the biological mechanisms of Alzheimer's disease progression.
The project aims are: a) build computational "supermodels" of disease progression that produce state of the art predictive and diagnostic accuracy for clinical trials and healthcare; and b) build mechanistic models that explain the underlying biological mechanisms of Alzheimer's disease progression for informing drug development.

3) Novelty of Research Methodology
Project objectives will be achieved by bringing together, for the first time: data-driven image-based modelling and large clinical/neuroimaging datasets; data originating from mouse models of Alzheimer's; and translational data including high-resolution imaging readouts of brain cell function and Alzheimer's pathology, as well as outputs from ultrasensitive assays for blood-based biomarkers. This is a unique combination of computer science, clinical neurology, and neuroscience.

4) Alignment to EPSRC's strategies and research areas
This project aligns with the Healthcare Technologies Theme, touching on two Grand Challenges: Optimising Treatment and Developing Future Therapies. Within this theme, this project aligns with the following Research Areas: Artificial intelligence technologies, Clinical technologies (excluding imaging), Mathematical Biology, Medical imaging.
Understanding Alzheimer's Disease is a high priority global healthcare challenge, and this multidisciplinary project aligns with all EPSRC's strategies, but particularly with Accelerating Impact.

5) Any companies or collaborators involved
None at the moment beyond the corresponding supervisors.

The critical mass of scientists and engineers that i4health will produce will ensure the UK's continued standing as a world-leader in medical imaging and healthcare technology research. In addition to continued academic excellence, they will further support a future culture of industry and entrepreneurship in healthcare technologies driven by highly trained engineers with deep understanding of the key factors involved in delivering effective translatable and marketable technology. They will achieve this through high quality engineering and imaging science, a broad view of other relevant technological areas, the ability to pinpoint clinical gaps and needs, consideration of clinical user requirements, and patient considerations. Our graduates will provide the drive, determination and enthusiasm to build future UK industry in this vital area via start-ups and spin-outs adding to the burgeoning community of healthcare-related SMEs in London and the rest of the UK. The training in entrepreneurship, coupled with the vibrant environment we are developing for this topic via unique linkage of Engineering and Medicine at UCL, is specifically designed to foster such outcomes. These same innovative leaders will bolster the UK's presence in medical multinationals - pharmaceutical companies, scanner manufacturers, etc. - and ensure the UK's competitiveness as a location for future R&D and medical engineering. They will also provide an invaluable source of expertise for the future NHS and other healthcare-delivery services enabling rapid translation and uptake of the latest imaging and healthcare technologies at the clinical front line. The ultimate impact will be on people and patients, both in the UK and internationally, who will benefit from the increased knowledge of health and disease, as well as better treatment and healthcare management provided by the future technologies our trainees will produce.

In addition to impact in healthcare research, development, and capability, the CDT will have major impact on the students we will attract and train. We will provide our talented cohorts of students with the skills required to lead academic research in this area, to lead industrial development and to make a significant impact as advocates of the science and engineering of their discipline. The i4health CDT's combination of the highest academic standards of research with excellent in-depth training in core skills will mean that our cohorts of students will be in great demand placing them in a powerful position to sculpt their own careers, have major impact within our discipline, while influencing the international mindset and direction. Strong evidence demonstrates this in our existing cohorts of students through high levels of conference podium talks in the most prestigious venues in our field, conference prizes, high impact publications in both engineering, clinical, and general science journals, as well as post-PhD fellowships and career progression. The content and training innovations we propose in i4health will ensure this continues and expands over the next decade.