The Connection is a monthly briefing for pharmaceutical supply chain insiders to cut through the noise and surface clear, opinionated insights on data, compliance, and the systems that run the industry.
AI Misuse in Manufacturing Caught / FDA
What happened
The FDA issued a warning letter to a drug manufacturer citing significant CGMP violations, including insanitary conditions, lack of required testing, and failure of quality systems.
During the inspection, the firm stated it was using AI to generate procedures and compliance documentation, but failed to properly validate or review the outputs.
Why it matters
This is what happens when AI is layered on top of a broken system.
The issue wasn't the use of AI, it was the absence of foundational controls. Required processes like testing and validation weren't in place, and AI was being used as a substitute rather than a support layer.
The FDA explicitly called out over-reliance on AI as a compliance failure, reinforcing that accountability doesn't shift, even when automation is introduced.
In practice
This is the risk that doesn't get talked about enough. AI can generate structure but it can't replace understanding.
If the underlying system isn't sound, AI doesn't fix it. It just creates the appearance of compliance while the real gaps remain.
And when those systems are tested by regulators, partners, or real-world conditions, things break.
More on this signal:
Read the FDA warning letter
AI in Pharma Supply Chain / Reality Check
What happened
A discussion across serialization vendors and operators focused on how AI is actually being applied in pharmaceutical supply chains.
Why it matters
There's a gap between what's being sold and what's being said.
The external narrative is speed and transformation. The insider guidance is more measured. Start small, prototype, don't over commit.
In practice
Most supply chains aren't failing because of a lack of intelligence, they're constrained by how data is organized, how it moves, and how systems connect. Until that's solved, AI is going to feel more like an overlay than a real solution. It also may fail at critical junctures.
More on this signal:
Listen to the Decommissioned Podcast
MIT / State of AI in Business
What happened
MIT reports that AI adoption is accelerating across industries, with growing investment and executive focus.
Why it matters
Adoption is scaling faster than results.
A significant portion of AI initiatives remain stuck in pilot phases or fail to deliver measurable ROI. That points to a broader issue; success depends less on the model itself and more on whether the surrounding systems are structured to support it.
In practice
Companies don't struggle to experiment with AI, they struggle to operationalize it. In pharma supply chains, that gap is even wider because you're dealing with fragmented systems and multi-party data exchange.
More on this signal:
Read MIT's State of AI in Business 2025
DHS for Drugs / FDA
What happened
The FDA is being framed as a form of national infrastructure rather than just a regulatory body.
Why it matters
Compliance is shifting from obligation to system stability.
If the FDA functions as infrastructure, failures in traceability and data integrity don't just create inefficiency, they introduce systemic risk. That reframes compliance as something that needs to be built as a system, not layered on after the fact.
In practice
Treating compliance as a checkbox is going to break down quickly. The companies that hold up are the ones that treat data and traceability as core system design decisions.
More on this signal:
Read the story on FDA Matters
Indulgence Warning / DSCSA
What happened
A 483 observation escalated into a formal DSCSA warning letter.
Why it matters
This is what enforcement looks like in practice.
Weak foundations operate quietly for a period of time, but once expectations tighten, the gaps become visible very quickly. This shows enforcement aligning with the intent of the regulation.
In practice
A lot of systems "work" until they're tested. The problem is that enforcement doesn't test the best-case scenario, it exposes the weakest parts of your process and vendors.
More on this signal:
Read the FDA warning letter
BMS 340B Update / Claim Serialization Data
What happened
Bristol Myers Squibb is requiring covered entities to submit claim-level data for 340B utilization, including detailed dispense and administration data, within defined timeframes.
Why it matters
340B is becoming a data validation system.
This introduces a requirement for transaction-level visibility across dispensing, administration, and contract pharmacy activity. It's a clear move toward enforcing program integrity through data, not just policy.
In practice
Most organizations aren't set up to consistently capture, normalize, and submit this level of data across multiple systems and partners. And if that layer isn't solid, everything built on top of it: compliance, reporting, and AI becomes harder to trust.
More on this signal:
Read the BMS letter to their customers
Partner Spotlight / AltiusHub
What they're doing
AltiusHub provides serialization and traceability solutions designed to help pharmaceutical companies meet compliance requirements while maintaining flexibility across their data infrastructure.
Why it stands out
They're focused on making systems adaptable, not just compliant.
A lot of the friction showing up right now isn't about meeting standards, it's about what happens when systems need to evolve, integrate, or change.
In practice
A lot of L4 systems work until something needs to change. That's when the real complexity shows up.
If your data is hard to move, your system is hard to evolve. And that becomes a problem quickly in an environment where both regulation and expectations are still shifting.
More on this signal: .
More on this signal:
Visit AltiusHub.com
Final / Thought
AI isn't the constraint right now.
The systems it depends on are.
And based on what's showing up, that gap isn't closing as fast as the expectations are rising.
Have a story to share?
Send me an email
Want to learn more about Trust.med?
Visit our website
Interested in becoming a tech partner?
Book a meeting
More from Trust.med
Keep exploring supply chain connectivity.
Read more practical notes on partner onboarding, data exchange, and network operations.