Neuronautix · Notes
Practical notes on Home-Cage Monitoring, FAIR metadata, behavioral data analysis, and preclinical research infrastructure — written from real project experience.
All notes
Practical notes written from real project experience. New articles are added as projects, methods, and tools are tested in the field.
NAMs & regulatory science
NAM platform qualification should not start after the assay works. Metadata is part of the evidence: context of use, provenance, controls, endpoint definitions, and validation records determine whether a result can be reviewed or reused.
Read noteNAMs & data infrastructure
A practical build plan for NAM Evidence Commons: schema-first metadata capture, validation reports, provenance packages, evidence graphs, and agent-assisted curation.
Read noteNAMs & FAIR metadata
FDA's Elsa and HALO trajectory changes the practical question for NAMs: not whether the assay is novel, but whether the data is structured enough to review, compare, and reuse.
Read noteNAMs & regulatory science
FDA now accepts NAMs in INDs. The bottleneck is not generating the data — it is making it structured, traceable, and interpretable enough for a reviewer to act on. Five concrete ways data management closes the gap between experiment and regulatory confidence.
Read noteOntologies & FAIR metadata
Organoids, organ-on-chip, and in silico models each have their own data silos. NAMO is a LinkML-based ontology from the Monarch Initiative that provides a single structured framework for all three — with a five-dimensional validation concordance model and deep integration with UBERON, Cell Ontology, and ChEBI.
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If you are working on a Home-Cage Monitoring implementation, FAIR metadata strategy, or behavioral data analysis challenge and want it covered, contact Neuronautix directly.