Implementing Artificial Intelligence to Optimize Process Development Workflows & Predict Manufacturing Outcomes

• Accelerating process development by examining machine learning case studies demonstrating practical tools, data requirements, and measurable workflow improvements
• Improving manufacturing predictability by leveraging machine learning to predict donor variability impacts and identify patient-specific factors affecting product quality
• Strengthening predictive process control by integrating real-time monitoring and AI analytics into existing GMP systems with traceable data collection

Speakers:

Benjamin Espen

Director - Engineering , Data Science & Cell Therapy

N/A, Personal