Leveraging big data to transform target selection and drug discovery

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 clinical research have dramatically increased the types of data available to the public. The past fe...

Drug Discovery and Big Linked Data

A large part of the daily practice of a researcher doing in vitro Drug Discovery is comparing and manually matching high-quality information from multiple disciplines in the Life and Biomedical Sciences. The Open PHACTS Discovery Platform is an initiative to integrate publicly available data relevant for both academia and the pharmaceutical industry. It integrates numerous datasets including fo...

Drug target ontology to classify and integrate drug discovery data

BACKGROUND One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable,...

Big data analytics for drug discovery

Big Data refers to data sets that are so large and complex that traditional data processing tools and technologies cannot cope with. The process of examining such data to uncover hidden patterns in them is referred to as Big Data Analytics. Drug discovery is related to big data analytics as the process may require the collection, processing and analysis of extremely large volume of structured a...

A New Big-Data Paradigm for Target Identification and Drug Discovery