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Challenges and opportunities for oncology biomarker discovery

Avisek Deyati1, Erfan Younesi, Martin Hofmann-Apitius

  • 1Knowledge Management, Merck Serono, 250 Frankfurterstrasse, Darmstadt 64293, Germany.

Drug Discovery Today
|January 3, 2013
PubMed

Insights

Drug discovery is accelerating biomarker discovery due to companion diagnostics and regulatory needs. This review explores current technologies and future integrative modeling for biomarker prediction.

Area of Science:

  • Biomedical research
  • Drug discovery
  • Systems biology

Background:

  • Companion diagnostics success and regulatory demands drive novel biomarker discovery.
  • High-throughput technologies generate vast amounts of OMICs data.
  • Knowledge management is crucial for analyzing complex biological data.

Purpose of the Study:

  • To review current biomarker discovery technologies.
  • To highlight challenges and opportunities in knowledge capture for biomarker discovery.
  • To present future perspectives on integrative modeling for biomarker prediction.

Main Methods:

  • Literature review of biomarker discovery technologies.
  • Analysis of knowledge management and systems biology approaches.
  • Discussion of integrative modeling in biomarker prediction.

Main Results:

  • Current biomarker discovery faces challenges in knowledge capture and data integration.
  • High-throughput technologies are advancing biomarker identification.
  • Systems biology and knowledge management offer solutions for OMICs data analysis.

Conclusions:

  • Integrative modeling approaches represent a future trend in biomarker prediction.
  • Effective knowledge capture is essential for leveraging OMICs data.
  • Novel strategies are needed to meet the demands of precision medicine.

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