What problem we solve
- Reproducibility crisis
- Fragmented data silos
- Submission friction (SEND, IND, IMPD)
- Systemic animal overuse due to non-reusable data
The FAIR metadata backbone for preclinical research
Turn preclinical studies into reusable, traceable evidence.
What Metadatapp is / is not
Not an ELN. Not a LIMS. Not an AMS.
Metadatapp sits above these systems as a shared metadata layer.
Metadatapp is:
- A FAIR metadata layer
- A semantic interoperability platform
- A research-grade data architecture
Who it's for
Tailored value for each stakeholder in the preclinical chain.
Academic / Public Research
Reusable, standards-aligned evidence that makes cross-cohort studies, open science, and grant reporting simpler.
CROs
Shareable metadata and traceability that reduce rework for SEND, IND, IMPD packages.
Biotech & Pharma
Evidence pipelines that de-risk IND and IMPD reviews and speed decision-making.
What is Metadatapp?
Vision: Extract maximum scientific value from every animal used.
Problem: scattered spreadsheets and siloed systems force repeat studies, missed phenotypes, and submission friction.
Solution: a research-grade FAIR metadata infrastructure that structures metadata, monitors outcomes, and integrates with your lab stack—so studies are traceable and reusable.
Metadatapp is not a digital notebook or database plumbing. It turns animal experiments into structured, interoperable scientific assets that can be combined, compared, and reanalyzed without re-running cohorts.
Why now
- FAIR mandates (Horizon Europe)
- NAMs & Virtual Control Groups
- Policy roadmaps (FDA / EMA)
Key pillars
Scientific rigor
Ontologies, standards, and interoperable metadata boost statistical power and translational probability.
Ethical responsibility (3Rs)
Reduction via reuse of traceable evidence; refinement via better monitoring; replacement via better predictions.
Operational performance
Less reinventing data, accelerated timelines, and AI-ready assets for multi-site programs.
FAIR by design
Metadatapp isn't merely "compatible" with FAIR; it makes FAIR measurable:
- Run multi-site studies without chaos.
- Statistical power from better metadata, fewer repeats.
- Traceable assets that feed AI/ML and submission packages (SEND, IND, IMPD).
Why Teams Choose Metadatapp
Accelerate and Simplify Research
Capture once, reuse everywhere—centralize and link data, metadata, and protocols to cut repeats.
Ensure Trust and Compliance
Ontology-driven, FAIR-by-design architecture with audit trails and SEND/ARRIVE-aligned outputs.
Collaborate, Integrate, Innovate
Secure sharing across sites; LIMS/ELN/HCM integrations; assets ready for AI and review.
Workflows made visible
01
Capture
Investigations → Studies → Assays. Ingest from LIMS/ELN/AMS with lineage intact.
02
Standardize
JSON-LD + vocab validation so every subject and assay stays comparable. See <a href="/fair-by-design">FAIR</a>.
03
Reuse & Decide
Assets, not files: export, reanalyze, and compare across cohorts. Browse the <a href="/use-cases">use cases timeline</a>.
ROI and reduction
Fewer repeats
Traceable metadata → higher statistical power → fewer repeated experiments.
Earlier go/no-go
Better monitoring → fewer missed phenotypes → earlier decisions.
Less waste
Cross-site reuse → reduced duplication and cleaner transfers.
Quantify it
Ask: “How many mice could we reduce with 30% reuse of traceable behavioral metadata?” Talk to us.
Q & A
Does Metadatapp replace my ELN or LIMS?
No. Metadatapp connects with your existing systems—ELNs, LIMS, HCM platforms—to avoid duplicate entry. It serves as a metadata hub that enriches, links, and harmonizes what you already capture.
What kind of data and standards does Metadatapp support?
Metadatapp manages preclinical metadata—subjects, protocols, devices, and outcomes—using ontology-based standards (JSON-LD, ARRIVE, FAIR, NWB soon) for semantic consistency and submission-ready packages (SEND, IND, IMPD). Learn more in <a href="/fair-by-design">FAIR-by-Design</a>.
How does Metadatapp ensure FAIR, transparent, and ethical research?
Metadatapp records all subject and experiment life events, enabling traceability, reproducibility, and transparency aligned with ethical best practices.
What export and integration options are available?
Export to CSV, JSON, JSON-LD, and RO-CRATE (NWB coming soon), and integrate with analytics tools, publications, or repositories like OSF.
Who is Metadatapp for?
Metadatapp serves academic labs, CROs, and pharma teams. Its modular architecture scales from small studies to enterprise programs.
The Team
Damien Huzard
Creator and CSO
Behavioral and metadata consultant at Neuronautix, developing Metadatapp as an API-first FAIR metadata platform for preclinical pipelines. Works at the intersection of behavior, physiology, and data science; co-developed LWTools and helps run TheBehaviourForum.org.
ORCID
Laurent Huzard
Backend Backbone
API Platform specialist; reviews architecture, hardens code, and crafts reusable modules.
Frédéric Deverre
Co-founder and CEO
Business development leader with 20+ years in MedTech across hematology, cell therapy, and osteoarthritis. Shapes GTM, builds CRO/biopharma/academic partnerships, and drives commercialization that keeps preclinical metadata FAIR and usable. Native French; fluent in English and Spanish.
Request an evidence readiness review
Validate alignment with SEND, IND, IMPD, and audit expectations.
Latest updates
View all1/21/2026
VICT3R Webinar: Standardization and Reuse of Data from Academic In Vivo Studies
Key takeaways from Damien Huzard's VICT3R webinar on FAIR metadata, operational standardization, and reuse in preclinical in vivo research.
11/1/2024
Welcome to Metadatapp
How we make preclinical metadata FAIR-by-design.