Pharmaceutical manufacturing is built on precision, yet exceptions still slow production, strain quality teams, and delay release. What if your execution system could see problems before they occurred? In this keynote, Apprentice.io unveils how agentic, predictive AI transforms MES from a reactive system into a proactive co-worker. Learn how AI anticipates deviations, guides operators in real time, and creates exception-free execution — accelerating throughput, ensuring compliance, and redefining what’s possible on the production floor. In this session, you will learn more about:

• Transforming MES from a reactive system into a proactive co-worker using agentic, predictive AI.
• Anticipating deviations and guiding operators in real time to achieve exception-free execution.
• Accelerating throughput, ensuring compliance, and redefining production possibilities with AI-driven MES.

As pharmaceutical manufacturing accelerates, the ability to anticipate issues before they occur is becoming a critical differentiator. While many organizations are exploring AI to enhance MES, the real value lies in predictive analytics—using real-time data streams to forecast deviations, optimize batch release, and improve overall yield. This presentation will focus specifically on how predictive AI can transform MES from a compliance-driven tool into a proactive driver of operational excellence. Drawing on industry use cases, we will explore the opportunities and challenges of embedding AI-driven insights into day-to-day manufacturing execution. In this session, you will learn how to:

• Leverage MES data streams to build predictive models that anticipate deviations and quality risks.
• Translate predictive insights into actionable interventions for faster, safer batch release.
• Balance regulatory compliance with AI-driven decision-making to ensure trust, transparency, and adoption.

• How can we define and implement simultaneous platform shifts involving AI, AR, personalized medicine, and manufacturing systems?
• In what ways can AI and AR work together to enhance training, troubleshooting, and maintenance processes on the manufacturing floor?
• How can we accelerate the adoption of AI to drive faster batch releases and reduce time-to-market for pharmaceutical products?
• What are the economic, strategic, and quality considerations when implementing AI-driven MES solutions in life sciences manufacturing?
• How can we ensure a seamless integration of AI with legacy MES systems, and what steps are required for a successful transition?

In the Harvesting Session the workshop moderators of the event will summarize the results of their discussions and highlight key findings from the World Cafés.