Hello, so glad you’re still here with us — and today is extra special: this is the 10th Prodeen blog post! 🥳

My name is Gabriel Ragazi, and I’m an AI Food Scientist at Prodeen. Over the past nine, we’ve dived into compliance, allergens, HACCP, nutrition, and innovation. And now, we’ve reached a topic that’s becoming absolutely central for anyone working with food packaging: Food Contact Materials (FCMs) and the tricky world of NIAS (Non-Intentionally Added Substances).

If you’re in this space, you know packaging comes with at least three big challenges:

1. Consumer safety
   Even low-level contaminants can pose health risks if not properly assessed.
   
   
2. Regulatory compliance
   Authorities like EFSA, FDA, BfR, and ANSES expect industry to identify, characterize, and evaluate NIAS. “We didn’t know” won’t cut it.
   
   
3. The innovation squeeze
   Recycled plastics, bioplastics, new coatings — every innovation brings opportunities, but also new NIAS risks that require close monitoring.
   
   

In other words: it’s not enough to react. The real game is staying ahead.

The problem: too much information, too little clarity

Anyone in FCMs knows the feeling:
Every day there’s a new publication in the Official Journal of the EU, new Food Contact Notifications in the Federal Register, fresh EFSA or FDA opinions, BfR reports, ANSES guidelines, border alerts, recalls… plus supplier spec updates.

The result?

• Overwhelming volume of updates: impossible to keep up manually.
  
  
• Noise: generic keyword searches bring dozens of irrelevant hits.
  
  
• Disconnected data: regulations, formulas, contracts, and scientific papers all live in separate silos.
  
  
• Late detection of NIAS risks: often buried in annexes, draft opinions, or technical guidance.
  
  

And when you catch it too late? The damage ranges from non-compliant stock to full-blown recalls. Nobody wants that.

This is precisely where generalized AI tools like ChatGPT fall short. While impressive for broad content generation, they are not designed for:

• Real-time, continuous monitoring of highly specific regulatory and scientific databases: ChatGPT's knowledge cutoff means it can't track daily changes in official journals, draft regulations, or supplier updates.
• Contextualized signal detection within highly structured, domain-specific data: It can't understand the nuances of "NIAS migration limits affecting the polymer series you actually use" by cross-referencing your product data with new legal texts. This requires deep integration with specific data sources and a highly specialized understanding of the food contact materials domain.
• Linking external alerts directly to your internal SKUs or formulas: ChatGPT operates on a generic knowledge base; it doesn't integrate with your company's proprietary product specifications or supply chain data.
• Providing actionable, traceable alerts with deadlines: It's a language model, not a workflow integration tool that can manage compliance tasks or generate reports based on evolving regulations.

When it comes to compliance and safety, "good enough" isn't good enough. You need AI that's purpose-built for the complexity of FCMs, not a general-purpose conversational model.

The way forward: smart monitoring (for real, with specialized AI)

Here’s what the ideal system should do:

• Continuous, multi-source surveillance: laws, draft proposals, scientific literature, recalls, supplier alerts — all in one stream.
  
  
• Contextualized signals: not just “anything about plastics,” but “draft NIAS migration limits affecting the polymer series you actually use.”
  
  
• Product-linked insights: mapping alerts directly to your SKUs or packaging material.
  
  
• Actionable delivery: traceable alerts, deadlines, and notifications integrated with your workflow.
  
  

Where Prodeen comes in

This is exactly why we built Prodeen Signals — to solve this problem for food contact, regulatory, and R&D professionals.

• You connect your product data — specifications, suppliers, COAs.
• You create plain-language signals (e.g., “monitor NIAS migration limits for phthalates in coatings”).
• You get continuous, product-specific alerts mapped to your SKUs, delivered straight to your inbox, teams, or PLM system.

Instead of reacting late, you get the head start you need to act before changes become binding.

A real-world snapshot

Picture this: you rely on a certain plasticizer in your packaging inks.
Suddenly, a draft regulation in the EU proposes lowering the migration limit for that substance.

• Your suppliers haven’t notified you yet.
  
  
• But Prodeen Signals already caught it, shows the proposed change, highlights which SKUs use the substance, and sends you an alert.
  
  

You’re ahead of the curve — free to adjust formulations, talk to suppliers, or plan alternatives before the law goes live.

👉 Or here’s another, more general example from this week: I set up a weekly monitoring signal for the ongoing Review of the EU Food Contact Materials (FCMs) Regulation. The idea was to automatically track initiatives, compliance challenges, risks, milestones, and stakeholder moves across trusted sources: EU portals, national government sites, NGO reports, and industry associations. The system checked these inputs, validated the findings, and then generated a structured report summarizing events, dates, sources, and stakeholders. Even though it’s still early days, the format already proved powerful — everything came together in one clear report instead of scattered updates across dozens of places.

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