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Enabling Precision Medicine in Cancer Care Through a Molecular Data Warehouse: The Moffitt Experience
Author(s) -
Steven A. Eschrich,
Jamie K. Teer,
Phillip Reisman,
Erin M. Siegel,
Chandan Challa,
Patricia Lewis,
Katherine Fellows,
Everin Malpica,
Rodrigo Carvajal,
Guillermo Gonzalez-Calderon,
Scott Cukras,
Miguel Betin-Montes,
Garrick Aden-Buie,
Melissa Avedon,
Daniel Manning,
Aik Choon Tan,
Brooke L. Fridley,
Travis Gerke,
Mattias Van Looveren,
Amilcar Blake,
Jennifer Greenman,
Dana E. Rollison
Publication year - 2021
Publication title -
jco clinical cancer informatics
Language(s) - English
Resource type - Journals
ISSN - 2473-4276
DOI - 10.1200/cci.20.00175
Subject(s) - data warehouse , precision medicine , informatics , health informatics , computer science , data science , health informatics tools , translational research , health care , precision oncology , knowledge management , medicine , database , engineering , political science , pathology , law , electrical engineering
PURPOSE The use of genomics within cancer research and clinical oncology practice has become commonplace. Efforts such as The Cancer Genome Atlas have characterized the cancer genome and suggested a wealth of targets for implementing precision medicine strategies for patients with cancer. The data produced from research studies and clinical care have many potential secondary uses beyond their originally intended purpose. Effective storage, query, retrieval, and visualization of these data are essential to create an infrastructure to enable new discoveries in cancer research.METHODS Moffitt Cancer Center implemented a molecular data warehouse to complement the extensive enterprise clinical data warehouse (Health and Research Informatics). Seven different sequencing experiment types were included in the warehouse, with data from institutional research studies and clinical sequencing.RESULTS The implementation of the molecular warehouse involved the close collaboration of many teams with different expertise and a use case–focused approach. Cornerstones of project success included project planning, open communication, institutional buy-in, piloting the implementation, implementing custom solutions to address specific problems, data quality improvement, and data governance, unique aspects of which are featured here. We describe our experience in selecting, configuring, and loading molecular data into the molecular data warehouse. Specifically, we developed solutions for heterogeneous genomic sequencing cohorts (many different platforms) and integration with our existing clinical data warehouse.CONCLUSION The implementation was ultimately successful despite challenges encountered, many of which can be generalized to other research cancer centers.

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