Manufacturing Intelligence: How Digital Twins Are Changing Cleanroom Validation

In Episode 4 of Manufacturing Intelligence, co-hosts Chris Cole and Richard Jaenisch explore the emerging role of digital twins in cleanroom design and qualification in pharmaceutical manufacturing with guest Jonathon Thompson, global director of the digital center of excellence at CAI.

To view the full fascinating, practical, engaging conversation, click here!

Digital twins of cleanrooms are offering measurable reductions in commissioning time, rework, and pressure excursion investigation, but only when paired with rigorous real-time data verification, explains Thompson. He adds that the technology's core value lies not in replacing IQ/OQ/PQ, but in catching design flaws before construction locks them in.

The traditional cleanroom qualification workflow exposes problems late, Thompson notes, often after equipment is already installed and early-phase processes are running. Digital twins, fed with 3D building information modeling (BIM) models, HVAC specifications, personnel flow data, and physics-based fluid dynamics simulations, allow manufacturers to stress-test facility designs upstream. Thompson points to tangible returns: 10–30% reductions in commissioning time and resource hours, 20–50% reductions in rework, and 30–70% faster root cause identification during pressure excursions.

Regulatory acceptance, Thompson argues, depends on how the twin is used. "If you're using this digital twin as your single source of truth without verifying that data in real time with what's actually happening out in the field," he warns, "they're going to start to question it." Continuous process verification—cross-referencing the model against live environmental monitoring data, particle counts, and pressure differentials—is what earns FDA and EMA confidence in the approach.

For CDMO and modular facilities, where equipment configurations and product mixes change frequently, the stakes around model maintenance are especially high. Thompson observes that "we've got to change the mindset" to treat the BIM model as a living asset subject to change management, not a static deliverable from the capital project phase. As generative AI and light detection and ranging-based reality capture mature, automated model updating may eventually reduce that burden, making the digital twin a true operational constant rather than a commissioning tool.