AI Tool Automates Validation of Laboratory Software Configuration Changes

A new capability now automates planning, execution, and audit-ready documentation for configuration changes in regulated laboratory systems.

Labbit (Vancouver, BC, Canada) has introduced the Validation Assistant as the latest addition to its change management lifecycle for regulated laboratories. Building on the Configuration Assistant unveiled in 2025, the artificial intelligence (AI)-powered feature targets the most time-consuming elements of revalidation. The capability is designed to help laboratories manage system changes more efficiently without sacrificing control or system validation status.

When a new Labbit configuration is created, the Validation Assistant detects what has changed and automatically generates the corresponding test plan, test scenarios, and scripts from the configuration version. It then executes the qualification run and assembles an audit-ready documentation package. The package includes the configuration specification, test plan, execution log, and a summary report to support traceability and minimize manual documentation effort.

The new capability streamlines qualification of configuration updates before deployment to production by generating and executing validation assets directly from the system configuration. It addresses a longstanding bottleneck that has required extensive manual revalidation activities prior to changes being promoted. Labbit will showcase the Validation Assistant at booth 518 during the Bio-IT World Conference & Expo in Boston from May 19 to 21, with live demonstrations of automated documentation workflows for configuration changes.

“Validating a configured piece of software in a regulated lab can be as much work as configuration itself – sometimes even more. Labs have spent years managing configuration risk by limiting change, because every update can create a significant documentation and requalification burden. With the Validation Assistant, we’re applying AI to a very specific operational problem: generating and executing validation assets directly from the system configuration itself,” said Peter Smith, CEO of Labbit.

“In a market where there’s a lot of broad discussion around AI, we think this is a good example of practical AI that addresses a real bottleneck in laboratory operations,” added Smith.

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