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Introducing AI-Powered Automated Quality Control to Accelerate Data-Driven Drug Development

By Proscia | May 24, 2022

Digital and computational pathology have become an integral part of the drug discovery and development process and are playing an increasingly important role in diagnostic labs. 

What was unthinkable some years back is now a reality, as computational pathology (AI) solutions are increasing the efficiency of lab operations, helping organizations drive new breakthroughs, and improving diagnostic precision.

You don’t have to take my word for it. According to a Deloitte’s life sciences digital innovation survey:

  • More than 60% of life sciences companies spent over US$20 million on AI initiatives in 2019, and more than half expect investments in AI to increase in 2020.
  • Top outcomes that life sciences companies are attempting to achieve with AI include enhancing existing products (28%), creating new products and services (27%), and making processes more efficient (22%). Most (43%) reported having used AI successfully to make processes more efficient.

Let’s examine that last point and apply it to pathology. As adoption increases and labs look to optimize their workflows in a digital environment, there are opportunities for computational technology to not only improve the way that images are analyzed, but improve on – or even eliminate – many of the manual and routine processes and tasks throughout the pathology workflow.

For example, the process of ensuring slide and image quality is both time-consuming and requires significant resources (it can be a full-time job for a technician) to review and ensure that images are of sufficient quality prior to analysis. Quality challenges are costly and disruptive, particularly if a rescan is initiated by a scientist or pathologist whose valuable time is being diverted away from analysis to address quality issues, and who sits significantly further downstream in the process. It is more cost and time effective to catch these poor quality images as soon as possible.

That’s why we’re excited to introduce you to Proscia’s Automated Quality Control (QC) for Concentriq for Research. Automated QC is an AI-enabled workflow automation application that detects the most frequently-occurring quality artifacts that would necessitate a re-prep or rescan, including those that result both from slide preparation and from the use of WSI scanners. It plugs seamlessly into the research workflow powered by Concentriq for Research. 

Through the power of our AI-enabled Automated QC product, we believe we will positively impact labs globally by:

  • Improving research efficiency. Automated quality control for Concentriq improves research efficiency by catching slides which require a rescan earlier in the workflow and presenting these images to reviewers in a way that reduces overall review time.
  • Improving the quality of research data. Garbage in, garbage out. Reliable research results depend on the quality and consistency of the data that drive it. Automated quality control for Concentriq significantly reduces the possibility of compromised images being introduced into the research process, helping to ensure that the data driving research efforts is consistent and reliable. This also applies to the data sets that support the training and validation of machine learning algorithms, impacting the success of algorithm development and the ultimate performance of these algorithms. 
  • Generate resource reallocation and cost savings. Automated quality control not only detects image artifacts with high precision, it reduces the amount of time required for the quality control process, allowing labs to reallocate time to other, higher-value efforts.
  • Reduce technician burnout: The burden of manual quality control is intensifying as the volume of pathology data continues to grow. Automating this process frees laboratory technicians from a tedious, repetitive task while enabling them to focus on adding more value.

A key element of what makes this automated quality control so powerful is that it’s natively integrated into the routine research workflow through our platform Concentriq. This seamless incorporation of AI into day-to-day operations enables it to deliver value while operating largely behind the scenes.

Pathology at Life Speed

To learn more about Automated Quality Control, the latest release of our Concentriq for Research platform, and the trends and technologies reshaping image-based research, visit our Pathology at Life Speed virtual event. Hear from industry leaders from Charles River Labs, Bristol Myers Squibb, Visiopharm, Digital Pathology Place, and Google Cloud Healthcare and Life Sciences.

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