Leveraging big data to transform target selection and drug discovery

The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and cli...

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Bibliographic Details
Published in:	Clinical pharmacology and therapeutics Vol. 99; no. 3; pp. 285 - 297
Main Authors:	Chen, B, Butte, AJ
Format:	Journal Article
Language:	English
Published:	United States Blackwell Publishing Ltd 01-03-2016 John Wiley and Sons Inc
Subjects:	Biomarkers, Pharmacological Datasets as Topic Drug Discovery - methods Humans Molecular Targeted Therapy - methods Precision Medicine - methods State of the Art
Online Access:	Get full text
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Summary:	The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine.
Bibliography:	National Institute of General Medical Sciences of the National Institutes of Health - No. R01GM079719 ark:/67375/WNG-3KNH2RBM-5 istex:0B6DBD0949D7F3FB850B089DE5F478B1FE7A3C3B ArticleID:CPT318 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-2
ISSN:	0009-9236 1532-6535
DOI:	10.1002/cpt.318