Open Targets Platform: new developments and updates two years on.

Denise Carvalho-Silva,Andrew Hercules,David G Hulcoop,Nikiforos Karamanis,Alfredo Miranda,Miguel Pignatelli,Eliseo Papa,Chuangkee Ong,Elaine Mcauley,Ian Dunham,Jeffrey Barrett,Adam Faulconbridge,Luca Fumis,Andrea Pierleoni,Michaela Spitzer,Miguel Carmona,Gareth Peat,Gautier Koscielny

doi:10.1093/nar/gky1133

Abstract

The Open Targets Platform integrates evidence from genetics, genomics, transcriptomics, drugs, animal models and scientific literature to score and rank target-disease associations for drug target identification. The associations are displayed in an intuitive user interface (https://www.targetvalidation.org), and are available through a REST-API (https://api.opentargets.io/v3/platform/docs/swagger-ui) and a bulk download (https://www.targetvalidation.org/downloads/data). In addition to target-disease associations, we also aggregate and display data at the target and disease levels to aid target prioritisation. Since our first publication two years ago, we have made eight releases, added new data sources for target-disease associations, started including causal genetic variants from non genome-wide targeted arrays, added new target and disease annotations, launched new visualisations and improved existing ones and released a new web tool for batch search of up to 200 targets. We have a new URL for the Open Targets Platform REST-API, new REST endpoints and also removed the need for authorisation for API fair use. Here, we present the latest developments of the Open Targets Platform, expanding the evidence and target-disease associations with new and improved data sources, refining data quality, enhancing website usability, and increasing our user base with our training workshops, user support, social media and bioinformatics forum engagement.

Highlights

Drug discovery is a long and costly endeavour characterized by high failure rates
We summarise information on cancer hallmarks [24,25], which are curated by COSMIC [26] and integrated in the Cancer Gene Census [14]
We have introduced filters on the graphical user interface (GUI) to allow for targets to be selected based solely on their properties and facilitate prioritisation of the most promising targets for downstream analysis

Summary

Introduction

Drug discovery is a long and costly endeavour characterized by high failure rates. Failure often occurs at the later stages of the drug discovery pipeline and the reasons for the low success are largely twofold: lack of safety and/or lack of efficacy. The Open Targets Platform capitalises on publicly available databases to create a virtuous cycle where we add value to the original data by computing, scoring and ranking integrated target-disease associations [3], linking these associations back to the underlying evidence and its provenance.

Results

Conclusion