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What really changed in digital pathology this year—and what still needs work?

As we close out 2025 and step into 2026, I wanted to pause, reflect, and share what I’ve seen shift from theory to real-world practice across labs, conferences, and clinical workflows.

I look back at the most meaningful developments in digital pathology and AI in 2025—from wider adoption of primary diagnosis on digital slides to more grounded, evidence-driven use of AI tools. We’ve moved past hype and pilots and started asking harder questions about validation, workflow integration, regulation, and trust.

I also share what I believe matters most as we move into 2026: building real-world evidence, upskilling pathologists, and focusing on tools that genuinely support patient care rather than distract from it.

This episode is for anyone navigating change in pathology and wondering where to invest their time, energy, and curiosity next.

Episode Highlights:

• [00:00–02:10] Why 2025 marked a turning point for digital pathology adoption
• [02:10–05:40] From pilot projects to clinical workflows: what actually changed
• [05:40–08:30] How AI usage shifted toward triage, quantification, and decision support
• [08:30–11:45] Why validation and real-world evidence became central topics
• [11:45–14:20] The growing role of pathologists in AI governance and quality assurance
• [14:20–17:10] Lessons from conferences, labs, and conversations worldwide
• [17:10–20:00] What I expect to see more of in 2026—and what I hope we leave behind
  
  

Key Takeaways:

• Digital pathology is no longer experimental—it’s becoming routine in more labs.
• AI tools are shifting from novelty to practical clinical support.
• Validation, regulation, and workflow fit matter more than algorithm performance alone.
• Training and continuous learning are now essential career components for pathologists.
• 2026 will reward teams that test, measure, and iterate thoughtfully.
  
  
  

Resources Mentioned

• Digital Pathology Place – education, podcasts, and community
• 2025 CONFERENCE insights and real-world lab experiences
  
  

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What if the biggest breakthrough in pathology AI isn’t a new algorithm—but finally sharing the data we already have?

In this episode, I’m joined by Jeroen van der Laak and Julie Boisclair from the IMI BigPicture consortium, a European public-private initiative building one of the world’s largest digital pathology image repositories. The goal isn’t to create a single AI model—but to enable thousands by making high-quality, legally compliant data accessible at scale.

We unpack what it really takes to build a 3-million-slide repository across 44 partners, why GDPR and data-sharing agreements delayed progress by 18 months, and how sustainability, trust, and collaboration are just as critical as technology. This conversation is about the unglamorous—but essential—work of building infrastructure that will shape pathology AI for decades.

⏱️ Highlights with Timestamps

• [00:00–01:40] Why BigPicture focuses on data—not algorithms
• [01:40–03:16] Scope of the project: 44 partners, 15–18 countries, 3M images
• [03:16–06:20] The 18-month delay caused by legal frameworks and GDPR
• [06:20–11:52] Extracting data from heterogeneous lab infrastructures
• [11:52–13:38] Current status: 115,000 slides uploaded and growing
• [13:38–18:39] Why LLMs and foundation models make curated data more valuable than ever
• [18:39–23:49] Industry collaboration and shared negotiating power
• [23:49–28:06] Data access models and governance after project independence
• [28:06–31:59] Sustainability plans and nonprofit foundation model
• [37:02–43:18] Tools developed: DICOMizer, artifact detection AI, image registration
  
  
  

📚 Resources from This Episode

• IMI BigPicture Consortium
• GDPR & Data Sharing Agreements (DSA)
• DICOMizer & SEND metadata tools
• Artifact detection AI for slide QC
• European AI Factories initiative

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What if the biggest transformation in digital pathology this year had nothing to do with new hardware—and everything to do with how we think about value, workflow, and readiness?

In this year-end recap livestream from the 11th Digital Pathology & AI Congress in London, I break down what truly mattered in 2025. Instead of focusing on buzzwords or hype cycles, this episode highlights the practical advances shaping diagnostics, patient care, and drug development—and the mindset shift our field must embrace to move forward.

Digital pathology is no longer “early adoption.” It’s becoming essential infrastructure. And yet the biggest barrier isn’t scanners or algorithms—it’s the knowledge and confidence needed to use them well.

Key Highlights & Timestamps

0:00 — Setting the Stage from London

An overview of the forces that shaped digital pathology in 2025: workflow integration, clinical readiness, and the move from theory to operational reality.

1:45 — Leica’s Expanded Portfolio & FDA-Cleared Collaborations

A look at Leica’s updated scanner lineup and co-developed, FDA-cleared solutions with Indicollabs. These launches reflect a broader industry trend toward highly specialized, clinically validated digital tools designed for end-to-end workflows.

4:12 — The Acceleration of Companion Diagnostics

From Artera’s de novo–approved prostate prognostic test to AstraZeneca’s TROP2 scoring efforts, 2025 pushed computational pathology directly into therapeutic decision-making.

6:20 — Why Workflow Integration Became the Theme of 2025

Partnerships like BioCare + Hamamatsu + Visgen and Zeiss + MindPeak show where the field is heading: full-stack solutions, not isolated tools. Labs want interoperability, reliability, and simplified digital workflows.

9:10 — Adoption Challenges: ROI, Education & AI Uncertainty

We explore the realities slowing digital transformation:
– ROI is real, but requires workflow change
– AI anxiety persists among clinicians and patients
– Education is still the strongest driver of adoption

12:00 — 2025’s Innovation Highlights

Breakthroughs shaping the next phase of digital pathology include:
– emerging agentic AI platforms
– voice-enabled image management systems
– improved multiplexing technologies like Hamamatsu’s Moxiplex

15:40 — The Growing Intersection of Pathology & Genomics

AI models predicting genomic alterations from H&E images gained traction, especially for cases with minimal tissue. Tempus acquiring Paige signals the deepening connection between digital workflows and molecular data.

18:30 — What 2026 Will Require

Priorities for the coming year include:
– building agentic AI solutions capable of real workflow orchestration
– strengthening validation and QC
– sharing real-world deployment case studies
– expanding training and hands-on learning

RESOURCES:

1. The Lucerne Toolbox 3: digital health and artificial intelligence to optimise the patient journey in early breast cancer-a multidisciplinary consensus

2. Artificial intelligence (AI) molecular analysis tool assists in rapid treatment decision in lung cancer: a case report

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