Pharma · Clinical Trials Databricks Lakehouse Metadata · Governance · Lineage

Get to your clinical insights weeks earlier.

Deep data engineering expertise, built for pharma. We architect Databricks Lakehouse platforms with Medallion pipelines, SDTM/ADaM standardisation, and metadata-driven governance — so your teams spend time on analysis, not on waiting for data.

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Life Sciences · Pharma

Clinical data that's ready to work the moment the study closes.

The bottleneck after study lock isn't creativity — it's plumbing. Manual data packages, siloed systems, no metadata. We remove that friction entirely.

SDTM Standardisation

Automated domain mapping from any EDC — Rave, Vault, REDCap

ADaM Derivation

ADSL · ADAE · ADLB · ADTTE in PySpark — at scale

Secondary Analysis

Self-serve access for biostatistics, safety, and medical affairs

Cross-Study Repository

Phase I–IV data harmonised, discoverable, governed

Real-World Evidence

EHR, claims, registries and omics alongside trial data

Clinical Data Flow — Post-Study Secondary Analysis

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CDISC-Compliant by Default

Every Silver domain lands as valid SDTM. Every Gold dataset is ADaM-structured. No manual QC sprint before analysis can begin.

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Metadata at Every Tier

Source provenance, transformation lineage, and semantic descriptions catalogued automatically in Unity Catalog — so teams know exactly what they're querying.

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Self-Serve, Not Gated

Biostatistics and medical affairs query curated, governed datasets directly. No central data request queue. No weeks-long wait for a bespoke extract.

Databricks Lakehouse

Medallion architecture,
built for clinical data.

We don't bolt Databricks on — we design every engagement around it. Bronze preserves raw source data. Silver standardises to SDTM. Gold delivers ADaM analysis datasets. Unity Catalog governs everything with metadata and lineage from ingestion to output.

Unity Catalog — metadata, lineage, and ABAC across every study and workspace
Delta Live Tables — declarative SDTM pipelines with built-in data quality expectations
Databricks SQL + Photon — sub-second queries on billion-row patient datasets
MLflow — reproducible PK/PD models and biomarker experiments with full data lineage
Asset Bundles — CI/CD-driven, version-controlled deployments across DEV→UAT→PROD

Metadata · Governance · Lineage

Data teams can't trust what they can't understand.

Metadata is the layer that makes everything else work. Without it, your SDTM domains are just tables. With it, they're described, traceable, and instantly discoverable by anyone who needs them.

Metadata

Automated Data Cataloguing

Every dataset, column, and transformation catalogued in Unity Catalog at ingestion time. Variable-level descriptions, CDISC controlled terminology links, and study context — automatically, not manually.

Lineage

End-to-End Data Lineage

Full lineage from raw EDC field to derived ADaM variable. When biostatistics asks "where did this value come from?", the answer is one click — not a week of detective work.

Governance

Access Without Bottlenecks

Unity Catalog ABAC gives the right team access to the right study data — automatically. No manual access requests, no shared passwords, no central team as the data gatekeeper.

Quality

Data Quality as Code

Great Expectations and Delta Live Tables constraints enforce quality rules at every Medallion tier. Bad data is caught and flagged at Silver — before it reaches the analysts in Gold.