Session 2 - Flexible Rigor: How to Use Innovation to Drive Robust Data Management for External Data Sources

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Monday, September 14, 2020: 9:30 AM - 10:15 AM
/ CEU Credits:0.2


Session Chair
Alexis Katsis
Director, Lab Data Management
SCHARP/Fred Hutchinson Cancer Research Center
Alvaro San Martin
Lead Clinical Data Manager
PRA Health Sciences
Heather Sprenger
Laboratory Data Division Chief
Frontier Science Foundation
Sara Aranda
Biomarker Data Specialist
Seattle Genetics


Do you manage a high volume of laboratory or other data from external sources? Does your organization strive to apply standards to ever-shifting external data? Want to learn more about the interface between clinical research and academic research? Join us for a series of fast-paced and dynamic IGNITE talks aimed to introduce innovative solutions to the complex issues surrounding external laboratory data submission and processing. 

In today's fast-paced clinical research environment, new laboratory tests and assays are being developed and validated at an increasingly rapid rate. The introduction of these tests into the clinical trial testing algorithm can often out-pace the research community's ability to determine how to fit laboratory data into existing standards for data management and data models. In this ignite session, we will introduce the latest thinking on how to design flexible data management systems that can handle new and innovative data while maintaining the rigor required by regulatory agencies.

Each talk will focus on a particular aspect of combining flexibility and rigor to meet the evolving needs of laboratory data that has dual uses, such as supporting both clinical trial endpoints and academic research aims. Examples include using nosql database designs to allow for flexibility in input data format and implementing Agile strategies in data management.

This session is designed to minimize presentation and maximize discussion and sharing of best practices so come and learn and share about this ever-changing and evolving space.



1. The learner will be able to identify the key challenges with external data.
2. The learner will be able to develop solutions for overcoming external data transfer challenges.
3. The learner will be able to envision new ways of processing external data.
4. The learner will be able to envision new and efficient solutions for data completeness for external data.


CDM Certification Competencies::
Electronic Data Collection,Processing External Data,Data Query Processing and Tracking

Target Audience:
Study Data Manager,DM Management,Programmer