Digital Bioprocessing

Overview

The end-to-end digitization of biopharmaceutical manufacturing using AI, real-time sensors, digital twins, and data infrastructure to reduce failures, accelerate development, and improve product quality. The dominant industry misperception is that digital bioprocessing means applying AI to existing environments, when in reality the prerequisite is building foundational IT/OT infrastructure, clean data layers, and ontologies before AI can generate value. True digital bioprocessing in the AI era requires curated process metrics and molecular measurements chained into digital twins that can train, create, and control molecular outputs end-to-end. (Segment 2 (05:00-10:00))