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Roadmap to a Comprehensive Clinical Data Warehouse for Precision Medicine Applications in Oncology

View Article: PubMed Central - PubMed

ABSTRACT

Leading institutions throughout the country have established Precision Medicine programs to support personalized treatment of patients. A cornerstone for these programs is the establishment of enterprise-wide Clinical Data Warehouses. Working shoulder-to-shoulder, a team of physicians, systems biologists, engineers, and scientists at Rutgers Cancer Institute of New Jersey have designed, developed, and implemented the Warehouse with information originating from data sources, including Electronic Medical Records, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology and Pathology archives, and Next Generation Sequencing services. Innovative solutions were implemented to detect and extract unstructured clinical information that was embedded in paper/text documents, including synoptic pathology reports. Supporting important precision medicine use cases, the growing Warehouse enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information of patient tumors individually or as part of large cohorts to identify changes and patterns that may influence treatment decisions and potential outcomes.

No MeSH data available.


Related in: MedlinePlus

Example of using BioFortis Qiagram interface to formulate and execute precision medicine queries. (A) Query building diagram using Qiagram (simplified for display purposes). (B) The result report can be published for general user access. The report form allows drop-down menu selection for close examination according to individual interests. The example shows a cohort of lung cancer patients presenting with EGFR (Epidermal Growth Factor Receptor) mutation who have been treated with therapeutic agents.
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f2-10.1177_1176935117694349: Example of using BioFortis Qiagram interface to formulate and execute precision medicine queries. (A) Query building diagram using Qiagram (simplified for display purposes). (B) The result report can be published for general user access. The report form allows drop-down menu selection for close examination according to individual interests. The example shows a cohort of lung cancer patients presenting with EGFR (Epidermal Growth Factor Receptor) mutation who have been treated with therapeutic agents.

Mentions: Although BioFortis queries can be constructed to suit a wide variety of specific data requirement, user can also leverage on BioFortis’s reporting capability to access data without immediate programming help. These data reports are based on prebuilt queries to suit general needs of the users. The data reports can easily incorporate filters to help user tailor the retrieval list. Figure 2 depicts an example where patient cohort was assembled with specific gene mutation and tumor diagnosis and treated with therapeutic agents. Users with appropriate IRB clearance are able to access additional information for a given data set, including the capacity to access and interrogate imaged pathology specimens. More advanced users can receive training to build ad hoc queries into their data mart or work closely with honest brokers to bring scientific logic to actual data.


Roadmap to a Comprehensive Clinical Data Warehouse for Precision Medicine Applications in Oncology
Example of using BioFortis Qiagram interface to formulate and execute precision medicine queries. (A) Query building diagram using Qiagram (simplified for display purposes). (B) The result report can be published for general user access. The report form allows drop-down menu selection for close examination according to individual interests. The example shows a cohort of lung cancer patients presenting with EGFR (Epidermal Growth Factor Receptor) mutation who have been treated with therapeutic agents.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5392017&req=5

f2-10.1177_1176935117694349: Example of using BioFortis Qiagram interface to formulate and execute precision medicine queries. (A) Query building diagram using Qiagram (simplified for display purposes). (B) The result report can be published for general user access. The report form allows drop-down menu selection for close examination according to individual interests. The example shows a cohort of lung cancer patients presenting with EGFR (Epidermal Growth Factor Receptor) mutation who have been treated with therapeutic agents.
Mentions: Although BioFortis queries can be constructed to suit a wide variety of specific data requirement, user can also leverage on BioFortis’s reporting capability to access data without immediate programming help. These data reports are based on prebuilt queries to suit general needs of the users. The data reports can easily incorporate filters to help user tailor the retrieval list. Figure 2 depicts an example where patient cohort was assembled with specific gene mutation and tumor diagnosis and treated with therapeutic agents. Users with appropriate IRB clearance are able to access additional information for a given data set, including the capacity to access and interrogate imaged pathology specimens. More advanced users can receive training to build ad hoc queries into their data mart or work closely with honest brokers to bring scientific logic to actual data.

View Article: PubMed Central - PubMed

ABSTRACT

Leading institutions throughout the country have established Precision Medicine programs to support personalized treatment of patients. A cornerstone for these programs is the establishment of enterprise-wide Clinical Data Warehouses. Working shoulder-to-shoulder, a team of physicians, systems biologists, engineers, and scientists at Rutgers Cancer Institute of New Jersey have designed, developed, and implemented the Warehouse with information originating from data sources, including Electronic Medical Records, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology and Pathology archives, and Next Generation Sequencing services. Innovative solutions were implemented to detect and extract unstructured clinical information that was embedded in paper/text documents, including synoptic pathology reports. Supporting important precision medicine use cases, the growing Warehouse enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information of patient tumors individually or as part of large cohorts to identify changes and patterns that may influence treatment decisions and potential outcomes.

No MeSH data available.


Related in: MedlinePlus