Computational Pathology Will Offset Clinical Lab Staffing Shortages by Streamlining Workflows

Following significant breakthroughs in computational pathology over the last five years, laboratories are starting to adopt digitized workflows and AI-driven technologies. They are gradually shaping a future in which computational pathology will be used in all clinical labs to support routine reporting, standardize results across samples, increase the efficiency of workflows, and reach more accurate and reproducible diagnoses. 

Computational pathology refers to the use of AI and diagnostic data to reveal more precise diagnoses and improve patient care. As clinical laboratories head into 2025, they should consider the benefits of this approach.

Specific workflows that AI can streamline

Digital pathology will continue to move towards fully automated workflows that include digital scanners and use AI-driven applications to analyze images and ensure their quality for subsequent diagnosis.

We will start to see laboratory directors responding to the global recruitment deficit in pathologists by adopting AI-tools that streamline workflows and provide pathologists with support for time-intensive activities, including:

• Triage of routine cases;
• Identification and assessment of cancers;
• Detection of rare events;
• Interpretation of biomarker assays;
• Ordering follow-up tests;
• Preparation of reports.  

Computational pathology will improve the cost effectiveness and turnaround times of applications that traditionally relied upon molecular approaches, such as the assessment of recurrence risk and prognosis for breast and prostate cancers. Whereas such tests are currently sent to specialty laboratories, with a turnaround time of up to two weeks, computational pathology approaches will be performed on digitized images in a matter of minutes.

As oncologists respond to the growing body of evidence demonstrating the accuracy, clinical utility, and cost effectiveness of these types of assays, uptake will increase in lieu of the more expensive molecular tests. 

Computational pathology forges a path to precision medicine

In the coming years, one of the most significant impacts of computational pathology will be in the realm of precision medicine. Technological advances in immunohistochemistry, multiplexing, spatial profiling, and AI will be used to develop novel companion diagnostics.

These cutting-edge tests will maximize the potential of next-generation targeted therapies including antibody drug conjugates, multi-specific antibodies, and immuno-oncology therapeutics to optimize cancer treatment by ensuring that the right medicines are prescribed to the right patients at the right times. 

Clinical lab managers who want to take advantage of technological advances, merge further into precision medicine, and potentially offset staffing shortages should discuss with data scientists on their teams whether computational pathology is a good fit in 2025.