The Medical Research Council (MRC) supports research that advances understanding of human health and disease worldwide. We encourage the inclusion of a global perspective across our portfolio, through development of equitable international partnerships.
Research with a global perspective is an important part of MRC’s mission to improve human health through medical research, addressing shared health challenges and supporting international partnerships in a changing and interconnected world.
Our understanding of human disease is enhanced through discovery research that includes diverse populations and settings. This diversity strengthens mechanistic insights and supports early translational research that considers how interventions will work in different contexts.
As health challenges increasingly transcend borders, from epidemic threats to the growing global burden of non‑communicable disease, this evidence supports effective and contextually relevant responses worldwide. We welcome interdisciplinary applications that integrate diverse perspectives to address complex global health challenges.
We are looking to fund global health research grounded in equitable, mutually beneficial partnerships that reflect modern best practice in global collaboration. These partnerships should create reciprocal advantages for all parties involved through:
- shared leadership
- capacity strengthening
- knowledge
- perspectives
- innovation
Where projects involve partners in the global south, assessment will consider the extent to which equity and mutual benefit are demonstrated. Projects should show evidence of co-design, shared leadership and appropriate recognition of all partner contributions.
By encouraging these partnerships, we expect that individuals contributing to projects will experience clear positive benefits for their careers including opportunities for leadership, skills development, and meaningful participation in shaping research outcomes.
MRC’s commitments to global health research are underpinned by a longstanding partnership with the FCDO.
We support global health research spanning the entirety of MRC’s remit.
The following are examples of global science that we support.
Mechanistic understanding across the life course
Understanding how diseases arise, evolve and interact across the life course is essential to identifying new opportunities for prevention, diagnosis and treatment. Research across diverse populations and environments can reveal both universal biological mechanisms and context-specific drivers of health and disease. Example areas of focus include:
- disease mechanisms in context: Explaining how diseases arise, evolve and interact across the life course through the integration of biological, environmental and population-level data across diverse settings.
- exposome and One Health approaches: Investigating how environmental, ecological and cross-species influences affect human health and disease to provide mechanistic insight
- comparative and cross-context insight: Using variation across populations and settings to distinguish universal biological mechanisms from context-specific effects, helping to identify population relevant targets for intervention
Precision prevention and risk prediction
Preventing disease before it develops requires a better understanding of how risk emerges, accumulates and varies across populations and environments. Research in diverse settings can support more effective, targeted and equitable prevention strategies. Example areas of focus include:
- cumulative risk across the life course: Understanding how environmental exposures and biological processes interact across the life course to shape disease risk and inform prevention strategies
- causal pathways and prevention windows: Identifying causal pathways and critical windows for intervention to enable prevention before disease onset, including, biomarker development, risk prediction models as well as research to predict the drivers of outbreak emergence and transmission
- resilience and modification of risk: Understanding why some individuals and populations remain healthy under adverse conditions, providing insight into determinants of resilience and informing prevention strategies across different environments and populations
Earlier diagnosis and stratification
Earlier and more accurate diagnosis is critical for improving outcomes and enabling timely intervention. Research across diverse populations and healthcare environments helps ensure diagnostic approaches are effective in the settings where they are most needed. Example areas of focus include:
- diagnostics that perform across disease contexts: Developing biomarkers and diagnostic approaches that are robust to variation in biology, environment and disease stage, enabling earlier and more precise detection of disease across diverse populations and disease presentations.
- diagnostics for real-world conditions: Developing diagnostic technologies that function effectively across diverse healthcare settings, including point of care, molecular and digital technologies, and novel approaches for disease monitoring and risk stratification
Vaccines and therapeutics for global use
Considering biological diversity, patterns of disease and implementation requirements early in development can improve the relevance, scalability and impact of vaccines and therapeutics. Effective interventions should therefore be designed with global populations and settings in mind from the outset. Example areas of focus include:
- biologically informed interventions: Designing vaccines and therapeutic approaches that reflect biological diversity and global patterns of disease from the outset, including discovery immunology, human challenge models, precision pharmacology and drug repurposing
- advanced and scalable treatments: Designing advanced therapeutic approaches that reflect biological diversity and can be translated and deployed across diverse settings, with early consideration of formulation, delivery, stability and usability to maximise scalability and impact
Experimental medicine
Experimental medicine studies provide critical mechanistic insights into disease processes and intervention responses in humans. Conducting these studies in globally representative populations helps ensure findings are relevant, robust and translatable across diverse settings.
Data science and Artificial Intelligence (AI)
Data science and AI enable the integration, analysis and interpretation of complex, multimodal and multiscale data, and play a critical role in enhancing the research we fund. The examples highlight specific priority areas where we aim to maximise the potential of data science and AI in a global health context.
Example areas of focus include:
- context-relevant models: Developing analytical and predictive models that are appropriate across different populations and settings
- AI-enabled intervention development: Applying artificial intelligence to improve the discovery, design and optimisation of interventions