title: Leveraging big data to transform target selection and drug discovery.
abstract: 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.
authors.affiliation: Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, California, USA.
authors.forename: B
authors.initials: B
authors.lastname: Chen
authors.affiliation: Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, California, USA.
authors.forename: A J
authors.initials: AJ
authors.lastname: Butte
mesh_terms: D054316:Biomarkers, Pharmacological; D066264:Datasets as Topic; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D058990:Molecular Targeted Therapy / Q000379:methods*; D057285:Precision Medicine / Q000379:methods*
chemical_list: D054316:Biomarkers, Pharmacological