Smart Factory Roundtable: Challenges & Opportunities of AI in Pharma

35 life science experts exploring the exciting world of Smart Manufacturing and the use of AI in the pharmaceutical industry.

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At the end of a busy day with a lot of thought leadership input, vivid discussions and knowledge sharing, we agreed on some meaningful insights when it comes to creating the Smart Factory.

Key Takeaways:

1. Progress & The Road Ahead: While data-driven operations and digital platforms are gaining traction, there's still work to be done. Luckily, we have a clear vision shared by the presenters, guidelines from ISPE Pharma 4.0, BioPhorum DPMM, FDA & EMA AI papers, and plenty of tools and expertise to support the journey.
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2. Balancing Act: The industry faces several challenges from price pressure, diversity across 18 different modalities, some of the new ones still immature (like CGT and ADCs). Integrating automation with the flexibility needed for new modalities; and the regulatory support for AI adoption will be crucial.
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3. Data is King: High-quality, accessible data across the entire company is essential for successful AI implementation. Building a robust business case with a clear ROI will be key to securing executive buy-in. As Thibaud highlighted, we need to “show the money”
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4. People Matter: Developing talent and managing the human impact of change are critical for success. It was pointed out that the emotional impact of transformation shouldn't be overlooked.
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5. Collaboration is Key: Smart manufacturing requires a cross-functional effort with key players like Process Technology, , QbD, Engineering, and IT/OT working together across different streams: Manufacturing Excellence by Design, IT/OT Convergence, Supply Chain Intelligence, and Workforce Readiness.

Special thanks to our presenters:

• @Thibaud Stoll for presenting valuable insights into what operations expects from Smart Factory and his vision of the future of manufacturing.
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• @Michelangelo Canzoneri for sharing Merck's journey from MANUfacturing to SMARTfacturing.
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• @Viktor Mettler for highlighting the importance of conferences like the Pharma's Journey to Digital Manufacturing and Supply Conference for successful AI/ML implementation.
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• ‍@James Colley for presenting the BioPhorum DPMM, a model that defines the criteria and capabilities needed for increased plant maturity.
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• ‍@Christian Hoferer and @Arpan Suryawanshi for showcasing Roche's innovative Factory of the Future with the modular visual inspection robotic unit (VRU).
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• ‍@Kurt in Albon for emphasizing the value of AI while ensuring alignment with current best practices in quality assurance.

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Regulatory Considerations: We also discussed the importance of regulatory interaction. The FDA and EMA's discussion papers on AI in Drug Manufacturing recommend a risk-based approach for adoption, emphasizing collaboration and open communication throughout the process.

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