Database Commons

a catalog of worldwide biological databases

MOTIVATION: The Open Targets Platform (https://platform.opentargets.org) is a unique, comprehensive, open-source resource supporting systematic identification and prioritisation of targets for drug discovery. The Platform combines, harmonizes and integrates data from >20 diverse sources to provide target-disease associations, covering evidence derived from genetic associations, somatic mutations, known drugs, differential expression, animal models, pathways and systems biology. An in-house target identification scoring framework weighs the evidence from each data source and type, contributing to an overall score for each of the 7.8M target-disease associations. However, the old infrastructure did not allow user-led dynamic adjustments in the contribution of different evidence types for target prioritisation, a limitation frequently raised by our user community. Furthermore, the previous Platform user interface did not support navigation and exploration of the underlying target-disease evidence on the same page, occasionally making the user journey counterintuitive.
RESULTS: Here, we describe 'Associations on the Fly' (AOTF), a new Platform feature-developed with a user-centred vision-that enables the user to formulate more flexible therapeutic hypotheses through dynamic adjustment of the weight of contributing evidence from each source, altering the prioritisation of targets.
AVAILABILITY AND IMPLEMENTATION: The codebases that power the Platform-including our pipelines, GraphQL API, and React UI-are all open source and licensed under the APACHE LICENSE, VERSION 2.0. You can find all of our code repositories on GitHub at https://github.com/opentargets and on Zenodo at https://zenodo.org/records/14392214. This tool was implemented using React v18 and its code is accessible here: (https://github.com/opentargets/ot-ui-apps). The tools are accessible through the Open Targets Platform web interface (https://platform.opentargets.org/) and GraphQL API (https://platform-docs.opentargets.org/data-access/graphql-api). Data is available for download here: (https://platform.opentargets.org/downloads) and from the EMBL-EBI FTP: (https://ftp.ebi.ac.uk/pub/databases/opentargets/platform/).

The Open Targets Platform (https://platform.opentargets.org) is a unique, open-source, publicly-available knowledge base providing data and tooling for systematic drug target identification, annotation, and prioritisation. Since our last report, we have expanded the scope of the Platform through a number of significant enhancements and data updates, with the aim to enable our users to formulate more flexible and impactful therapeutic hypotheses. In this context, we have completely revamped our target-disease associations page with more interactive facets and built-in functionalities to empower users with additional control over their experience using the Platform, and added a new Target Prioritisation view. This enables users to prioritise targets based upon clinical precedence, tractability, doability and safety attributes. We have also implemented a direction of effect assessment for eight sources of target-disease association evidence, showing the effect of genetic variation on the function of a target is associated with risk or protection for a trait to inform on potential mechanisms of modulation suitable for disease treatment. These enhancements and the introduction of new back and front-end technologies to support them have increased the impact and usability of our resource within the drug discovery community.

The Open Targets Platform (https://platform.opentargets.org/) is an open source resource to systematically assist drug target identification and prioritisation using publicly available data. Since our last update, we have reimagined, redesigned, and rebuilt the Platform in order to streamline data integration and harmonisation, expand the ways in which users can explore the data, and improve the user experience. The gene-disease causal evidence has been enhanced and expanded to better capture disease causality across rare, common, and somatic diseases. For target and drug annotations, we have incorporated new features that help assess target safety and tractability, including genetic constraint, PROTACtability assessments, and AlphaFold structure predictions. We have also introduced new machine learning applications for knowledge extraction from the published literature, clinical trial information, and drug labels. The new technologies and frameworks introduced since the last update will ease the introduction of new features and the creation of separate instances of the Platform adapted to user requirements. Our new Community forum, expanded training materials, and outreach programme support our users in a range of use cases.