Abstract: Laboratory automation is often viewed as technologically challenging, yet our experience suggests that successful adoption depends far more on understanding the processes than on selecting platforms. We describe our progression from manual workflows through semi-automation and ultimately to advanced liquid-handling systems, using cell-based assays as case study.

A key lesson for successful automation implantations was that critical aspects of assay execution exist as undocumented analyst knowledge. Before automation can succeed, these factors must be identified and translated into explicit process instructions.

Semi-automation proved to be a valuable intermediate stage. Standard electronic pipettes mounted on robotic arms enabled controlled evaluation of workflow parameters while maintaining close analyst oversight. These systems supported rapid optimization, side-by-side comparison with manual execution, and identification of critical process variables before transfer to larger/complex liquid-handling platforms. Across multiple workflows, mixing behaviour emerged as one of the most influential factors affecting assay performance and reproducibility.

As workflows and understanding matured, automation efforts transitioned to complex automated systems developing reusable workflow components for common operations such as serial dilution, reagent addition, and cell dispensing. Comparisons between manual, semi-automated, and automated execution demonstrated that comparable outcomes could be achieved, but only after careful optimization of workflow details and platform-specific implementation strategies. This improved consistency, reduced duplicated effort, and supported adoption across projects.

Overall, rather than considering automation as a single complex step change, capability was built incrementally, using each stage of automation to improve understanding, reproducibility, and readiness for future scale.

Contributing Authors:
Mona Shehata, Theo Jackson
AstraZeneca, Cambridge, United Kingdom