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L4 Data Migrations in Pharma Traceability Explained
Busting the myths around L4 data migrations in pharma supply chains — data ownership, data retention, and how to switch traceability systems without disrupting operations.
At AltiusHub, we built our platform on one conviction — compliance shouldn't be a black box. The more informed you are, the better decisions you make.
That's exactly why we launched the AltiusHub Podcast. A space for honest, unfiltered conversations about pharma traceability — no spin, no vendor narratives. Just the kind of clarity the industry has been missing.
For our first episode, we chose a topic that's long overdue for an open conversation: L4 Data Migrations.
Why this topic?
Bring up L4 data migrations in any enterprise conversation, and the temperature in the room changes. Fear kicks in — fast. What's behind it? Some of it is real. A lot of it isn't.
We wanted to understand exactly where the line is. So we brought in two of the most respected voices in pharma serialization to help us draw it.
Who joined us?
- Scott Pugh, Founder and Principal Consultant at Jennason, has 17 years in serialization and has spent the last 13 years advising manufacturers, CMOs, and 3PLs through some of the most complex compliance transitions in the US market, including navigating full DSCSA enforcement.
- Justin Ahdan, Customer Champion at Ankhero, brings over 25 years of experience aligning technology and business operations, with the last seven of which have been deeply focused on serialization across the EU, UK, and the broader interoperability landscape.
Together, they represent a rare combination of ground-level execution experience and strategic advisory depth.
What we got into?
- We explored the real reasons why pharma companies hesitate to migrate from existing L4 systems
- We unpacked what data ownership actually means in the context of serialization
- What the regulations do and don't require when it comes to data retention
- What a rigorous, well-planned migration actually looks like in practice
- We also asked both Justin and Scott to weigh in on the role of AI in pharma supply chain data operations
The conversation closes with a rapid fire round on some of the most commonly held assumptions in the industry. The answers might surprise you.
If you're in Supply Chain, IT, Compliance, or Packaging Operations in pharma, this one is worth your time.
Short takes. Big industry shifts.
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Frequently asked questions
The main risks include data integrity issues, improper validation, and poor planning. However, with structured processes, testing protocols, and clear data mapping, these risks can be effectively managed and significantly reduced.
Regulations require data retention, not system retention. Companies can archive required data in accessible formats outside legacy systems, avoiding unnecessary costs while still meeting compliance requirements.
This perception often comes from past implementation experiences and legacy system limitations. Modern tools and standardized approaches have made migrations more structured, reducing complexity, timelines, and overall cost compared to earlier projects.
Traceability data always belongs to the company generating it. Vendors should only facilitate storage and access. Limited accessibility or paywalled data is a red flag indicating restricted control over critical operational data.
By implementing clear data mapping, transformation rules, and reconciliation checks. Running multiple test suites and formal validation protocols ensures migrated data matches the source accurately and meets regulatory and quality standards.
Meanwhile, read our top resources
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