Data Integrity by Design: What a Pharma IT/OT Project Manager Looks for in the Cloud
How a pharma IT/OT project manager maps ALCOA+ data integrity principles to AWS services, and why the shared responsibility model is a validation scoping tool.
In regulated pharma manufacturing, a project isn't "done" when the system works. It's done when you can prove — to an inspector, years later — that every record is trustworthy. That changes how you evaluate cloud services.
The lens: ALCOA+
Regulators expect data to be Attributable, Legible, Contemporaneous, Original and Accurate — plus Complete, Consistent, Enduring and Available. Every architecture decision I review as a project manager gets mapped against these principles before anything else.
Regulators expect data to be Attributable, Legible, Contemporaneous, Original and Accurate — plus Complete, Consistent, Enduring and Available. Every architecture decision I review as a project manager gets mapped against these principles before anything else.
How this maps to AWS building blocks
- Attributable & Contemporaneous → AWS CloudTrail for who-did-what-when on infrastructure actions; IAM Identity Center for individual, non-shared accounts.
- Original & Enduring → Amazon S3 Object Lock (WORM) to prevent alteration or deletion of records during their retention period.
- Consistent → AWS Config to detect configuration drift against a validated baseline.
- Available → backup and multi-AZ design, documented and tested — not assumed.
The shared responsibility model is a validation scope tool
The most useful conversation I have with QA early on: what does the provider qualify, and what do we validate? Mapping the shared responsibility model onto GAMP 5 categories turns a vague "is the cloud compliant?" into a concrete list of controls we own, test and document.
The most useful conversation I have with QA early on: what does the provider qualify, and what do we validate? Mapping the shared responsibility model onto GAMP 5 categories turns a vague "is the cloud compliant?" into a concrete list of controls we own, test and document.
Lessons from the PM side
- Involve QA at the architecture stage, not at the validation stage. Rework costs multiply later.
- Treat audit trails as a requirement with acceptance criteria, not a checkbox.
- Risk-based thinking (GAMP 5 / CSA) lets you focus validation effort where patient safety and data integrity are actually at stake.
- Configuration drift is the silent compliance killer. Automate detection.
Open question for the community
How do you handle change control for managed services that evolve continuously? In GxP, "the provider updated it" still needs an impact assessment. I'd love to hear how other regulated teams approach this.
How do you handle change control for managed services that evolve continuously? In GxP, "the provider updated it" still needs an impact assessment. I'd love to hear how other regulated teams approach this.
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