GCC pharma builds clinical-trial data…

01 · The challenge

Problem

Clinical-trial data was scattered across CROs, labs, and country-specific repositories. Regulatory submissions took quarters and queries from regulators were frequent.

02 · How we delivered

Solution

Lakehouse with study-of-record semantic layer, data-quality contracts, and a standardised submission package generator. CRO data ingested via signed contracts.

03 · Outcome

Impact

Submission preparation time cut 36%. 12 trials live on the platform. Data-prep time cut 71%. 3 regulators accepted submissions on first attempt.

How we delivered

Programme phases.

Five phases. One accountable team. Every phase had a named decision point and a measurable outcome.

Discovery & alignment

2–3 weeks

Workshops with the Leading GCC Pharma Major executive team, baseline metrics, target outcome tree, programme governance set up.

Design & architecture

4–6 weeks

Reference architecture, security blueprint, joint squad model agreed. Data model and integration contracts published.

Build & live-parallel

Q2 onwards

Vertical slice built and run live-parallel against the existing system. Continuous integration, daily deploys, weekly business demos.

Cutover & scale

Mid-programme

Phased cutover, audit-aligned reconciliation, scaling out of squads, capability transfer to Leading GCC Pharma Major teams.

Run & continuous improve

Steady state

Managed run with named SLOs, quarterly value reviews, and a 15% optimisation budget reserved for improvement work.

Engineering view

Architecture overview.

Foundations

Cloud landing zone, identity, network, security baseline. Data fabric with lineage-by-default. Audit-grade observability stack from day one.

Application & integration

Domain-aligned microservices behind a published API surface. Event-driven core with CDC into the data fabric. Live-parallel capability built in, not bolted on.

Trust & governance

RBAC, audit logs, lineage, policy-as-code. Model risk records for every production model. Compliance posture on the executive dashboard, not in a quarterly slide.

Built on

Technology stack.

Production-grade choices, defended by track record. The stack is one engineering decision among many — but a load-bearing one.

Databricks Iceberg dbt Great Expectations Domino Tableau

Trust by design

Governance & assurance.

01

Programme assurance

Independent assurance reviews at each phase gate. Findings tracked in a single risk register with named owners and remediation deadlines.

02

Security & data

ISO 27001, SOC 2 Type II controls applied throughout. Data lineage captured by default; sensitive data tokenised at the edge.

03

Audit-grade evidence

Every change tracked; every release reproducible. Audit packs assembled automatically for internal and external review.

04

Continuous compliance

Policy-as-code scans on every commit. Compliance posture surfaced on the executive dashboard, not in a quarterly report.

A submission cycle is no longer a war. It is a checklist.

V VP Clinical Operations · Leading GCC pharma major

What we learnt

Three things we would do again.

01

14 months from kickoff to first regulated outcome — squad density and decision velocity matter more than headcount.
02

Joint squads with Leading GCC Pharma Major engineers stayed in place after go-live. Ownership did not transfer in a hand-off — it grew in place.
03

Live-parallel for a meaningful window before cutover bought us trust. The cutover itself was a flag flip, not a war room.

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GCC pharma builds clinical-trial data lakehouse — submission time −36%