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Description

Next-generation sequencing (NGS) based genomic tests have been rapidly adopted for diagnostic use. Results from NGS assays are not confined to a single biomarker but produce a multitude of data points , this poses a technical challenge in terms of data collection, storage and reporting. A novel informatics solution is required to manage such complex clinical data that allows integration capabilities with medical and clinical research applications within Memorial Sloan Kettering Cancer Center.

Learning Objective 1: To architect a comprehensive NGS assay agnostic solution to store, facilitate review, and manage genomic test results.

Authors:

Aijazuddin Syed (Presenter)
Memorial Sloan Kettering Cancer Center

Anoop Balakrishnan, Memorial Sloan Kettering Cancer Center
Aaron Dack, Memorial Sloan Kettering Cancer Center
John Ziegler, Memorial Sloan Kettering Cancer Center
Shruti Madur, Memorial Sloan Kettering Cancer Center
Jack Birnbaum, Memorial Sloan Kettering Cancer Center
Jason Hwee, Memorial Sloan Kettering Cancer Center
Meera Prasad, Memorial Sloan Kettering Cancer Center
Mustafa Syed, Memorial Sloan Kettering Cancer Center
Mohammad Haque, Memorial Sloan Kettering Cancer Center
Zhen Liu, Memorial Sloan Kettering Cancer Center
Sumit Middha, Memorial Sloan Kettering Cancer Center
Ryan Ptashkin, Memorial Sloan Kettering Cancer Center
Gowtham Jayakumaran, Memorial Sloan Kettering Cancer Center
Rana Satshil, Memorial Sloan Kettering Cancer Center
Anita Bowman, Memorial Sloan Kettering Cancer Center
Yun-Te Lin, Memorial Sloan Kettering Cancer Center
Angela Brannon, Memorial Sloan Kettering Cancer Center
Michael Berger, Memorial Sloan Kettering Cancer Center
Ahmet Zehir, Memorial Sloan Kettering Cancer Center

Presentation Materials:

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