Designing safe, modular workflows for novel digital pathology algorithms.

Each algorithm has a unique set of inputs, outputs, and user needs — and each one required its own purpose-built workflow. Some require pathologist input at every step; others score slides automatically with little or no interaction.

Building trust in those automated algorithms — particularly among users new to AI-assisted pathology — was a persistent challenge that shaped design decisions across every workflow.

Rather than a one-size-fits-all approach, I developed a structured but flexible process that could be adapted to the specific demands of each algorithm — ensuring every workflow was grounded in user needs, validated through research, and built within real platform constraints.

Designs were delivered on time and within scope across multiple algorithm workflows. By staying out of the critical path, design ensured timely continuation of development activities — preventing downstream delays and keeping the project on schedule.

Feedback from pathologists during usability testing was positive overall, and the research findings generated through the process were leveraged beyond these workflows — contributing to other project activities and informing the broader platform roadmap. Most significantly, the quality of delivery solidified an ongoing relationship with Roche, securing additional design work for future algorithm iterations.