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The Wellcome Mental Health Data Prize UK 2026-2028 supports the development of data tools and AI solutions contributing to improving early intervention for anxiety, depression, and psychosis. This prize program, managed in partnership with Social Finance, funds teams to develop innovative data science and AI tools that can identify individuals at risk of mental health conditions earlier and connect them with appropriate interventions.
The prize builds on Wellcome's broader mental health science priorities and complements their separate generative AI mental health research program. Previous rounds funded teams at approximately £200,000 each. The UK 2026 round accepts applications until May 8, 2026 at 12pm.
The prize program has previously operated in Africa (2024-2026 with £200,000 per team) and globally (2022-2023 with £1. 4 million total). Contact: dataprize@wellcome.
org.
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Search similar grants →Based on current listing details, eligibility includes: Open to UK-based researchers, organizations, and teams. Teams should include data science expertise and mental health domain knowledge. Applications managed through Social Finance platform. Must focus on developing data tools for early intervention in anxiety, depression, or psychosis. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Approximately £200,000 (~$260,000) per team based on prior rounds. Managed in partnership with Social Finance. Prize covers 2026-2028 period. Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is May 8, 2026. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
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Review timelines vary by funder. Federal agencies typically take 3-6 months from submission to award notification. Foundation grants may be faster, often 1-3 months. Check the program's timeline in the official solicitation for specific dates.
Many federal programs offer multi-year funding or allow competitive renewals. Check the official solicitation for continuation and renewal policies. Non-competing continuation applications are common for multi-year awards.
Wellcome Genomics in Context Awards is a grant from the Wellcome Trust that funds research integrating genomic data with clinical, environmental, and social context to improve understanding of health and disease. The program supports projects that go beyond generating sequence data to investigate how genomic variation interacts with lived experience, exposures, and biological systems. Eligible applicants include researchers at universities and research institutions globally, with preference for international collaborations. Awards fund multidisciplinary teams combining genomics, epidemiology, social science, and clinical research to generate actionable health insights.
The Evidence for AI in Health (EVAH) initiative is a $60 million joint investment by the Gates Foundation, Novo Nordisk Foundation, and Wellcome Trust to support rigorous, country-led evaluations of AI health tools in low- and middle-income countries. Delivered in partnership with J-PAL and the African Population and Health Research Center, EVAH funds evaluations of AI-enabled clinical decision support tools in primary and community healthcare settings across Sub-Saharan Africa, South Asia, and Southeast Asia. Pathway A supports early-deployment evaluations focusing on usability, workflow integration, and safety for up to $1 million. Pathway B funds randomized controlled trials, economic analyses, and implementation science studies of tools ready for deployment at scale for up to $3 million. The initiative addresses a critical evidence gap about whether AI diagnostic and clinical decision support tools actually improve health outcomes in resource-limited settings.