Data First
FAIR-by-Design Standardization for NAM Evidence
Damien Huzard, PhD · Neuronautix
· 12 min
NAM science is advancing faster than NAM data infrastructure
Assays improved. Interoperability did not.
The bottleneck is metadata, not assay novelty
Current state
- Context trapped in prose
- Lab-specific endpoint semantics
- Legacy data hard to recover
Consequence
- Slow, manual reuse
- Costly cross-study synthesis
- Fragmented AI training corpora
Regulatory framing is data-intensive
Context of use, technical characterization, and fit-for-purpose are fundamentally metadata requirements.
FDA draft NAM guidance, 2026
Design-time FAIR beats post-hoc FAIRification
Post-hoc
- Expensive reconstruction
- Provenance gaps
- Uneven record quality
By design
- Required fields at source
- Validation at ingest
- Immediate reuse readiness
NAMO provides a practical domain model
Schema-first vocabulary for NAM systems, evidence context, and interoperability.
Minimal deployment pattern
Assay execution
-> Structured capture form
-> Schema + term validation gate
-> Versioned evidence record
-> Reuse query and reviewer export
AI assists curation; validation enforces trust
LLMs can draft mappings, but deterministic schema checks and human review decide acceptance.
Compounding return
Standardize now and accumulate reusable evidence assets; delay and accumulate remediation debt.
Position paper synthesis with FAIR and NAM evidence anchors
Next step: one 90-day pilot
- Select one assay family
- Define minimum metadata contract
- Enforce validation before acceptance
- Pilot historical-control reuse audit
White paper
·
PDF
·
Contact