Feature|Videos|October 7, 2026

Embedding Artificial Intelligence within Pharma Supply Chains

Key Takeaways

  • Identify the risks of layering AI onto legacy supply chain systems, including data fragmentation, hallucinations, and limited auditability in GxP environments.
  • Describe how end-to-end contextualization of internal and syndicated data supports real-time decisions across the pharmaceutical cold chain.
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Sponsored by PAXAFE

Artificial intelligence (AI) is advancing quickly, yet many pharmaceutical supply chain solutions layer AI onto legacy software rather than designing one for a specific purpose. This approach can complicate decisions in an industry that requires good practice (GxP) compliance. Drawing on supply chain expertise, Mark Talens, Chief Commercial Officer at PAXAFE, highlights the consequences of this persistent fragmentation problem. He outlines guardrails for AI adoption, clear expectations for what AI should deliver, and defined limits on what AI may act on rather than only recommend. For example, using an end-to-end approach that contextualizes multiple high-quality data sources in real time—weather, political events, route disruptions—can support a product as it moves across the cold chain from packaging to the hands of a patient. Talens further emphasizes the need to audit AI and keep human oversight at the forefront. Doing so builds a foundation of trust as AI solutions progression and provides more automation across the supply chain.


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