Xtalks — The Life Science Community™, Online webinar
2026-10-28
Biopharmaceutical teams are increasingly looking to AI to improve process development and optimization. However, the biggest constraint is often not the model; it’s the data. If experiments are run at low throughput, captured inconsistently or spread across different systems and organizations, there simply isn’t enough usable information for AI to work with. In this webinar, the featured speakers will explore how high-throughput laboratory workflows and better data integration can create the foundation for AI-enabled process optimization. The discussion draws on a high-throughput antibody production laboratory and an end-to-end workflow spanning expression, purification, analytics and data capture. The panelists will discuss the practical impact of automation in antibody purification, including the integration of an automated protein purification system into an existing workflow. Since introducing the system, the laboratory has reduced hands-on purification time and labor by approximately 80% and increased throughput from one run per day to three. Beyond simply making the laboratory faster, more consistent execution produces more consistent data, the kind of data that process models need. The webinar will also examine what happens when process data moves across sites, systems and organizations. Pharma sponsors and manufacturing partners often generate pieces of the same process data in different environments, making it difficult to build a complete picture of the process. The speakers will discuss how connecting that information can help teams use AI on a broader and more representative set of process data without requiring every organization to replace its existing systems. Attendees will gain practical insights into evaluating purification automation, integrating automated systems into existing laboratory workflows and thinking about the data infrastructure needed to support AI-enabled process development and optimization. Register for this webinar to learn how antibody production workflows can support higher-throughput purification, more consistent data and AI-enabled process optimization.
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