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. 2021 Jan 8;49(D1):D1302-D1310.
doi: 10.1093/nar/gkaa1027.

Open Targets Platform: supporting systematic drug-target identification and prioritisation

David Ochoa  1   2 , Andrew Hercules  1   2 , Miguel Carmona  1   2 , Daniel Suveges  1   2 , Asier Gonzalez-Uriarte  1   2 , Cinzia Malangone  1   2 , Alfredo Miranda  1   2 , Luca Fumis  1   2 , Denise Carvalho-Silva  1   2 , Michaela Spitzer  1   2 , Jarrod Baker  1   2 , Javier Ferrer  1   2 , Arwa Raies  1   2 , Olesya Razuvayevskaya  1   2 , Adam Faulconbridge  1   2 , Eirini Petsalaki  1   2 , Prudence Mutowo  2   3 , Sandra Machlitt-Northen  2   3 , Gareth Peat  1   2 , Elaine McAuley  1   2 , Chuang Kee Ong  1   2 , Edward Mountjoy  2   4 , Maya Ghoussaini  2   4 , Andrea Pierleoni  1   2 , Eliseo Papa  2   5 , Miguel Pignatelli  1   2 , Gautier Koscielny  2   3 , Mohd Karim  2   4 , Jeremy Schwartzentruber  2   4 , David G Hulcoop  2   3 , Ian Dunham  1   2   4 , Ellen M McDonagh  1   2
Affiliations

Open Targets Platform: supporting systematic drug-target identification and prioritisation

David Ochoa et al. Nucleic Acids Res. .

Abstract

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target-disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive.

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Figures

Figure 1.
Figure 1.
Overview of the Open Targets Platform. (A) The Platform data model includes the entities targets, diseases and drugs. The relationships between the three entities is shown. (B) Annotation of biomedical entities is provided from 26 underlying data sources. (C) The target identification and prioritisation framework is based on evidence from 20 evidence sources providing target–disease relationships. EFO expansion allows for capture of further associations between targets and diseases/phenotypes. For each target–disease association, the underlying data sources that provide evidence are scored, and an overall scoring ranks targets associated with the disease. Targets are further prioritised based on additional key attributes including tractability, safety and expression. (D) Platform data is accessible via a user interface or programmatically via the EMBL-EBI FTP server, API endpoints or as downloads via Google Cloud. Abbreviations: D, disease/phenotype; Dr, drug; EFO, Experimental factor ontology; T, target.
Figure 2.
Figure 2.
Post-marketing pharmacovigilance analysis for Pazopanib. Significant adverse events associated with Pazopanib (CHEMBL477772), based on systematic analysis of all available FDA Adverse Event Reporting System. Analysis is displayed in the Open Targets Platform for all drugs with available data.
Figure 3.
Figure 3.
Target - disease evidence in the Open Targets Platform. Data sources are grouped by data type—left. Unique validated evidence available in each of the platform releases since April 2016 (16.04)—middle. Relevant changes in the most recent period are annotated in further detail—right. A full list of the data sources with references is found in Supplementary Table S2.
Figure 4.
Figure 4.
Enhanced user interface and new functionality. Platform interface redesign for PTGS2 target profile page. (A) Identifiers and links to other resources are provided at the top of the page. Target information widgets outline the available data (in blue). By clicking on a widget, the user is taken to that section. Sections can be rearranged by the user, allowing them to personalise their experience. (B) The ‘Known drugs’ widget takes the user to a sortable and filterable table including information on clinical candidates or approved drugs, sourced from ChEMBL (12). (C) The ‘Tractability’ section provides a druggability assessment by small molecule, antibody or other modality.
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