While fully autonomous bioprocessing is within reach, adoption remains gradual as manufacturers navigate challenges around data maturity, regulatory expectations, and operational readiness. As companies modernize, the focus is shifting toward building the digital and organizational foundations needed to enable more intelligent, scalable process control, particularly through connected systems, stronger data infrastructure, and more explainable AI models that can support real-time decision-making.

In this episode of Off Script, we spoke with Mel Radford, director, life sciences global accounts at Rockwell Automation, about the key barriers to autonomy and how companies can move from reactive operations toward predictive and closed-loop process control. The conversation explores how hybrid models combining first-principles engineering with AI can improve control performance, stability, and yield while remaining transparent and easier to validate, as well as the importance of embedding compliance, governance, and human-centered change management into next-generation control strategies.