Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery

• Published in: Nucleic acids research Vol. 53; no. D1; pp. D1467 - D1475
• Main Authors: Buniello, Annalisa, Suveges, Daniel, Cruz-Castillo, Carlos, Llinares, Manuel Bernal, Cornu, Helena, Lopez, Irene, Tsukanov, Kirill, Roldán-Romero, Juan María, Mehta, Chintan, Fumis, Luca, McNeill, Graham, Hayhurst, James D, Martinez Osorio, Ricardo Esteban, Barkhordari, Ehsan, Ferrer, Javier, Carmona, Miguel, Uniyal, Prashant, Falaguera, Maria J, Rusina, Polina, Smit, Ines, Schwartzentruber, Jeremy, Alegbe, Tobi, Ho, Vivien W, Considine, Daniel, Ge, Xiangyu, Szyszkowski, Szymon, Tsepilov, Yakov, Ghoussaini, Maya, Dunham, Ian, Hulcoop, David G, McDonagh, Ellen M, Ochoa, David
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 06.01.2025
• Subjects: Database Issue; Drug Discovery; Humans; Internet; Knowledge Bases; Software
• ISSN: 0305-1048; 1362-4962; 1362-4962
• DOI: 10.1093/nar/gkae1128

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.