In this exclusive interaction with The Catalyst, Luke Benko, International Business Leader for Digital Pathology at Roche, shares how the company is leveraging AI, data, and strategic collaborations with national stakeholders to align with healthcare priorities, scale innovation, and build a more proactive, equitable, and sustainable future for diagnostics.
How do you see AI transforming the field of diagnostics over the next 5–10 years, especially in emerging markets like Egypt?
Egypt is a country with a population of nearly 120 million, with a relatively small number of pathologists and an even smaller population of sub-specialist pathologists. Digitization and AI usage will need to fill the deficit by providing more efficient pathology workflows, improved triage and screening tools, and faster methods to render a diagnosis. AI tools will also be used to help predict patient response and potential therapeutic pathway management. More patients will need more complex care, and an analog solution won’t be able to keep up in a digital world.
How is Roche ensuring that the deployment of digital pathology scanners aligns with national healthcare priorities?
Digital pathology scanners are the foundation of change implementation in modern pathology. Without digitization, cases can’t be shared instantly, AI algorithms can’t help predict outcomes, and algorithms can’t improve workflows. Roche’s commitment to improving patient care includes ensuring equitable access to technology and healthcare for all. This technology impacts positive improvements in many aspects of patient care, pathology, oncology, women’s health and many others.
In what ways Roche plans to leverage AI and data analytics to move from reactive care to proactive and preventive care?
Roche continues to make large investments into the digital and AI space. This includes development and collaboration to bring AI technology to the forefront of medicine, especially in pathology. These tools enable screening tools and triage applications that can help focus critical time and resources. AI workflow algorithms can help identify relevant areas likely to reflect impactful data in patient histological samples, allowing proactive measures to be applied earlier. Harnessing the power of complex and extensive data allows additional prediction models to continue to evolve, potentially enabling AI tools to predict therapeutic outcomes and pathways.
How do AI diagnostics improve diagnostic turnaround time quantitatively, and what benchmarks are you targeting?
AI-based image analysis algorithms can significantly reduce the time it takes for a pathologist to review a case. A study has shown that our image analysis algorithms can lead to a 66.8% reduction in diagnostic time. This is a powerful metric that demonstrates the direct impact of technology on efficiency.
Our goal is not just to hit specific benchmarks but to continually optimize the entire pathology workflow. Our digital solutions, like the navify platform, are designed to turn operational data into actionable insights, allowing labs to continuously improve their performance, manage staffing requirements, and adjust operations to reduce turnaround times.
Discuss the role that national stakeholders play in co-designing these AI solutions to meet local healthcare system needs.
National stakeholders are indispensable partners in co-designing solutions. They provide the local context, regulatory frameworks, and public health priorities that ensure our innovations are relevant and impactful. The collaboration with the Egyptian government is a perfect example of this. By working with their Ministry of Health, we were able to deploy a solution that directly addresses the most pressing needs of their public health system.
The future of diagnostics is being reshaped by the integration of AI, digital pathology, and data-driven innovation. As healthcare systems in emerging markets adapt to growing patient demands and limited specialist resources, these technologies are creating pathways to faster, more accurate, and more equitable care. By combining cutting-edge tools with collaborative partnerships at the national level, the focus is shifting from reactive treatment to proactive and preventive healthcare. This evolution signals a new era where precision, accessibility, and sustainability define the standards of modern diagnostics.
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