The Benefits of Digital Pathology with Automated Quality Control for Accelerating Drug Discovery

Digital pathology and computational pathology have become an integral part of the drug discovery and development process and are playing an increasingly important role in R&D and diagnostic labs. These computational pathology solutions use artificial intelligence (AI) to increase the efficiency of lab operations, help organizations drive new breakthroughs and improve diagnostic precision. As digital and computational pathology 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 time consuming for laboratory technicians and pathologists 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. Additionally, artifacts affecting slides may affect the accuracy of diagnosis and research. It is more cost effective and workflow efficient to catch these poor quality images as soon as possible. This webinar explores such technological advances in improving slide and image quality along with the benefits of digital pathology with Automated Quality Control for accelerating drug discovery.

Join this webinar to learn the benefits of digital pathology with automated quality control for accelerating drug discovery.

Speaker

Casey Wahl, Product Manager for AI – Workflow Solutions, Proscia Inc

Casey Wahl is the Product Manager for AI at Proscia. She is responsible for determining the relative priority of the various opportunities and concepts in the company’s backlog/roadmap, market & customer research, product requirements & performance target definition, coordination & collaboration with the AI team in developing specifications and refining targets, engagement and co-management of centers of excellence, study & early adopter sites alongside application specialists, professional services & sales, identifying and executing against product operations/process improvements with the Proscia internal teams, supporting go-to-market asset creation & handoff to product marketing. Prior to Proscia, Casey worked in various product, operations and marketing roles.

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