Data-Driven Methods to Discover Molecular Determinants of Serious Adverse Drug Events

被引:32
作者
Chiang, A. P. [1 ,2 ,3 ]
Butte, A. J. [1 ,2 ,3 ]
机构
[1] Stanford Univ, Dept Med, Sch Med, Stanford Ctr Biomed Informat, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Pediat, Sch Med, Stanford, CA 94305 USA
[3] Lucile Packard Childrens Hosp, Palo Alto, CA USA
关键词
GENOME-WIDE ASSOCIATION; GENE-EXPRESSION PATTERNS; INDUCED CYTOTOXICITY; MONOCLONAL-ANTIBODY; RNA EXPRESSION; VARIANTS; PHARMACOGENETICS; SUSCEPTIBILITY; PROFILES; CHEMOSENSITIVITY;
D O I
10.1038/clpt.2008.274
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The dangers of serious adverse drug reactions (SADRs) are well known to clinicians, pharmacologists, and the lay public. efforts to elucidate the molecular mechanisms behind SADRs have made significant progress through genetics and gene expression measurements. however, as the field of pharmacology adopts the same novel higher-density measurement modalities that have proven successful in other areas of biology, one wonders whether there can be more ways to benefit from the explosion of data created by these tools. The development of analytic tools and algorithms to interpret these biological data to create tools for medicine is central to the field of translational bioinformatics. in this review we introduce some of the types of SADR predictors that are required, and we discuss several databases that are publicly available for the study of SADRs, ranging from clinical to molecular measurements. We also describe recent examples of how bioinformatics methods coupled with data repositories can advance the science of SADRs.
引用
收藏
页码:259 / 268
页数:10
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