Andrew Janowczyk

About Andrew Janowczyk

Pathology stands at a pivotal crossroads in modern medicine, with digital tools offering unprecedented potential to improve diagnostic accuracy, efficiency, and patient outcomes. Yet despite the surge of commercial products and research-driven algorithms, few have successfully transitioned into routine clinical use. This gap – between innovation and implementation – led us to examine the barriers to translation in depth.

Over the past two years, we have focused not only on developing algorithms but on the entire lifecycle of clinical deployment: from prototyping and validation to regulatory alignment and institutional integration. One of our key lessons has been the importance of mapping the full development and deployment pathway from the outset. Without this foresight, teams risk costly rework – particularly when algorithm updates force revalidation and invalidate prior evaluations.

Clinical deployment requires a mindset distinct from research. Whereas research cohorts are curated, clinical pipelines must process every incoming slide – including controls and technically suboptimal samples. Edge cases are the rule, not the exception. Integration also falters when technical constraints are overlooked. For example, an algorithm that annotates a million cells may be unusable if the image viewer cannot render them. Early feasibility prototyping proved essential to stress-test interoperability across algorithms, infrastructure, viewers, and regulatory frameworks.

Defining success upfront was another critical step. We looked beyond accuracy to include throughput, compatibility with accreditation standards, and long-term maintainability. These priorities guided our approach and helped us identify pain points early. We are now finalizing a manuscript that distills these lessons into practical resources – deployment templates, checklists, and software development kits – to help others scale digital pathology more effectively.

Importantly, clinical translation cannot be done in isolation. Success demands collaboration across departments – pathologists, biomedical engineers, IT specialists, and quality assurance teams – aligned by a shared vision. Our role is as much about building ecosystems as building algorithms: enabling reproducible, accredited, and sustainable digital pathology deployment. In doing so, we aim to help reposition pathology not only as a diagnostic specialty, but as a driving force in the future of precision medicine.