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Delivering systems pharmacogenomics towards precision medicine through mathematics
Yaqun Wang1, Ningtao Wang, Jianxin Wang
1Center for Statistical Genetics, Pennsylvania State University, Hershey, PA 17033, USA.
Advanced Drug Delivery Reviews
|March 26, 2013
Summary
A new statistical framework merges systems biology and pharmacogenomics to identify dynamic genes influencing drug response. This approach aids in discovering novel drug targets and genetic biomarkers for personalized medicine.
Area of Science:
- Pharmacology and Systems Biology
- Genomics and Bioinformatics
Background:
- Post-genomic era pharmacology requires advanced methods beyond traditional genomics.
- Identifying novel drug targets necessitates understanding genetic variation in drug response pathways.
Purpose of the Study:
- To present a statistical framework merging systems biology and pharmacogenomics.
- To accelerate the identification of dynamic genes and biomarkers for drug response.
Main Methods:
- Developed a statistical framework for mapping dynamic genes.
- Incorporated pharmacokinetic and pharmacodynamic pathways.
- Integrated genomic, proteomic, and metabolic data with pharmacogenetic information.
Main Results:
- The framework maps dynamic genes impacting drug response.
- It elucidates mechanistic and therapeutic differences in drug response.
- Enabled characterization of novel therapeutic targets and genetic biomarkers.
Conclusions:
- The proposed framework facilitates a shift towards systems approaches in pharmacogenomics.
- It aids in the discovery and utilization of novel biomarkers and drug targets.
- Supports personalized medicine through a deeper understanding of drug response.
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