BioMAN 2026 Summit

Dec 09, 2026 - Dec 10, 2026

Samberg Conference Center

Posted by Massachusetts Institute of Technology

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Add to Calendar + 2026-12-09 8:00 2026-12-10 15:00 America/New_York BioMAN 2026 Summit

The 2026 BioMAN Summit held on December 9 – 10, 2026 will bring together leading experts from industry, academia, and regulatory agencies to explore the growing role of artificial intelligence, advanced sensing, and automation in biomanufacturing.

The Summit will examine how these technologies are being integrated into biomanufacturing operations, including data strategies and infrastructure for reliable AI models in GMP environments, maintaining and re-qualifying AI models at manufacturing scale, advances in sensing technologies, automation across biological drug modalities, regulatory expectations, and workforce development for AI-powered facilities.

Discussions will also highlight the potential for AI, real-time sensing, and automation to support continuous process monitoring, optimization, predictive control, predictive maintenance, and quality control and assurance, while considering the challenges associated with successful implementation.

Samberg Conference Center, Cambridge, MA, 50 Memorial Dr

The 2026 BioMAN Summit held on December 9 – 10, 2026 will bring together leading experts from industry, academia, and regulatory agencies to explore the growing role of artificial intelligence, advanced sensing, and automation in biomanufacturing.

The Summit will examine how these technologies are being integrated into biomanufacturing operations, including data strategies and infrastructure for reliable AI models in GMP environments, maintaining and re-qualifying AI models at manufacturing scale, advances in sensing technologies, automation across biological drug modalities, regulatory expectations, and workforce development for AI-powered facilities.

Discussions will also highlight the potential for AI, real-time sensing, and automation to support continuous process monitoring, optimization, predictive control, predictive maintenance, and quality control and assurance, while considering the challenges associated with successful implementation.

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