Pharmaceuticals & Life Sciences

Enterprise AI Platform for Pharmaceuticals & Life Sciences

Enterprise AI Platform for pharmaceuticals & life sciences, built around the constraint that defines the sector: GxP validation means every system change needs documented evidence before it reaches production.

Regulations in scope
5
Systems we integrate
5
Typical first release
6 weeks

What changes when it is pharmaceuticals & life sciences

Cost allocation is the feature that gets a platform funded. The moment finance can see spend by team and by feature, the conversation changes entirely.

In pharmaceuticals & life sciences, GxP validation means every system change needs documented evidence before it reaches production. That single fact reshapes how enterprise ai platform has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is regulatory dossier assembly, usually integrated against QMS. Integration comes before intelligence. A model that cannot reach your systems of record is a demo with good manners.

Deployed across regulated and unregulated sectors, with audit trails where the regulator expects them. You own the code, the models where they are open-weight, and the documentation to run it without us.

The sector constraints we design around

Defining constraint
GxP validation means every system change needs documented evidence before it reaches production
Regulations in scope
CDSCO · US FDA 21 CFR Part 11 · EU GMP Annex 11 · GxP validation · ICH guidelines
Systems of record
LIMS · QMS · eTMF · SAP · pharmacovigilance databases
Where we usually start
batch record review

Enterprise AI Platform workloads in pharmaceuticals & life sciences

  • batch record review
  • adverse event intake and coding
  • regulatory dossier assembly
  • deviation and CAPA drafting
  • literature monitoring

What is included

  • Model gateway across providers with failover
  • Central prompt and template registry with versioning
  • Per-team quotas, budgets and cost allocation
  • Policy enforcement, PII handling, allowed models, data residency
  • Full audit log of every prompt and response
  • Self-service onboarding for product teams

Questions from this sector

Can an AI system be GxP validated?

Yes, with a documented validation approach, IQ/OQ/PQ, defined intended use, change control and evidence of consistent performance. We build the validation pack alongside the system, not afterwards.

How do you handle 21 CFR Part 11?

Audit trails, electronic signatures, access control and record integrity designed in from the start, because retrofitting them is effectively a rebuild.

Why not let teams call the APIs directly?

Because you lose cost visibility, audit trail and policy enforcement, and you end up with keys in a dozen repositories. A gateway gives teams the same speed with none of that exposure.

Does it lock us to one model provider?

The opposite, the gateway is what makes providers swappable, with failover when one has an outage.

How long does a platform take?

A usable first version with gateway, logging and quotas typically lands in six to eight weeks; governance depth grows from there.

Enterprise AI Platform for pharmaceuticals & life sciences, worth a conversation?

Tell us the workload and the regulation it sits under. We will tell you what is realistic.

Or email bd@dtrasglobal.com · call +91 74118 77878