Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery
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.
Authors
- Ian Dunham (ORCID: https://orcid.org/0000-0003-2525-5598)
- Vivien W. Ho (ORCID: https://orcid.org/0000-0002-2992-0252)
- Daniel Considine (ORCID: https://orcid.org/0009-0008-7769-2195)
- James Hayhurst (ORCID: https://orcid.org/0000-0002-7460-403X)
- Miguel Carmona (ORCID: https://orcid.org/0000-0002-7582-4771)
- David G. Hulcoop (ORCID: https://orcid.org/0000-0003-1323-1759)
- Manuel Bernal Llinares (ORCID: https://orcid.org/0000-0002-7368-180X)
- Helena Cornu (ORCID: https://orcid.org/0009-0003-9388-107X)
- Polina Rusina (ORCID: https://orcid.org/0000-0001-7917-3120)
- Poonam Uniyal (ORCID: https://orcid.org/0000-0002-2779-9647)
- Kirill Tsukanov (ORCID: https://orcid.org/0000-0003-1573-5782)
- Graham McNeill
- Jeremy Schwartzentruber (ORCID: https://orcid.org/0000-0002-6183-2092)
- Juan María Roldán‐Romero (ORCID: https://orcid.org/0000-0002-5651-4313)
- Ellen M. McDonagh (ORCID: https://orcid.org/0000-0001-5806-6174)
- Annalisa Buniello (ORCID: https://orcid.org/0000-0002-4623-8642)
- Javier Ferrer (ORCID: https://orcid.org/0000-0003-4392-2198)
- Irene López
- Maria J. Falaguera (ORCID: https://orcid.org/0000-0002-6635-4982)
- Carlos Cruz-Castillo (ORCID: https://orcid.org/0000-0002-6723-0076)
- Luca Fumis (ORCID: https://orcid.org/0000-0001-6318-057X)
- Maya Ghoussaini (ORCID: https://orcid.org/0000-0002-2415-2143)
- Yakov A. Tsepilov (ORCID: https://orcid.org/0000-0002-4931-6052)
- Ines Smit (ORCID: https://orcid.org/0000-0002-1772-6487)
- Dániel Süveges (ORCID: https://orcid.org/0000-0003-4133-0447)
- David Ochoa (ORCID: https://orcid.org/0000-0003-1857-278X)
- Xiangyu Ge (ORCID: https://orcid.org/0000-0001-5048-8081)
- Ricardo Esteban Martinez Osorio
- Chintan Mehta
- Ehsan Barkhordari
- Tobi Alegbe
- Szymon Szyszkowski
Institutions
- AstraZeneca (United Kingdom) (GB)
- European Bioinformatics Institute (GB)
- Wellcome Sanger Institute (GB)
- Open Targets (GB)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1093/nar/gkae1128
- Citations
- 135
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 48.79
Funders
- Wellcome Trust