Accelerating Parameter Optimization in Process Development

The biopharma industry is investing in moving away from manual, fragmented process development toward connected, AI-ready workflows. Benchling makes that shift possible with a process-centric data model built for structured, connected data. Teams analyze data faster, share results across the organization, and put AI to work on drug development.

In this webinar, Jason Boyd from Benchling will share a practical framework for improving process development efficiency. Two customer case studies ground it in practice: one shows how structuring parameter data in Benchling helped a team scale functional titer yield, and the other shows how a connected, traceable data model cut time spent on method validation.

Key Takeaways:

• Where AI fits into process development workflows today and where it's headed.
• Which digital capabilities actually drive efficiency gains.
• How to evaluate where your team stands now, and what to do next.
• Analyzing a firsthand look at how to prototype Benchling AI.