What if we could automate the manual tasks that create capacity bottlenecks in pathology labs — so patients get the answers they need sooner?
In the Asia-Pacific region, pathology labs are under pressure. Rapidly ageing populations are increasing demand for diagnostics. But specialist skills are in short supply, particularly in remote or underserved communities; Asia is home to just 6.8 pathologists per one million population, compared with 17 per million in South America and 48.8 in North America.
At the same time, health systems — burdened with the growing prevalence of chronic conditions including Type 2 diabetes, HCC (liver cancer) and cardiovascular disease must do more and more with fewer resources.
Traditional workflows can’t keep pace with rising demand
Traditional pathology workflows are not well suited to these challenges. Manual workflows are very time-consuming, resulting in capacity bottlenecks and high variability of quality and turnaround times across sites.
Traditional workflows also require subspecialist skills for preparation, analysis and handling. The process includes:
- Multi-step preparation: Tissue samples are collected and embedded in paraffin, then sliced into ultra-thin sections, stained, and mounted on glass slides.
- Slide-by-slide reading: Pathologists review each case individually under a microscope.
- High touch handling: Samples are labelled and tracked, with documented custody at every stage.
- Physical movement of materials: Slides are transported between labs/clinics, risking delays or damage.
The process creates additional burdens over the long term, too; glass slides must be stored, retrieved as needed and re-filed. Physical storage space creates constraints to scale. Access in remote areas is often severely limited.
Digital pathology tools overcome the limitations of manual processes
Digital pathology addresses the challenges in a connected workflow. Whole slide imaging (WSI) scanners convert glass slides into ultra-high-resolution digital files which can be viewed, annotated and shared instantly — removing the delays and risks of physically moving slides between sites, and enabling remote consultation where expertise is scarce.
Once digitised, cases are stored in secure platforms, integrated with the laboratory information system (LIS) and hospital IT systems.
This interoperability allows for much more efficient accessioning, worklist triage, case assignment, and reporting, by standardising processes across sites and reducing variation driven by local workarounds. Pathologists can pick up the right case at the right time, with the context they need to make a decision, from any connected workstation.
Digital pathology workflows also create more structure — with audit trails by default, automated case tracking, and collaboration tools for second opinions.
AI and advanced analytics provide deeper, more accurate insights
All of which creates a platform to unlock deeper clinical insights throughout the diagnosis pathway, with AI and advanced analytics.
Machine learning algorithms can identify patterns difficult to detect with the human eye, standardise biomarker quantification, prioritise high-risk cases for rapid review, support precision medicine through reproducible, data-driven decision-support.
These capabilities can be used for both pre-screening — flagging cases for review — and second-line reviews: giving pathologists a ‘second pair of eyes’ for quality control to improve diagnostic accuracy. A meta-analysis of 100 studies examining accuracy of AI-enabled digital pathology tools across all disease areas reported a mean sensitivity of 96.3% and specificity of 93.3%.
Importantly, AI complements rather than replaces the pathologist — standardising interpretation, reducing oversight risk and helping maintain consistent diagnostic quality across sites and workloads.
Hub and spoke networks can address skills shortages
Digital pathology also supports hub-and-spoke models of service delivery — increasingly vital in regions with unequal access to subspecialist expertise.
In this model, smaller “spoke” laboratories handle sample preparation and slide scanning locally, while digitised images are sent instantly to a central “hub” for review, reporting and quality oversight.
This approach reduces turnaround times and variability between labs. By decoupling where samples are processed from where they are interpreted, digital pathology in a hub and spoke model can improve health equity in the communities who need it most.
In Indonesia, a hub-and-spoke model is scaling HPV DNA testing nationwide in the National Cervical Cancer Elimination Plan (2023–2030). High-capacity laboratories in urban centres act as testing hubs, supported by community-based spoke sites for self-sampling and specimen collection.
Early pilots in East Java show 99.9% successful self-sampling and strong community uptake — proving the model’s feasibility and efficiency.
And in the Philippines, the Centralised Laboratory Model for Cervical Cancer Screening (CLAMS) project in Metro Manila has also demonstrated how a hub-and-spoke approach can widen access to HPV testing.
Nearly 5,000 women were screened over 18 months, with 98.5% choosing self-collection and centralised lab testing, achieving a 7% positivity rate. The pilot highlights how centralised testing paired with decentralised treatment can drive equitable, large-scale screening.
Connected ecosystems transform clinical and economic outcomes
In a digital pathology ecosystem, outcomes improve for everyone. Clinicians have better data, on which they can make faster, more informed decisions. Patients can play a more empowered role in their own care, because earlier diagnosis often means more agency in choosing their treatment pathway, as well as a lower risk of complications from long-term conditions.
With pathologists focusing their expertise where they can add the most clinical value, lab leaders can transform a high-touch, resource-heavy, location-bound process into a scalable, quality-managed service.
And at the health system level, digital pathology addresses one of the biggest challenges facing our region: access.
In Vietnam, Roche’s pathology lab partnership has increased capacity tenfold, transforming 50-person manual operations into an automated end-to-end laboratory system, from pre-analytics to post-analytics.
Digital pathology’s benefits for efficiency, access and scale are clear. But before we can get there, there are barriers to overcome; upfront costs can be substantial. Regulatory and approval processes differ across health systems. Legacy IT infrastructure may create technical complexity.
This is why digital pathology can only improve outcomes at scale if we work together. Pathology leaders, policymakers, key opinion leader clinicians and digital innovators all have a role to play.
We must each champion digital pathology as the way forward — as the only way to address soaring incidences of chronic disease across the Asia-Pacific region and build stronger, more resilient health systems.
There’s one more stakeholder with the ability to drive positive change in health and care: you. By liking, sharing or reposting this article, you can help to spread the word. Please do so. Thank you.
