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Automated Quality Control in Concentriq for Research: Accelerate R&D with AI-Based Controls that Save Time and Improve Quality

By Proscia | February 6, 2023

One thing I love about working at Proscia is the daily reminder that we’re working with customers in the life sciences who are at the forefront of an ongoing digital transformation. By adopting digital pathology, our customers are rapidly expanding their abilities to understand biology and disease from tissue to genes with people and pixels. 

Since launching Automated QC in May of 2022, our customers have achieved dramatic workflow efficiencies and quality benefits, and these companies are now charting a course for a computational future that accelerates discovery with artificial intelligence (AI).

Artifacts and digital pathology

For any organization that dives into digital pathology, the challenge of artifacts and image quality issues will emerge. Artifacts are simply imperfections in the slide or image being reviewed. 

A well-known challenge in traditional, microscope-based pathology, artifacts persist in the world of digital pathology as well. But with digital pathology, new artifacts are introduced during the digitization process. The sheer volume of whole slide images (WSIs) produced, demands a technology-assisted way of detecting and dealing with such artifacts quickly – because if they go undetected, the alterations caused by the artifact can adversely skew research findings. 

Early detection is key 

The fact is, slide preparation and scanning is time-consuming – requiring significant resources to review and ensure that images are of sufficient quality prior to analysis. As a manual process, there is room for error. Artifacts happen – but they can be difficult to identify.

Quality challenges are costly and disruptive. Issues that are not caught upfront create significant downstream complications and costs. Your researchers may need to request a rescan, which can be a cumbersome process that diverts attention away from analysis. 

Clearly, it is more cost and time effective to catch quality issues as far upstream as possible. But variations in determining what constitutes “poor quality” result in inconsistencies regarding what gets flagged and what passes through. This, in turn, can lead to variations in the data that serves as the basis of ongoing biomedical research – which is particularly problematic when using images to train machine learning algorithms.  

How Proscia helps

Concentriq for Research automates quality control (QC) with an AI-enabled application that helps identify commonly occurring slide- and image-quality artifacts. Your team is able to: 

  • Increase research efficiency
    The automated quality control application for Concentriq for Research flags slides that require a rescan earlier in the workflow. These images are then presented to reviewers in a way that reduces overall review time.
  • Improve the quality of research data
    Reliable research results depend on the quality and consistency of the data that drive it. Automated quality control significantly reduces the possibility of compromised images being introduced into the research process, helping to ensure that the data driving research is consistent and reliable. The same is true for the data sets that support the training and validation of machine learning algorithms. Automated quality control ensures that algorithms are trained on the highest quality data. 
  • Resource reallocation and cost savings
    Automated quality control not only detects image artifacts with high precision, it also speeds the quality control process. This enables your lab to reallocate time to other, higher-value efforts.
  • Boost lab tech satisfaction
    Automated quality control minimizes time spent on one of the more tedious tasks from your lab techs’ daily list of duties. This improves lab tech satisfaction and helps to drive productivity. 

Quality, automated

Every time a quality issue is identified, research and analysis slow down, tissue needs to be recut, reprocessed, and re-evaluated. Automated quality control in Concentriq for Research keeps the research flowing by catching issues early using AI and prevents compromised data from being passed along. 

What’s more, it plugs seamlessly into the routine research workflows of Concentriq for Research users – enabling you to automate what has historically been a manually intensive task. 

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