Data science is central to the future of health and the scientific endeavour. To support the right tools and people, we are investing £75 million in a five-year programme on data for science and health.
Data science is transforming how science solves urgent health challenges but progress in this field is inconsistent and is hindered by three systematic blockers:
Health data is information about physical and mental wellbeing, and the biological, environmental or socioeconomic factors that contribute to it. The data can be about an individual or a population. It is often collected as part of routine clinical care or research studies. Other sources of health-related data include climate monitoring data, location data or data from phone apps.
We have two goals:
Our programme is global, and we want to ensure that people in low- and middle-income countries benefit from innovation with health data, as well as those in high-income countries.
In each area below, we’re working to advance the objectives of Wellcome’s new strategy. These include a broad programme of discovery research and a focus on the urgent health challenges of mental health, infectious disease and climate.
Disproportionate effort is spent in preparing health data for analysis and computational methods now dominate modern science. Despite their importance, little funding is available for the foundational data and software tools used in health data research.
Without the right tools, work with health data is slow, the barrier to entry for data scientists is high, and only well-resourced institutions are able to make substantial progress.
We will fund open source foundational data and software tools for science and health, with a focus on usability, adoption and long-term sustainability. We will make it easier and more equitable for data scientists globally to innovate with health data.
Information about health feels intensely personal and people have concerns about privacy, security and commercial access to health data. Those collecting and using health data must earn the trust of people and society by demonstrating that they are trustworthy.
There are technical, institutional and social aspects to trust, all of which need to work together in practice. These include computational and data security measures, establishing good governance and clear accountability, being transparent about how data is used, and involving people in decisions.
Effective health data innovation requires a diverse set of people from multiple disciplines to communicate and work effectively together: data scientists and research software engineers, clinicians and healthcare providers, biomedical researchers, patients and the public, policy and decision-makers. These groups often don’t have a shared understanding of problems and there are few opportunities for them to collaborate effectively.
We’re enabling trustworthy data science by supporting specific projects. These include:
We often have calls for specific projects as part of our work, for applicants and teams in any country. We’ll update this page when there are opportunities to get involved in these projects.
If you’re looking for funding to support your research ideas, have a look at our discovery research funding schemes. These are open to applicants based in the UK, the Republic of Ireland and low- and middle-income countries, and coapplicants from the rest of the world if applying as part of a team.