May 2023 - QuartzBio

Duration: 30 minutes

Register to Join the Webinar:

Summary:

“Sample tracking and reconciliation are so much easier when all information around sample status, consent, and location are in one place.”
–Director of Biomarker Operations, QuartzBio Client Company N

Watch our webinar to learn how our clients, representing major biopharmas and biotechnology companies, have eliminated tedious data management processes and costly delays with the QuartzBio^® virtual Sample Inventory Management SaaS solution.

QuartzBio’s Adam Brown, PhD, demonstrates new capabilities of our technology, enabling teams to:

Track samples across every stage of their lifecycle with dynamic reports comparing actual and expected sample status
Proactively monitor sample stability and consent expiration with automated notifications
Quickly and accurately identify samples to ship for testing using intuitive Sample Ship List generator
Report on portfolio-level metrics and vendor and site performance across all clinical programs, including closed and active studies, to inform future planning

Adam also shows QuartzBio’s reimagined user interface*, which empowers teams to gain insights efficiently without requiring data expertise. Whether you are a current user or learning about the technology for the first time, you will learn new ways to immediately begin streamlining your work.

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*Current QuartzBio Users: Questions about when you can expect rollout of the new user interface for your account? Contact us!

AI/ML can be a powerful, error-reducing tool for managing clinical sample data as well as biomarker data.

AI/ML-based tools should not replace human judgment, particularly for insight generation, at least until AI/ML-based tools are extensively and rigorously validated (as any piece of critical software would be). Furthermore, regulatory compliance and data privacy are of utmost importance and must be considered when building and using solutions that leverage generative AI frameworks.

However, near-term applications of AI/ML can dramatically improve any tedious process involving a human inspecting data. We list some of these processes in the box below, along with steps we recommend taking to reduce risk in each case.