Are We There Yet? A Digital Maturity Model for Enabling Process Monitoring and Artificial Intelligence in Biologics Manufacturing

Digital transformation promises to revolutionize biopharmaceutical manufacturing, yet most organizations leverage only a fraction of their process data — and the challenges are paradoxically increasing with digitization and globalization. Digitization does not automatically deliver analytics-ready data. New AI capabilities, from multivariate methods through foundation models and agentic systems, demand data infrastructure that most sites have never been asked to provide.

This webinar introduces BioMetre, a practical maturity framework serving as a GPS for process monitoring readiness, developed and deployed across a global biologics manufacturing network. The model scores data readiness along two axes: what process data exists across six categories, and how well it flows across six delivery dimensions — freshness, frictionlessness, accessibility, authenticity, structure, and availability. Assessments across 25+ products revealed scores ranging from 30–80%, with organizations excelling at collecting critical data but struggling to make it analytically accessible.

Drawing on nearly four decades applying AI to biologics manufacturing, Jack Prior will share practical lessons for identifying the specific data gaps standing between current operations and effective AI adoption — and why getting the data foundation right is the highest-leverage investment a manufacturing organization can make.

Presented by Jack Prior, Head of Process Monitoring & Data/AI Strategy at Sanofi

Jack Prior leads process monitoring and data science/AI strategy within Sanofi’s Global Manufacturing Science and Technology organization, where he has spent nearly 30 years focused on biologics manufacturing. His career has consistently sat at the intersection of manufacturing science and data analytics, and at the interface of process development and cGMP manufacturing. He has led organizations of up to 50, supported global technology transfers, and delivered yield improvements with 8-figure annual impact.

Jack’s MIT doctorate applied artificial intelligence to biologics process troubleshooting and monitoring nearly four decades ago. He has been building on that foundation ever since, from early multivariate methods through modern data science to current efforts advancing agentic AI readiness across global operations. He earned his B.S. in Chemical Engineering from the University of Connecticut, where he was inducted into the Academy of Distinguished Engineers in 2013.

He serves on the PDA Science Advisory Board and the MIT Leaders for Global Operations Governing Board, and is a frequent speaker on practical AI readiness in regulated biomanufacturing. An eight-time marathoner and Boston Marathon qualifier, he has raised over $45,000 for Dana-Farber Cancer Institute and the National Organization for Rare Disorders.

From Ready to Routine: Agentic AI for Bioprocess Decision Support

Once process data is ready, the next question is how teams can leverage it for routine decisions. Bioprocess organizations have invested heavily in digitization, yet day-to-day work such as investigating deviations, comparing batches, supporting tech transfers, and preparing regulatory justifications still often depends on manual analysis stitched together from disconnected systems. Agentic AI offers a path to change the economics of this work, but only when it operates on well-structured, accessible, and trusted process data.

Masaki will share how Invert is applying agentic AI to help bioprocess teams achieve consistent decision support. The session explores how agentic systems build process-level context from heterogeneous data, surface data-quality issues before they distort analysis, and guide scientists and engineers through multivariate, mechanistic, and root-cause analyses.

The session closes with practical lessons on which data-readiness gaps matter most for AI adoption, where agentic systems add disproportionate value today, and how to deploy them in regulated environments without compromising auditability, explainability, or trust.

Presented by Masaki Yamada, Head of Product at Invert

Masaki Yamada is the Head of Product at Invert, where he leads the development of AI agents to help bioprocess teams move faster from data to decisions. His work sits at the intersection of process engineering, data systems, and applied AI in manufacturing environments, informed by his wet-lab experience in strain engineering and process development at NASA Ames, Genentech, and Culture Biosciences.

Sponsored by Invert Bio

Invert builds data infrastructure and intelligence for bioprocessing. The invert product automatically connect all process data across equipment, instruments, and other systems. Scientists and engineers can easily achieve weeks of data analysis in minutes, using the native AI tools.