Digital pathology and AI are finally coming into focus for diagnostics laboratories, according to a recent laboratory leadership report. We connected with Nathan Buchbinder, Chief Strategy Officer at Proscia, to explore the resulting data and what it means for the future of precision medicine.
In your survey, 86 percent of respondents say precision medicine has moved beyond the hype. What role do you see digital pathology playing in making precision medicine a daily clinical reality?
Precision medicine hinges on the ability to deliver highly specific, data-driven diagnoses. Digital pathology is making that possible at scale.
By transforming glass slides into whole-slide images, digital pathology drives far more than the operational benefits – like streamlined collaboration and remote access – that have largely defined its value to date. It creates a new data modality that offers one of the most detailed and direct views into diseases like cancer. With AI, we can now extract insights from this data that enhance clinical and genomic information, enabling a more precise understanding of each individual patient.
Building on rapid advancements in AI, whole-slide images also fuel the development of image-based companion diagnostics that can identify patients most likely to benefit from specific therapies. These assays are often more cost-effective, faster to run, and less tissue-destructive than their molecular counterparts, further enabling the delivery of precision diagnoses.
At the same time, digital pathology is helping to operationalize these and other novel image-based tests. It’s no surprise, then, that 59 percent of laboratory leaders believe digital pathology will be highly or extremely impactful in realizing the promise of precision medicine – generating richer and more efficient diagnostic insights.
Staffing shortages and financial pressures were the top two challenges identified by laboratory leaders. How is digital pathology uniquely positioned to help mitigate these pressures while maintaining diagnostic quality?
The ways in which digital pathology helps laboratories navigate workforce shortages and financial pressures aren’t new: expanding access to remote talent pools, automating routine tasks to boost efficiency and quality, and ultimately enabling pathologists to review more cases – with greater confidence – in the same amount of time.
What’s changed is the urgency with which laboratory leaders are acting on these benefits. There’s a growing recognition that point-level solutions are no longer enough. Our survey reveals laboratory leaders now embrace digital pathology, AI, and broader technology-driven modernization as solutions for long-term resilience. This shift is evident in the wide range of opportunities leaders are prioritizing, from automation and AI integration to partnering with pharmaceutical companies to unlock new revenue streams.
What types of diagnostic tasks are best suited for AI augmentation right now – and where do you see it going in the next 5-10 years?
There are fundamentally two categories of diagnostic tasks where AI is making the biggest impact today.
Firstly, there are tasks that benefit from increased precision. AI is already playing a role in identifying more nuanced biomarkers, correlating morphological patterns with therapeutic outcomes, and stratifying patients for clinical trials. In these contexts, AI is expanding the insight generated by the diagnostic toolkit and helping to lay the foundation for more personalized, data-driven care.
Secondly, there are manual, routine tasks that are ripe for automation. Quality control, triaging cases, pre-screening slides, and flagging regions of interest are all examples where AI is streamlining such processes. These applications allow pathologists to focus their time and expertise where it matters most, improving efficiency and consistency.
As we look ahead, it’s difficult to imagine a diagnostic task that AI won’t be able to augment in the next 5 to 10 years. AI’s progress is outpacing even the boldest predictions from just a few years ago. And just as we’re seeing today, AI will not replace pathologists. It will continue to enhance their work and amplify their impact.
What do you see as the biggest barriers to adoption and how are laboratories overcoming them?
The biggest barrier to adoption isn’t technology, culture, or regulation. It’s inertia.
The technology is ready. Platforms have matured to handle the scale and complexity of diagnostics. Cultural resistance is giving way as the evidence grows and pathologists experience the value of AI-driven pathology firsthand. And while regulatory frameworks continue to evolve, we’ve seen meaningful progress – enough to move forward with confidence.
The organizations seeing the most success on their digital journeys are the ones that had the courage to take that first step, even without having every answer in place. They’re looking to early adopters for a blueprint, building the business case, identifying the solutions that align with their strategic goals, and adjusting as needed.
If you could offer one strategic recommendation to pathology leaders considering AI adoption in diagnostics, what would it be?
Focus on building the right foundation, because no single model, algorithm, or vendor will solve every diagnostic challenge.
Deploying AI effectively in diagnostics isn’t about chasing the next promising algorithm. It’s about creating the infrastructure that allows AI to scale, adapt, and deliver meaningful clinical and operational impact. That’s why pathology leaders should prioritize a platform that enables AI to move beyond isolated outputs. This platform shouldn’t just run models. It should integrate them seamlessly into diagnostic workflows, connect pathology’s billions of pixels to clinical insight, and generate intelligence capable of navigating the complexity of real-world cases.
To truly deliver on the promise of precision medicine, we don’t just need more AI. We need the right environment for AI to thrive.
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