BioFAIR is thrilled to announce the funding for our first round of Pathfinder Projects. With an investment of £826,000, these nine innovative projects will tackle critical FAIR bottlenecks across specific life science domains across the UK.
From clinical pathology and ecological monitoring to single-cell analysis and neuroscience, the inaugural Pathfinder cohort represents a united effort to make complex biological data more accessible, reusable, and AI-ready for researchers everywhere.
“Through Pathfinder Projects, we’re establishing a collaborative network of researchers who are tackling domain-specific FAIR-related challenges from across the UK. We’re looking forward to this group coming together to share practical experiences, identify common patterns that are shown to work in context, and help BioFAIR map out the template that we will use to create a federated, interoperable data ecosystem that accelerates research in UK life sciences.” – Tony Burdett, BioFAIR Director
Rather than a one-size-fits-all approach, the first set of Pathfinder projects is designed to tackle specific FAIR bottlenecks; spanning data standards, complex workflows, targeted training, and community building. Teams will investigate distinct challenges within their own domains, from clinical pathology to ecological monitoring, and through experimentation and co-creation with other BioFAIR teams, their practical successes will directly inform and shape the future of BioFAIR’s national infrastructure.
Meet our Pathfinder Cohort:
- OME Zarr Framework For AI-Driven Whole Slide Analysis (Led by David Harris-Birtill, University of St Andrews): Progress in AI digital pathology is slowed by proprietary image formats. This project will build an initial reference workflow using the largest public colorectal cancer histopathology dataset in OME-Zarr, creating a reusable pipeline for computational pathology.
- UK Regulatory Network Commons Portal (Led by Kedar Natarajan, University of Southampton): Researchers cannot fairly compare gene regulatory network predictions due to incompatible outputs. This project will benchmark leading inference methods against curated reference datasets to produce validated, FAIR-compliant regulatory networks accessible to the whole UK community.
- Connecting Bioconductor, Galaxy, and nf-core (Led by Kevin Rue-Albrecht, University of Oxford): Single-cell data analysis suffers from a fragmented ecosystem. This team will map selected Bioconductor single-cell workflows to Galaxy and nf-core pipelines, aligning metadata to establish a FAIR, interoperable baseline.
- FAIR-Figures: making publication figures AI-ready (Led by Melissa Harrison, EMBL-EBI): Biomedical publication figures are difficult to reuse for AI training because literature databases lack figure search capabilities. Co-creating with the Europe PMC team, this project will develop a metadata model and open workflow to make multi-panel brain images usefully searchable and AI-ready.
- Creating AI-enabled analysis pipelines for FAIR neuroscience data (Led by Padraig Gleeson, University College London): Complex multiscale neuroscience datasets are often inaccessible to those without programming experience. This project will develop a novel AI-enabled research assistant integrated with the Open Source Brain platform to provide interactive access to these models.
- From Local Monitoring to National Capability (Led by Phil Wilkes, Royal Botanic Gardens, Kew): UK ecological monitoring data is among the least FAIR in life sciences. This project will survey the UK monitoring landscape to expose gaps and deliver practical, modality-specific guidance – from bioacoustics to soil sampling – to embed FAIR data practices from the ground up.
- Advancing Comparative Metabolomics (Led by Ralf Weber, University of Birmingham): Systematic comparative metabolomics across model organisms is underdeveloped due to a lack of standardised resources. This project will expand the DMAdb platform into a multi-model-organism, FAIR-compliant community resource, piloting integration with UK ELIXIR-endorsed resources to support cross-species exploration.
- FAIRPath: Foundations for a FAIRer Plant Pathology Community (Led by Richard Ostler, Rothamstead Research): Plant pathology trials need improved data management. FAIRPath will launch a community survey on current data practices and standards to inform targeted workshops that drive community adoption of FAIR practices.
- The FAIR-in-action Bridge (Led by Xenia Perez Sitja, ELIXIR-UK, Earlham Institute): Research Data Management professionals lack the capacity to translate dispersed FAIR resources into practical materials. This project will co-create two FAIR-in-action playbooks and deliver six in-person events across UK Research Performing Organisations to distill international resources into reusable templates and activities.
Pathfinder projects represent a critical first step in a coordinated, UK-wide effort to remove the friction from data reuse and accelerate life science research. However, this initiative is about much more than funding nine isolated projects; it is a strategic, grassroots approach to blueprinting BioFAIR’s long-term national infrastructure. By tackling diverse, real-world FAIR bottlenecks, ranging from technical data interoperability and complex analytical workflows to essential community building and targeted training, these teams are providing requirements and acting as a testing ground for the entire UK ecosystem. The practical solutions they identify will feed directly back into BioFAIR, ensuring our emerging infrastructure is built on proven, community-led successes rather than assumptions.
To follow the progress of this cohort and learn more about our overarching mission, visit biofair.uk and follow our journey on LinkedIn and BlueSky.