Invisible Infrastructure at Risk: Funding Crises Threaten Global Bioscience Research
Abstract Modern biology depends on invisible infrastructure that is essential yet precariously funded. Millions of biological observations are interpreted through resources that sit beneath routine scientific practice, largely unseen in everyday research. Every experiment, genome analysis, AI model, and clinical interpretation relies on these biological knowledgebases, which most researchers rarely notice until they disappear. That infrastructure is now under threat. Across the world, the biological databases that underpin modern research, built over decades of public and charitable investment, face severe and increasing financial instability. This crisis arrives at a particularly damaging moment: many governments have identified life sciences as a strategic growth sector and are investing heavily in genomics, AI-enabled drug discovery, and precision medicine. Yet every one of these ambitions ultimately depends on curated biological data resources reliant on emergency bridge grants, donations, staff secondments, and ad hoc rescue efforts.
Authors
- Christine Orengo (ORCID: https://orcid.org/0000-0002-7141-8936)
- Steven J Marygold (ORCID: https://orcid.org/0000-0003-2759-266X)
- Paul Nurse (ORCID: https://orcid.org/0000-0002-9244-7787)
- Elspeth A. Bruford (ORCID: https://orcid.org/0000-0002-8380-5247)
- Valerie Wood (ORCID: https://orcid.org/0000-0001-6330-7526)
- Valerie B. O’Donnell (ORCID: https://orcid.org/0000-0003-4089-8460)
- Neil Hall (ORCID: https://orcid.org/0000-0003-2808-0009)
- Katja Röper (ORCID: https://orcid.org/0000-0002-3361-766X)
- Jamie A Davies
Institutions
- University of Cambridge (GB)
- Norwich Research Park (GB)
- The Francis Crick Institute (GB)
- Cambridge School (PT)
- Earlham Institute (GB)
- Institute of Structural and Molecular Biology (GB)
- University College London (GB)
- Cardiff University (GB)
- University of Edinburgh (GB)
Publication Details
- Journal
- Genetics
- Published
- 2026-10-07
- DOI
- https://doi.org/10.1093/genetics/iyag274
- Primary Topic
- Research Data Management Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00