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Personalized medicine using DNA biomarkers: a review
Andreas Ziegler1, Armin Koch, Katja Krockenberger
1Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Maria-Goeppert-Str. 1, 23562 Lübeck, Germany. ziegler@imbs.uni-luebeck.de
Human Genetics
|July 4, 2012
Summary
Biomarkers are crucial for personalized medicine, aiding diagnosis, prognosis, and targeted therapy selection. This review covers DNA biomarkers, tumor biomarkers, and general biomarkers, detailing their validation and clinical trial applications.
Area of Science:
- Biomarker research
- Personalized medicine
- Clinical trial design
Background:
- Biomarkers are increasingly vital for personalized medicine, impacting diagnosis, prognosis, and targeted therapy selection.
- Their applications span pharmacodynamics to treatment monitoring.
- This review focuses on DNA biomarkers, DNA tumor biomarkers, and general biomarkers.
Purpose of the Study:
- To provide a concise review of biomarker terminology, applications, and clinical trial designs.
- To discuss the identification, validation, and interpretation of diagnostic, prognostic, and predictive biomarkers.
- To examine the suitability of clinical trial designs for predictive biomarkers, including validation study designs.
Main Methods:
- Review of current literature on biomarker applications and clinical trial designs.
- Categorization of biomarkers into DNA biomarkers, DNA tumor biomarkers, and general biomarkers.
- Discussion of clinical trial phases for biomarker validation and interpretation of treatment effects.
Main Results:
- Biomarkers are essential for personalized medicine, with diverse applications.
- Diagnostic and prognostic biomarkers require specific clinical trial phases for validation.
- Predictive biomarkers, or companion diagnostics, forecast treatment response and require tailored trial designs.
Conclusions:
- Effective biomarker validation and interpretation are critical for advancing personalized medicine.
- Clinical trial designs must be adapted to suit the specific goals of biomarker research (diagnostic, prognostic, predictive).
- Understanding biomarker profiles is key to interpreting treatment effects, especially with complex datasets.
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