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:
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, global heating and infectious disease.
Tools to transform
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. This will build on our completed work:
Trust in practice
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.
Talent with incentive
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.
Our series of Global Health Data Challenges will create multi-disciplinary collaborations aimed at solving some urgent health challenges. This builds on the scoping done by the Open Data Institute. The first data challenge aims to understand effective interventions against anxiety and depression in young people and will be run with Wellcome’s Mental Health priority area.
The Data for Science and Health programme does not have any funding calls at this time.
The Data for Science and Health programme does not have any calls for proposals at this time.
We are supporting the Lancet and Financial Times Commission(opens in a new tab), Governing health futures 2030: Growing up in a digital world. The Commission is exploring the convergence of digital health, artificial intelligence (AI) and other frontier technologies with universal health coverage (UHC). Read the FT’s Special Report on the Future of AI and Digital Healthcare.(opens in a new tab)