2026 · Research-practice perspective
Better benchmarks, more trustworthy biomedical AI
The next advance depends on how models are tested, not only how large they become.
Research publication: 2026-09-17 · English briefing: 18 September 2026
What the research found
A September 2026 EMBL-EBI perspective highlighted the importance of independent benchmarking for biomedical AI. Reliable comparisons depend on appropriate datasets, clear metrics and evaluation that reflects the intended scientific task. Shared benchmark initiatives can reveal strengths and weaknesses that may be hidden by selected demonstrations.
Where the evidence stops
A strong benchmark result does not automatically establish clinical usefulness. Data leakage, shifts between populations and settings, and poorly matched endpoints can make an impressive score misleading in practice.
The private-client perspective
This principle belongs at the centre of Noah In Silico’s proposed framework. Before a model influences a research priority or clinical discussion, its intended use, validation population, uncertainty and failure modes should be documented. A private client’s interests are served by a system that can explain when it should defer to human expertise or decline to produce a recommendation.
Read the source
- EMBL-EBI: benchmarking reliable AI in biomedicine (2026-09-17)
An independent editorial synthesis of published research, not an original NoahThera study or a personal medical recommendation. Evidence stages are identified above; cited researchers and institutions are not represented as NoahThera partners.