From Data to Decisions: AI and Multi-Omics for Cell Culture Development

As biologics developers work to improve productivity, maintain product quality, and accelerate development timelines, traditional optimization approaches can sometimes reach a point of diminishing returns. While cell culture processes generate vast amounts of biological and process data, extracting actionable insights from that information remains a significant challenge.

In this webinar, Thermo Fisher Scientific specialists discuss how the integration of multi-omics data, artificial intelligence (AI), and deep cell culture expertise can help uncover the biological mechanisms driving process performance. Learn how AI-enabled analytics can support more informed decision-making, identify optimization opportunities, and accelerate media and process development.

In this session, you will learn about:
~ The role of multi-omics in understanding cell culture performance
~ How AI is helping uncover biological drivers of productivity and quality
~ Emerging applications of predictive modeling in media and process development
~ New approaches to turning complex biological data into actionable insights

Key topics include:
~ Case study: using AI and metabolomics to overcome optimization plateaus
~ Multi-omics approaches in cell culture development
~ AI-enabled data integration and pattern recognition
~ Understanding productivity and product quality trade-offs
~ From biological data to development decisions

Discover how AI and multi-omics are helping developers move beyond descriptive analytics toward more predictive, mechanism-based approaches to cell culture optimization.