Life sciences · GxP
Regulated data ingestion your quality team can validate.
For pharma, biotech, medical devices, CROs, and labs: code-native, validation-friendly ingestion for regulated data across GMP, GCP, and GLP. Built on dlt, run on dltHub.
Life sciences teams building on dltHub
For regulated life sciences · GxP
GxP validation that survives your next upgrade.
dlt is code-native, test-first ingestion; dltHub runs it. Together they satisfy CSA and GAMP 5 without freezing versions or exposing you to platform churn.
- GxP
- CSA
- GAMP 5
- 21 CFR Part 11
- EU Annex 11
- ALCOA+
- Your git tag is the validated baseline
- Python in your repo. You choose when to upgrade and which version runs.
- Deterministic by design
- Same input, same output, re-run on every change.
- ALCOA+ evidence built in
- Lineage, schema contracts, and run state in the context catalog.
- Read-only source access
- Enforced in pipeline code for Veeva Vault and LIMS, not by policy.
- Snowflake stays your orchestrator
- dltHub runs the pipeline; your control plane does not move.
The validation workflow, in three commands
Pin the validated baseline
git tag validated/veeva-vault@1.4.0tag created · this exact code is what you validate
Prove it behaves the same every run
pytest tests/behavioural/214 passed · same input, same output
Open the evidence trail
dlthub showrun history, schema contracts, lineage · the ALCOA+ record
How the validation works
You validate one pipeline. The evidence comes with it.
A coding agent builds it, your platform lead and QA sign it off, and Snowflake keeps triggering the runs. What changes is that every run leaves an evidence trail behind it.
Your coding agent
Claude Code, Codex, or Cursor
builds and fixes the pipeline
Your people
Platform lead + QA/validation sign-off
a person approves the release, not an agent
the agentic layerdltHub AI harness
Skills, commands, rules, and MCP: the agentic primitives to build, run, and fix pipelines
dltHub context catalog
ALCOA+ evidence: lineage, schema, run state, and provenance
the evidence is generated by the run, not assembled after it
Regulated sources
Veeva Vault
read-only access
LIMS
ERP
managed infrastructure, in your environment
the artefact you validate
One validated dlt pipeline
git tag = validated baseline
Ingestion & transformation
Scheduling & managed runs
Reconciliation & data quality
Warehouse
Snowflake
orchestrator of record
Snowflake triggers the run
Evidence produced per run
- Test results
- Schema contract
- Lineage
- Release notes
Maps to
- CSA
- GAMP 5
- 21 CFR Part 11
- ALCOA+
Snowflake Premier Partner for Healthcare & Life Sciences
dlt consolidates data from Veeva Vault, LIMS, REST APIs, SQL databases, and files into Snowflake; dltHub runs it as managed infrastructure in your own environment. The 30-day POC ships with the validation evidence your quality team reviews, and Snowflake stays your orchestrator of record.
The four questions every audit returns to
Each one is answered by a specific dlt or dltHub artefact, not a document, and each artefact feeds an audit-ready report module.
What went in?
dltHub answers with
The dlt pipeline's declared source and schema. Resources defined in code, source access read-only.
Where the evidence lives
The dlt pipeline (Python, in git)
What came out?
dltHub answers with
Snowflake tables, plus reconciliation checks (row counts, checksums) that run with the pipeline.
Where the evidence lives
Snowflake + the reconciliation test results
What changed?
dltHub answers with
A git diff and machine-readable release notes describing the behavioural impact.
Where the evidence lives
Git history + the release notes
Who approved?
dltHub answers with
The tagged release and its sign-off. Behaviour is stable until a released version alters it.
Where the evidence lives
The git tag + the approval record
Every answer is an artefact, attributable to a released version. One source of truth for your team, your agents, and your auditor.
What the 30-day GxP POC delivers
One regulated source into Snowflake, in your own environment, time-boxed to 30 days. For example Veeva Vault or a LIMS source via a read-only API. The output is a reusable template, not a bespoke pilot.
A validated baseline
The pipeline itself, ready for your quality process.
- dlt pipeline pinned to a git tag
- Behavioural test suite proving deterministic input to output
An audit-ready evidence pack
Generated by the run and mapped to CSA and GAMP 5.
- Test results, schema contract, and release notes
- Object-level lineage in the dltHub context catalog
A pattern you can repeat
Pipeline two to ten gets cheaper, not equally expensive.
- Snowflake-as-orchestrator trigger pattern
- Vendor-risk pack for quality and procurement
- A template your next pipelines inherit
How dltHub maps to your frameworks
How does dltHub fit Computer Software Assurance (CSA) and GAMP 5?
CSA and GAMP 5 favour risk-based, critical-thinking assurance over document volume. With dltHub you validate one artefact, the dlt pipeline pinned to a git tag, and the behavioural test suite is the objective evidence: same input, same output, re-run on every change.
How does dltHub support 21 CFR Part 11 and EU Annex 11?
dltHub provides the traceable run records: who ran what version, when, with which schema, and what it produced. Electronic signatures and your quality management workflows stay in your QMS; dltHub supplies the audit trail they reference.
Where does the ALCOA+ evidence come from?
The dltHub context catalog records object-level lineage, schema contracts, and run state for every load. Data stays attributable, contemporaneous, and complete because the record is generated by the run itself, not assembled afterwards.
Can dltHub read from Veeva Vault or a LIMS without write access?
Yes. Read-only access is enforced in the pipeline code itself, for example via Veeva's read-only Direct Data API, so the control is testable and reviewable rather than a policy statement.
Do we have to freeze versions to stay validated?
No. The git tag is your validated baseline; you choose when to upgrade. Re-running the behavioural suite against the new version produces the evidence that behaviour is unchanged, so upgrades become a controlled change instead of a revalidation project.
Scope your GxP POC
Bring one source and one stakeholder from Quality or Compliance. We map the validation package to your framework before any code runs.