DiMeN XL Research themes
DiMeN‑XL brings together institutional strengths and external partners to enhance the training landscape and accelerate the translation of research into health and societal benefits.
The programme is structured around three disease-focussed discovery themes addressing major health challenges across the life-course, alongside a cross-cutting training theme designed to build essential quantitative and computational skills. Themes align with MRC priorities and new UKRI priority buckets
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Theme 1. Multifactorial diseases associated with health inequity
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Theme 2. Infection, Immunity and Inflammation
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Theme 3. Translation of discovery science to advanced therapies and healthTech innovation
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Theme 4 (crosscutting). Quantitative and computational biology, incorporating machine learning and advanced imaging technologies.
Theme 1: Multifactorial diseases associated with health inequity.
Conditions such as cancer, neurodegeneration, musculoskeletal disorders and mental health represent major regional and global challenges due to their complex interplay of genetic, environmental and lifestyle factors. Understanding these interactions is essential for developing targeted prevention strategies, personalized treatments, and effective public health interventions. Projects addressing these conditions to improve long-term health outcomes and mitigate the societal and economic impact of chronic disease are welcomed in this theme
Theme 2: Infection, Immunity and Inflammation.
Infection, immunity and inflammation research is fundamental to safeguarding public health and are a keystone to a broad range of diseases and thus for biomedical research. Projects to understand immune mechanisms in disease and to develop innovative vaccines, diagnostics and therapeutic strategies for infectious and non-infectious diseases are welcomed in this theme. This research also strengthens epidemic preparedness and resilience, ensuring rapid and effective responses to emerging threats
Theme 3: Translation of discovery science to advanced therapies and healthTech innovations.
Translating discovery science into advanced therapeutics and healthTech innovations is critical for accelerating patient focused solutions and driving regional economic growth. Projects around rapid development of cutting-edge diagnostics, vaccines, therapeutics and digital health technologies that convert breakthroughs into real-world impact are supported through this theme.
Theme 4: Quantitative and computational biology, incorporating machine learning and advanced imaging technologies.
This is a crosscutting training theme so projects aligning to this theme should also align with one of the first three themes. The scope of this theme includes technologies to enable large-scale dataset integration and analysis; methods to drive advances in disease mechanisms and therapeutic development; and the application of Artificial Intelligence, machine learning and cutting-edge imaging approaches for diagnostic precision, drug design, predictive modelling, virtual screening and the translation of early‑stage discoveries into clinical applications. The theme also aligns closely with the UKRI artificial intelligence research and innovation strategic framework.