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Molecules under a microscope, purple

Advancing AI-Powered Sample Management: Automating Sample Registration through Imaging and Data Extraction


Publications & Posters

Clinical trial sample management can be challenging to automate due to the diversity of tube types, labels, and the information on these labels, which may be printed and/or handwritten. Combining sample sets from multiple clinical trials increases complexity, as different data elements are required based on trial type, therapeutic area, and specific sponsor requirements. The tubes and labeling method chosen must be suitable for all stakeholders associated with the trial, including clinical sites, central labs, and specialty labs, many of which may be lacking the tools needed to use pre-barcoded labels without human readable information.

This creates challenges for the central laboratories and repositories which must catalogue the data in standardized electronic formats that align with the required formats and ontology of diverse sponsor CTMS systems. Learn more by downloading our poster.

Advancing AI-Powered Sample Management: Automating Sample Registration through Imaging and Data Extraction