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Clinical and biological data integration for biomarker discovery
Marco D Sorani1, Ward A Ortmann, Erik P Bierwagen
1Genentech Inc, 1 DNA Way, South San Francisco, CA 94080, USA. sorani.marco@gene.com
Drug Discovery Today
|June 19, 2010
Summary
Integrating diverse clinical and biological data enhances biomarker discovery for clinical trials. This strategy aids in understanding disease variations and developing predictive biomarkers.
Area of Science:
- Biomedical informatics
- Clinical trial methodology
- Genomics and proteomics
Background:
- Biomarker discovery is crucial for improving clinical trial success rates.
- Integrating high-throughput biological data with clinical data presents challenges.
- Existing data integration tools are evolving for complex biomedical datasets.
Purpose of the Study:
- To present a data integration strategy for combining clinical and biological data.
- To facilitate biomarker discovery and exploration of disease heterogeneity.
- To support data analysis, storage, and access for research.
Main Methods:
- Developed an integrated repository combining a clinical and biological database.
- Implemented a wiki interface for data access and management.
- Integrated parameters from clinical trials with genetic, gene expression, and protein data.
Main Results:
- Demonstrated the utility of the integrated data system.
- Provided examples of exploring disease heterogeneity using integrated data.
- Showcased the development of predictive biomarkers through data integration.
Conclusions:
- Data integration strategies are essential for advancing biomarker discovery.
- Integrated repositories improve the analysis of complex clinical and biological data.
- This approach supports the development of more effective clinical trials and personalized medicine.